JP4151680B2 - Refrigeration cycle monitoring system - Google Patents

Description

  The present invention relates to a technique relating to failure diagnosis and monitoring of equipment such as a compressor of a refrigeration cycle apparatus used in a refrigeration apparatus or an air conditioner, a fluid circuit, a blower and other equipment and devices.

  For fault diagnosis of air conditioners, control data such as sensors, set values, and abnormal signals are taken in, and the operation status sequence for each fault is stored in the microcomputer with operation data such as pressure and temperature. Techniques to do are proposed. See Patent Document 1. On the other hand, many attempts have been made to use Mahalanobis distance, which is a multivariate analysis technique, for failure diagnosis. In the old days, there have been known ones that compare vibration sensor signals with normal ones, refer to Patent Document 2, and recently, use a variety of sensors to find signs of deterioration, refer to Patent Document 3. Yes.

  In the conventional refrigeration cycle apparatus described in Patent Document 4, the liquid refrigerant in the liquid reservoir and the auxiliary tank is set to the same liquid surface level by communicating the liquid reservoir (liquid receiving tank) and the auxiliary tank through a communication pipe. The liquid level is detected by a float type level sensor installed in the auxiliary tank, and the refrigerant leakage is detected depending on whether the detected liquid level in the liquid reservoir is equal to or higher than a predetermined normal liquid level.

  Moreover, in the conventional refrigeration cycle apparatus described in Patent Document 5, a sight glass (flow sight) is attached to a liquid take-out pipe extending from a lower portion of a liquid reservoir (receiver tank), and directed toward the refrigerant liquid flowing in the sight glass. Then, light is emitted from the light emitter, received by the light receiver, and bubbles are mixed into the refrigerant liquid, that is, refrigerant leakage is detected based on the level of the detection signal of the light receiver.

JP-A-2-110242 (FIGS. 4 to 11) JP 59-68643 A (page 23, upper left to upper right column) JP 2000-259222 A (FIGS. 3 to 9) JP 10-103820 A (Claim 1, FIG. 1, FIG. 2, FIG. 4) JP-A-6-185839 (Claim 1, FIG. 1, FIG. 3)

  Attempts to perform fault diagnosis of the operating state of each fault using conventional sensors, set values, control signals such as error signals, and operation data such as pressure and temperature can judge extreme abnormal conditions but have high accuracy. There was a problem of not being a device. For example, even if an alarm signal is to be generated from an alarm means when a measured value exceeds a preset allowable limit value, the focus is only on the threshold value of specific operation data, Because it was impossible to capture complex data changes, it was not possible to detect the possibility of anomaly when a sign of failure appeared.

  In addition, when trying to improve accuracy, it takes too much data, and it is necessary to make judgments assuming various conditions, and it increases costs not only for sensors but also for microcomputer changes each time the target device changes and the capacity of the microcomputer increases. In addition, since the threshold value for failure determination is determined by design values or tests on specific machines, this determination takes a long time, and individual differences between actual machines cannot be taken into consideration, and the possibility of false detection is high.

  In addition, even if a multivariate analysis method is used, it is not possible to determine the threshold value, or a large amount of data is necessary for the countermeasure, so it cannot be put into practical use, and further, the cause of the failure cannot be specified, We were unable to respond quickly to failure monitoring and maintenance.

  Further, the conventional refrigeration cycle apparatus is very expensive because it needs to install a special sensor for specific data in order to measure the mixing of bubbles into the liquid level of the liquid reservoir or the refrigerant liquid flowing out of the liquid reservoir. There was a problem of becoming a device.

  Further, the conventional refrigeration cycle apparatus has a problem that it is difficult to install the existing refrigeration cycle apparatus because a special sensor for necessary data is assembled in the apparatus.

  Further, the conventional refrigeration cycle apparatus detects the refrigerant leak after reaching the limit at which the refrigerant leakage amount can maintain the normal cooling capacity, and cannot detect the refrigerant leak at an early stage and take countermeasures before reaching the limit. There was a problem.

  In addition, since the conventional refrigeration cycle apparatus tries to detect the refrigerant leak with specific data, there is a problem in that it is impossible to determine the abnormality between the refrigerant leak and another abnormality.

  The present invention has been made in order to solve the above-described problems, and the object of the present invention is based on a calculated state quantity including the entire apparatus such as a refrigeration cycle in addition to a single unit of a compressor, for example, It is to obtain what makes it possible to detect early signs of failure. It is another object of the present invention to obtain a practical product that absorbs actual machine individual differences in failure determination, can easily set threshold values, and can be easily used at any time and anywhere. Another object of the present invention is to obtain a technology that can specify a cause of failure in failure determination and has high accuracy and high reliability.

  Another object of the present invention is to obtain an inexpensive and reliable refrigeration cycle apparatus or diagnosis and monitoring technology that can detect an abnormality in the refrigeration cycle such as refrigerant leakage by using only information of general temperature measurement means and pressure measurement means. It is said. Another object of the present invention is to obtain a refrigeration cycle apparatus that can be easily applied to an existing refrigeration cycle apparatus or a technique for diagnosis and monitoring.

  Further, the present invention not only obtains a refrigeration cycle apparatus or a diagnosis or monitoring technique that can detect abnormalities at an early stage by identifying each abnormality such as refrigerant leakage by utilizing the correlation of a plurality of data, and also predicting The purpose is to obtain a practical one that can.

The refrigeration cycle monitoring system of the present invention includes a refrigeration cycle in which a compressor, a condenser, an expansion means, and an evaporator are connected by piping to form a fluid circuit through which refrigerant flows, and a flow path from the discharge side of the compressor to the expansion means Between the expansion means and the suction side of the compressor. The high-pressure measurement means is a high-pressure measurement means that measures the high pressure of the refrigerant Low pressure measuring means for measuring low pressure that is the pressure of the refrigerant at any position in the flow path, low pressure measuring means that is at least one of evaporating temperature measuring means for measuring the saturation temperature of the low pressure, and the condenser to the expansion means Liquid temperature measuring means for measuring the refrigerant temperature at any position in the flow path to reach, compression temperature measuring means for measuring the discharge temperature at any position in the flow path from the compressor to the condenser, and compression from the evaporator Measured by the refrigerant temperature measuring means, which is at least one of the intake temperature measuring means for measuring the intake temperature at any position in the flow path leading to the flow path, the high pressure side measuring means, the low pressure side measuring means, and the refrigerant temperature measuring means A calculation means for calculating a state quantity having characteristics of a plurality of measurement values, which are aggregates having a distribution based on at least a deviation of the measurement values and a calculation value calculated from the measurement values; and a refrigeration cycle The refrigeration is performed by comparing a state quantity calculated from a measured value that has been measured or is classified so as to obtain an abnormal state when it is determined to be an abnormal state with a set initial state quantity. A state quantity storage means that is classified as a degree of abnormality of the abnormal state of the cycle and is set as a plurality of state quantities, and an operation state quantity calculated from an operation measurement value measured by the measurement means during operation A comparison unit that compares a plurality of state quantities stored in the period state quantity or the state quantity storage means, and a wire that transmits at least one of the operation measurement value, the operation state quantity, and the comparison result compared by the comparison means Or a transmission means formed wirelessly, and the state quantity calculated and set by the calculation means has different settings depending on the change in the outside air temperature, the detected high pressure range, and the like.

  The present invention diagnoses an operation state from a general measured amount of fluid, and it is possible to detect an abnormality and predict an abnormal time by a simple and reliable diagnosis. In addition, the present invention provides a diagnostic technique that is accurate, practical, and capable of specifying the cause of failure. In the present invention, monitoring of the equipment and the refrigeration cycle is reliably performed.

Embodiment 1 FIG.
The configuration of the first embodiment of the present invention will be described with reference to FIGS. FIG. 1 is an overall conceptual diagram of the present invention, in which 1 is a refrigeration cycle apparatus such as a refrigerator or an air conditioner, 2 is an operation state quantity of the refrigeration cycle apparatus 1, and a detection result is calculated, stored, and displayed. Alternatively, a board or a microcomputer with a built-in device for transmitting / receiving data to / from the warning lamp and the like, 3 is a means for communicating with the outside such as a telephone line, a LAN line, and wireless, 4 is a remote of the refrigeration cycle apparatus 1 A remote monitoring room 5 for centralized management such as monitoring and control, 5 is a computer installed in the remote monitoring room 4 as a remote monitoring means having a display and calculation function for transmitting and receiving data to and from the refrigeration cycle apparatus 1. A display device such as a liquid crystal display provided in the refrigeration cycle apparatus 1, 7 is an input device such as a touch panel or a button, and 8 is a warning label for notifying the occurrence of an abnormality. Flop 9 is a speaker that generates a sound for notifying an abnormal occurrence. The refrigeration cycle apparatus 1 such as a refrigerator or an air conditioner is an air conditioner installed in a building, a refrigerator or an air conditioning system installed in a large store such as a supermarket, a refrigeration / air conditioner such as a small store, or an air conditioner in an apartment house. The remote monitoring room may be a device that monitors a plurality of such facilities, or may monitor individual facilities. Alternatively, it may be connected to a monitoring computer or a monitoring device in each house such as a detached house. Although FIG. 1 shows the case where the display device 6, the input device 7, the warning lamp 8, and the speaker 9 are built in the refrigeration cycle apparatus 1, naturally, all or some of them are refrigeration cycle. Even if the apparatus 1 may be installed outside the apparatus 1 or some of them are not provided, some alternative means, for example, a computer connected to the remote point by the communication means 3 is installed. If you have any, you do not mind.

  FIG. 2 is a block diagram showing details of the refrigeration cycle apparatus 1 of FIG. 1 according to the present invention. 11 is a compressor, 12 is a condenser, 35 is a liquid reservoir, 37 is a supercooling means, 36 is a flow path opening / closing means, 13 Is an expansion means, and 14 is an evaporator, which are connected by a pipe and circulate a refrigerant therein to constitute a refrigeration cycle. One or a plurality of compressors 11, flow path opening / closing means 36, expansion means 13, and evaporators 14 are installed. Condenser 12 is installed in a machine room or outdoors. Built in. 16 is a refrigerant measurement amount detection means for detecting the refrigerant state such as the pressure and temperature of the refrigeration cycle apparatus 1, 16a is a refrigerant high pressure detection means, 16b is a refrigerant low pressure detection means, 38 is a liquid pipe temperature detection means, 61 is a refrigerant discharge temperature detection means, 62 is a refrigerant suction temperature detection means, 41 is a data collection means, 18 is a calculation means for performing various calculations based on detection results of the refrigerant state quantity detection means 16, and 19 is a past calculation. Storage means for storing the result, reference value, etc., 20 is a comparison means for comparing the calculation result with the stored content, 21 is a determination means for making a determination based on the result of the comparison, and 22 is for outputting the determination result to the display means or remotely. It is an output means. FIG. 3 is a Mollier diagram showing the operation of the refrigeration cycle of the refrigeration cycle apparatus. The compression of the refrigeration cycle is such that the abscissa indicates pressure on the enthalpy ordinate and the numbers i to e correspond to those in FIG. A cycle of condensation, expansion and evaporation is shown. Although not shown in FIG. 2, the condenser 12 and the evaporator 14 are provided with an air cooling fan. The compressor 11 is of scroll type, rotary type, reciprocating type, screw type or the like, but most of the compressors are driven by a motor (not shown) directly connected to the compression mechanism inside the casing. ing. This motor includes an induction motor that rotates at a substantially constant speed by commercial power from an AC power source, and a DC brushless motor that changes the rotational speed of the compressor by changing the commercial power to direct current and adjusting the frequency with an inverter. A voltage is applied to the motor that drives the compressor, and a current corresponding to the load flows. The data collection unit 41 outputs not only the physical quantity of the fluid, but also the motor that drives the device that circulates the fluid of the refrigeration cycle apparatus. The current, that is, the amount of electricity that drives the device driving means is also detected and collected as data.

  In FIG. 2, the compound variable calculation processing is performed in the calculation means 18 based on the state quantities such as the pressure and temperature of each part of the refrigeration cycle detected by each detection means and collected by the data collection means 41. Then, storage means 19 in which past data and setting threshold values are stored, comparison means 20 that compares the stored data with the current value, determination means 21 that makes a comprehensive determination based on the comparison result, and output that outputs the determination result The means 22 and the output determination result are displayed on the display means 6 or transmitted to the remote monitoring means 5 for monitoring the driving state at a remote place. In the description of FIG. 1 and FIG. 2, a refrigerant circuit that circulates the refrigerant to perform air conditioning such as heating and cooling, refrigeration and freezing such as a refrigerator and a freezer warehouse, sensors that detect the operating state of the refrigerant circuit, computation, etc. It is described that the microcomputer and the substrates necessary for the control are housed in the refrigeration cycle apparatus, the operation state is measured, calculated, compared, evaluated and judged in this apparatus. However, it may be provided in the vicinity of the refrigeration cycle until it is measured by sensors, and after the calculation 18 may be provided in the remote monitoring room 4.

  The operation of the refrigeration cycle apparatus will be described with reference to FIG. A refrigerant is sealed in the refrigerant circuit of the refrigeration cycle apparatus 1, the refrigerant is compressed and pressurized by the compressor 11, and the high-temperature and high-pressure refrigerant is cooled by a liquid cooling system such as an air cooling fan or water cooling (see FIG. The refrigerant is cooled and liquefied by an expansion valve 13 to become a low-temperature and low-pressure refrigerant and evaporated by the evaporator 14 by heat exchange with an air cooling fan or a liquid heat medium (not shown) such as water. It is heated and vaporized. The vaporized refrigerant returns to the suction side of the compressor 11 and moves again to the compression and pressurization step. At this time, the air or liquid exchanged with the refrigerant in the condenser 12 is heated at a high temperature and used as a heating heat source or exchanged with the outside air, and the air or liquid exchanged with the refrigerant in the evaporator 14 has a low temperature. It is cooled and used as a cooling or refrigeration / freezing heat source or exchanges heat with the outside air. Refrigerants used include natural refrigerants such as carbon dioxide, hydrocarbons, and helium, refrigerants that do not contain chlorine, such as alternative refrigerants such as HFC410A and HFC407C, or fluorocarbon refrigerants such as R22 and R134a that are used in existing products. The fluid equipment such as the compressor that circulates the refrigerant is of various types such as reciprocating, rotary, scroll, and screw. Note that the abnormality determination of the present invention can be realized not only for new products but also for existing products that have already been in operation by adding a deficient sensor later.

  The configuration of the data collection means 41 to the output means 22 shown in FIG. 2 is a description of a method in which each set of means is built in the refrigeration cycle apparatus 1 as a substrate. A function up to the means 22 may be provided in the computer 5 provided in the remote monitoring room 4 of FIG. Further, both the refrigeration cycle apparatus 1 and the computer 5 provided in the remote monitoring room 4 may share functions or coexist. For example, it is possible to rewrite the data in the storage means in the refrigeration cycle apparatus 1 having both storage means 19 and having a small storage area with the corresponding data in the computer 5 having a large storage capacity, and want to use different data depending on the season. This is an effective method. Moreover, the function of each means should just be able to satisfy | fill the function even if it arrange | positions in either the refrigeration cycle apparatus 1 main body or the remote monitoring room 4. In addition, although it demonstrates as the computer 5 provided in the remote monitoring room 4, since this is convenient for centralized monitoring of several apparatuses, when it targets a specific apparatus, it is for movement like a mobile. Of course, it is possible to use a monitoring device so that the service person can constantly monitor while moving, or a simple monitoring device in the home.

  Next, the diagnosis and abnormality determination operation of the refrigeration cycle apparatus according to an example of the present invention will be described with reference to FIG. The measured amount collected by each detecting means of the refrigeration cycle apparatus is a measured amount of each part pressure and temperature of the refrigerant flowing through the refrigerant circuit necessary for grasping the operating state of the refrigeration cycle. The measured refrigerant amount detecting means 16 Various data are detected and collected by the data collecting means 41. In addition, in order to grasp the operating state of the refrigeration cycle, in FIG. 2, the compressor 11, the condenser 12, the expansion means 13, and the evaporator 14 are connected by piping to form a refrigeration cycle. The refrigerant is circulated, and the high pressure measuring means for measuring the high pressure of the refrigerant pressure at any position in the flow path from the discharge side of the compressor 11 of the refrigeration cycle apparatus 1 to the expansion means 13 or the saturation temperature of the high pressure is measured. A high pressure side measuring means 16a that is a condensing temperature measuring means, and a low pressure measuring means that measures the low pressure that is the refrigerant pressure at any position in the flow path from the expansion means 13 to the suction side of the compressor 11, or a low pressure saturation. The low pressure side measuring means 16b which is an evaporation temperature measuring means for measuring the temperature, and the liquid temperature measuring means 38 or pressure for measuring the temperature at any position in the flow path from the condenser 12 to the expansion means 13. The suction temperature measurement unit 61 measures the temperature at any position in the flow path from the machine 11 to the condenser 12 or the temperature at any position in the flow path from the evaporator 14 to the compressor 11. Refrigerant temperature measuring means which is means 62 and, in other words, measuring means for measuring the physical quantity of the refrigerant is provided in each part. It is easy to use these measuring means normally arranged in the refrigeration cycle, but they may be externally attached later if necessary.

  A state quantity that represents the characteristics of the data can be calculated from the measured values of the high-pressure side measuring means, the low-pressure side measuring means, and the refrigerant temperature measuring means. For example, a composite variable is calculated by the calculation means 18, and a plurality of measurement values of each measurement means are used as a composite variable, or a characteristic calculation value is obtained from a measured amount and used as a composite variable, and the calculation value is stored together with the measurement value. It is memorized by means 19. The past value stored in the storage means can be compared with the current measured value or calculated value, and an abnormality in the refrigeration cycle can be determined based on the comparison result. The pressure is measured using a pressure converter that converts the refrigerant pressure into an electrical signal, and the temperature is measured using temperature detection means such as a thermistor or a thermocouple. The pressure and temperature measurement positions are configured so that the refrigeration cycle operation status can be grasped more accurately by changing the position and adding the measurement position according to the configuration and operating characteristics of the target refrigeration cycle. Also good. The measurement of the state quantity is performed at a certain interval, for example, a minute unit such as one minute or a time unit interval, and information is transmitted to the data collection unit 41.

  The measurement of the physical quantity of the refrigerant by each measuring means is measured in a state where it is mutually related to the fluid that is the refrigerant that flows through the refrigerant circuit that is the fluid circuit from which data is collected. The data measured in the band is used. Note that state quantities are obtained by calculating from a plurality of measured data. In order to handle each piece of measurement data as data in the same column, calculation processing is performed at the same measurement interval, and calculation processing is performed at regular time intervals. Therefore, the state quantity is obtained from the related data.

  Next, a method of combining each measured data into a composite variable, and a method of detecting an abnormality in a system such as a device such as a compressor or a refrigeration cycle using the composite variable will be described. As an example of a method of processing a plurality of measurement quantities, a generally known Mahalanobis distance is given. The Mahalanobis distance is, for example, described in “Multivariate analysis that can be easily understood” issued by Tokyo Library Co., Ltd. on October 26, 1992, and is a technique used in the field of multivariate analysis. Hereinafter, a method for detecting an abnormality of a compressor or the like using the Mahalanobis distance will be described. Except for the final stage that clearly appears on the surface, such as leakage, deterioration, and failure, the operating quantities, data, and phenomena that appear on the surface are more complex in the initial stage. This is a combination of complex factors such as data, and the complex structure may be simplified by grasping them in a multiple rather than a unified way, and a technique called multivariate analysis is adopted. ing. However, simply using multivariate analysis cannot find the desired result, for example, an early stage defect. In the present invention, a practical diagnostic technique can be obtained from the correlation between variables.

  The total number of each measurement data representing the refrigeration cycle operation state is set to m, each measurement amount or state amount is assigned to a variable X, and m operation state amounts X1 to Xm are defined. Next, a normal operating state as a reference, for example, a state in which the air conditioner is installed and tested and confirmed to be normal, or an operating state amount of X1 to Xm during operation of a device that outputs smoothly set capability Collect the reference data for a total of n (2 or more) combinations.

  And each average value mi and standard deviation (sigma) i (reference | standard variation degree) of X1-Xm are calculated | required by the following (1) Formula and (2) Formula. Note that i is the number of items (the number of parameters), and here, it is set to 1 to m and indicates a value corresponding to X1 to Xm. Here, the standard deviation is taken as the square root of the expected value of the square of the difference between the variable and its average value.

  Next, the original X1 to Xm are converted into X1 to Xm by the following equation (3) using the average value mi and the standard deviation σi, which are state quantities that are calculated and indicate characteristics. That is, the variable is converted into a random variable having an average of 0 and a standard deviation of 1. In the following equation (3), j takes any value from 1 to n and corresponds to each of n measured values.

  Next, in order to perform analysis with the data standardized to 0 for the variables and 1 for the variance, a correlation covariance matrix X1 to Xm as a variance covariance matrix, that is, a correlation matrix R indicating the relationship between the variables and an inverse matrix of the correlation matrix R-1 is defined by the following equation (4). In the following equation (4), k is the number of items (number of parameters), and here it is m. Moreover, i and p show the value in each item, and take the value of 1-m here.

  After such calculation processing, the Mahalanobis distance, which is a state quantity indicating the feature, is obtained based on the following equation (5). In the equation (5), j takes any value from 1 to n and corresponds to each of n measured values. Further, k is the number of items (number of parameters), which is m here. Further, a11 to akk are coefficients of the inverse matrix of the correlation matrix of the above equation (4), and the Mahalanobis distance is about 1 in the reference data, that is, in the normal operation state, and is within 4 or less. The distance increases and the distance increases in accordance with the degree of abnormality (degree of departure from normal). Although the dissimilarity required for cluster analysis, that is, the Mahalanobis distance is used here, a multivariate analysis method such as standardized Euclidean distance, Minkowski distance, or other shortest distance method or longest distance method may be used. .

  Here, the concept of Mahalanobis distance and the calculation flow will be described with reference to FIGS. FIG. 4 illustrates the relationship with the Mahalanobis distance on the horizontal axis and the appearance rate on the vertical axis. As shown in the figure, it is possible to determine the positional relationship of the computed Mahalanobis distance with respect to the reference data group regardless of the number of parameters, and to confirm the failure state of the refrigeration cycle apparatus. In the reference data group, the Mahalanobis distance has an average value of about 1, and is 4 or less even when variation is considered.

  FIG. 5 is a flowchart for calculating the Mahalanobis distance. First, the average value of the reference data, the standard deviation, the inverse matrix of the correlation matrix, and the number of items are set (ST1), and the state quantity measured and calculated during the refrigeration cycle operation is acquired (ST2). Next, these acquired data are normalized based on the above-described equation (3) (ST3), and then the Mahalanobis distance is set to 0 as an initial value, and counters i and j are set to the initial value 1 (ST4). ). Then, the counters i and j are changed until the number of items k is reached, and the Mahalanobis distance is calculated by repeating the calculation of equation (5) in ST5 to ST7 and the integral value obtained in ST8 is divided by the number k of items. To obtain the Mahalanobis distance D2.

  Next, the refrigerant leakage diagnosis will be described with reference to FIG. First, the amount of refrigerant in the refrigeration cycle will be described. For example, in a refrigeration system used for cooling for a supermarket showcase, the showcase is installed in the food department, but the number, size, type, and arrangement vary depending on the store where it is installed, and are thus arranged in the showcase. The internal volume of the evaporator 14 is also different. Moreover, the installation location of the compressor 11, the condenser 12, and the liquid reservoir 35 also differs depending on the store structure. For example, the compressor 11, the condenser 12 and the liquid reservoir 35 may be installed on the back of the food department or on the roof, thereby compressing the evaporator 14 and the compressor. The lengths of the pipes forming the control tower cycle are different between the machine 11, the condenser 12, and the liquid reservoir 35. In order for the refrigeration cycle to exhibit the specified performance, an amount of refrigerant suitable for the internal volume of the refrigeration cycle is required, and the amount of refrigerant required for the entire refrigeration cycle differs depending on the internal volume of the evaporator and the length of the piping. Therefore, the refrigerant of the refrigeration system is filled after installing the equipment on site. In addition, the amount of refrigerant required in the refrigeration cycle varies depending on the state of the refrigeration cycle, and the state of the refrigeration cycle varies depending on the operating conditions of the load side equipment such as the outside air temperature and showcase. Regardless of the operating conditions, a little more refrigerant is charged so that the required amount of refrigerant is always distributed to each component such as a condenser and evaporator, and each component of the refrigeration cycle has the appropriate amount of refrigerant. After that, the excess refrigerant accumulates in the liquid reservoir 35.

  Of the refrigerant filled in the refrigeration cycle, the amount of refrigerant required by each component device changes from moment to moment depending on the state of the refrigeration cycle, and thereby the amount of excess refrigerant in the liquid reservoir 35 also changes. And if the refrigerant | coolant amount which each component apparatus of a refrigerating cycle requires becomes large enough with respect to a refrigerant | coolant filling amount, it will become impossible to have a surplus refrigerant | coolant in the liquid reservoir 35, and two phases with which gas is mixed from the liquid reservoir 35 The refrigerant will flow out. If the gas is mixed to some extent, it is liquefied by heat exchange in the liquid pipe heat exchange means 37b via the branch expansion means 37a in the supercooling means 37 (including cooling of the liquid piping by the ambient air). Therefore, it is not important, but when the amount of gas mixed into the refrigerant flowing out of the liquid reservoir 35 further increases, the two-phase refrigerant flows into the expansion means 13, and the necessary cooling capacity cannot be secured. It falls into an uncooled state, the ambient air temperature of refrigerated or frozen foods becomes high, and the quality of the foods deteriorates.

  In order to prevent such a situation, a liquid reservoir 35 for storing surplus refrigerant is installed, and the refrigerant is sealed in anticipation of fluctuations in the refrigerant amount required by the refrigeration cycle. However, there may be a refrigerant leak that causes the refrigerant to escape from the refrigeration cycle due to changes over time such as poor construction at the beginning of installation or loosening of the connection between the pipe and the valve due to vibration. When the refrigerant leaks, the refrigerant in the refrigeration cycle gradually decreases and finally falls into an uncooled state.

  However, since the refrigerant leaks from a minute pipe gap, there are many slow leaks that proceed at a very slow speed. Slow leaks are gradually discovered over a few weeks or months, so there is almost no sound of the refrigerant blowing out. It is difficult to. Further, in the refrigeration apparatus, since the liquid reservoir 35 holds excess refrigerant, even if the refrigerant is removed a little, the refrigerant liquid level in the liquid reservoir 35 is merely lowered, and does not appear as a change in the refrigeration cycle. Finding refrigerant leaks is even more difficult. When the refrigerant liquid level in the liquid reservoir 35 reaches the refrigerant outlet at the lower portion of the liquid reservoir, the two-phase refrigerant mixed with gas flows out of the liquid reservoir 35, and when it further proceeds, it enters an uncooled state. Refrigerant leaks are difficult to detect, such as the amount of leakage evaporates and does not remain afterwards, and suddenly falls into an uncooled state. It is very significant to refill and take measures. The state of the refrigeration cycle in the refrigerant leakage can be divided into three stages, following the stages.

  First, in the initial state of refrigerant leakage, the refrigeration cycle does not change because the refrigerant liquid level in the liquid reservoir 35 is sufficiently high. This is the first stage. When the refrigerant leaks, the liquid level in the liquid reservoir 35 decreases and the refrigerant flowing out of the liquid reservoir 35 becomes a two-phase refrigerant mixed with gas. ) Is cooled and liquefied, and returns to the liquid refrigerant before the refrigerant reaches the expansion means, so that the cooling performance is sufficiently ensured. This is the second stage. As the refrigerant leaks further, the amount of gas mixed into the refrigerant flowing out of the liquid reservoir 35 increases, and the cooling capacity by the supercooling means 37 (including cooling of the liquid piping by ambient air) cannot be sufficiently cooled. In addition, the two-phase refrigerant mixed with gas flows into the expansion means, and a necessary cooling capacity is not obtained, and an uncooled state occurs. This is the stage where the air conditioner or refrigeration unit is useless, and this is the third stage. Even if a refrigerant leak is found at this stage, it is already late, so it is necessary to detect the refrigerant leak in the first stage or the second stage.

  In order to detect refrigerant leakage in the first stage, a special sensor for measuring the liquid level in the liquid reservoir 35 is essential, which is not applicable to existing machines, and is different for each product. However, since the purpose here is to detect a refrigerant leak that is practical, inexpensive, and can be used in a standard refrigeration apparatus, a method of detecting a refrigerant leak in the second stage instead of the first stage is considered. In the second stage, since the refrigerant flowing into the supercooling means 37 is a two-phase refrigerant, the cooling capacity in the supercooling means 37 is lower than that in the case of a complete liquid refrigerant, and at the inlet of the expansion means 13. The subcool (degree of supercooling) of the refrigerant is smaller than the state without refrigerant leakage or the first stage of refrigerant leakage. Therefore, if the change in this subcool (difference between the condensation temperature and the liquid pipe temperature) is captured, the refrigerant leakage can be identified.

  However, in the refrigeration system, the heat exchange amount in the condenser 12 differs when the outside air temperature is different. In addition, the ambient air temperature of the evaporator 14 built in a load-side device such as a showcase or a refrigerator is constantly controlled by the opening / closing of the flow path opening / closing means 36 and the opening of the expansion means 13. Further, the compressor 11 performs capacity control, number control, or ON / OFF control so that the refrigeration cycle operates normally. In the refrigeration system, since the refrigeration cycle is formed by circulating the refrigerant in the pipe, the state quantities of the refrigeration cycle change in correlation with each other. Each state quantity of the refrigeration cycle such as subcool (difference between condensation temperature and liquid pipe temperature) changes.

  That is, the subcool of the refrigeration cycle (the difference between the condensation temperature and the liquid pipe temperature) is the amount of heat exchange in the condenser 12, the control state of the flow path opening / closing means 36 and the expansion means 13, the control state of the compressor 11, the refrigerant leakage The amount of state changes in other refrigeration cycles, such as high pressure and low pressure other than the subcool, similarly, the amount of heat exchange in the condenser 12, the flow path opening / closing means 36 and the expansion means 13. It changes depending on any factor of the control state, the control state of the compressor 11, and the refrigerant leakage amount. Therefore, even if only the change in the refrigeration cycle subcool (the difference between the condensation temperature and the liquid tube temperature) is measured, it is specified whether the change in the subcool is due to refrigerant leakage or a change in the operating state of the refrigeration cycle. I can't.

  However, since the change factors other than the refrigerant leakage occur in the normal operation of the refrigeration apparatus, a plurality of state quantities including the subcooling of the refrigeration cycle are measured in the operation state where the refrigerant leakage does not occur, and these are mutually connected. If it can be handled as an assembly having a correlation, it will be separated from the assembly when a refrigerant leak occurs, so that the refrigerant leakage can be specified. As described above, as a method of capturing a plurality of state quantities as an aggregate, there is a method of using the Mahalanobis distance already described.

  When the Mahalanobis distance method is used to detect refrigerant leaks in the refrigeration cycle, the results of studies have revealed that the refrigerant leak feature quantities are high pressure, low pressure, and subcool. The feature amount is a state amount in which a change appears when the phenomenon occurs. Now, the high pressure of the refrigeration cycle is X1, the low pressure is X2, the subcool is X3, and X1 to X2 are changed in a state where refrigerant leakage does not occur to make a total of n (two or more) combinations. Measure. The measured value is used as reference data. The average values and standard deviations (data variation degrees) of X1 to X3 have already been described in Expressions 1 and 2. Next, using these, the original X1 to X3 converted to x1 to x3 after being normalized as shown in Equation 3. Note that j takes any value from 1 to n and corresponds to each of n measured values. As shown in Expression 4, a correlation matrix R indicating the correlation between x1 to x3 and an inverse matrix R-1 of the correlation matrix are obtained.

  Data can be handled as an aggregate having a certain distribution by the matrix indicating the average value, standard deviation, and correlation. This collection of data is called a unit space. A unit space with respect to a normal state as a base for judgment, here, a state without refrigerant leakage, is referred to as a reference space. Data constituting this reference space is referred to as reference data.

  The Mahalanobis distance D2 is defined by Equation 5. Note that j in the equation takes any value from 1 to n and corresponds to each of the n measured values. K is the number of items (number of parameters), which is 3 here. Further, a11 to akk are coefficients of the inverse matrix of the correlation matrix, and the Mahalanobis distance is about 1 in the reference space, that is, when there is no refrigerant leakage. Then, the high pressure X1, the low pressure X2, and the subcool (difference between the condensation temperature and the liquid pipe temperature) X3 corresponding to the refrigerant leakage amount to be detected are measured, and the Mahalanobis distance in the refrigerant leakage state is obtained as described above and stored as a threshold value. To do. At this time, the inverse matrix of the correlation matrix is obtained in a state where there is no refrigerant leakage as a reference.

  The concept of Mahalanobis distance is shown in FIG. FIG. 6 shows the correlation between two parameters, in which the horizontal axis indicates high pressure and the vertical axis indicates subcool (difference between condensation temperature and liquid pipe temperature). That is, as the high pressure increases, the subcool increases. And although each measurement data varies depending on differences in operating conditions, device control, etc., there is a correlation between high pressure and subcool, and within a range where there is no refrigerant leakage, these are used as reference data, Create a reference space. The other state quantities also have a correlation like the high pressure and the subcool. Then, with respect to the reference space (reference data), whether the data to be determined is normal or abnormal is determined based on the Mahalanobis distance.

  Further, as already explained in FIG. 4, the Mahalanobis distance and its appearance rate are normal or abnormal depending on the positional relationship of the calculated Mahalanobis distance with respect to the reference space, regardless of the number of parameters. Judgment can be made. In the reference space, the Mahalanobis distance has an average of about 1 and has a property of being 4 or less even if variation is taken into consideration. And in an actual machine, the measurement means which measures each measured quantity of a freezing apparatus is provided, these measured values are processed with a previous formula, and it is made into a state quantity, and the distance of Mahalanobis is calculated | required. Then, the magnitude of the Mahalanobis distance corresponds to the refrigerant leakage amount, and the refrigerant leakage can be known from the magnitude of the Mahalanobis distance. Since the Mahalanobis distance is normally a value of 4 or less in the reference space (normal state), it is assumed that the distance up to this threshold is normal, and that it exceeds this threshold is abnormal. However, in practice, there is also a problem of detection error, so the threshold value for judging refrigerant leakage is set to an appropriate value larger than 4, for example, 50. The threshold value is set to a value corresponding to the refrigerant amount in the second stage of refrigerant leakage before the refrigeration cycle is not cooled.

  In FIG. 7, the horizontal axis indicates the amount of refrigerant in the refrigerant circuit, and the vertical axis indicates the Mahalanobis distance. In other words, this is an example showing the relationship between the refrigerant leakage amount and Mahalanobis distance in an actual machine. In FIG. 7, a reference space is created with this data in a state where there is no refrigerant leakage normally, and the triangle that is the liquid level drop is the first stage of refrigerant leakage shown above, the two-phase outflow / liquefaction indicated by squares Indicates the second stage. There is no change in the distance of Mahalanobis in the first stage of refrigerant leakage and refrigerant leakage, but it can be seen that the distance of Mahalanobis gradually increases as the second and third stages proceed. In this case, it was not possible to distinguish between the normal state and the first stage because the feature values were high pressure, low pressure, and subcool. However, the sensor was attached with a sensor that can detect changes in the liquid level in the liquid reservoir (the amount of refrigerant in the liquid reservoir). It is also known that when the amount of refrigerant in the reservoir is added to the feature amount, the Mahalanobis distance changes between the normal state and the first stage, and the normal state and the first stage can be distinguished. Therefore, the normal range can be set more strictly by increasing the measurement amount. In this way, by providing an intermediate stage between normal and abnormal in addition to the normal stage, failure or abnormal stage close to failure, the failure can be predicted by detecting this intermediate stage and estimating the time required for the failure. It is possible to ensure reliable operation of equipment and devices. As such an intermediate stage, for example, a characteristic deterioration phenomenon such as an electrical part may be captured, or a deterioration such as a partial abnormal contact of a mechanical part or a change in surface roughness may be captured.

  Next, the operation will be described with reference to the operation flowchart shown in FIG. First, the average value of the reference data, the standard deviation, the inverse matrix of the correlation matrix, the number of items are set (ST61), and the Mahalanobis distance threshold is set (ST62). Next, the high pressure, the low pressure, and the liquid tube temperature are measured, the subcool is calculated from the high pressure and the liquid tube temperature (ST63), and the high pressure, the low pressure, and the subcool are sequentially placed in X1 to X3 (ST64). Then, the data is standardized by the above-described equation 9 (ST65), the Mahalanobis distance is set to the initial value 0, and the counters i and j are set to the initial value 1 (ST66). Next, the counters i and j are changed until the number of items reaches k, and the above-described calculation of Equation 5 is performed (ST67 to ST70). The above calculation is performed by the calculation means. Then, the calculated Mahalanobis distance and the threshold value are compared by the comparing means, and it is determined by the determining means whether the Mahalanobis distance exceeds the threshold value (ST71). If YES, the refrigerant leaks. For example, the refrigerant leakage display and voltage output are performed (ST72).

  Here, the refrigerant leakage has been described as an example in which the refrigerant leakage is estimated by three measured amounts or state quantities of the high pressure, low pressure, and subcool (difference between the condensation temperature and the liquid pipe temperature) of the refrigeration cycle. It is not limited to. The condensation temperature (condenser saturation temperature) may be used instead of the high pressure, or the evaporation temperature (evaporator saturation temperature) may be used instead of the low pressure. Further, the Mahalanobis distance may be obtained by using a state quantity larger than the three state quantities, which improves detection accuracy. Further, the liquid pipe temperature detection means 38 has been described as an example in which the liquid pipe temperature detection means 38 is installed in the outlet pipe of the supercooling means. However, the liquid pipe temperature detection means 38 is not limited to this. The same effect is produced. However, the greater the subcool (the difference between the condensing temperature and the liquid tube temperature) at the position where the liquid pipe temperature detecting means is installed, the higher the refrigerant leakage detection accuracy. It is more preferable to install at a position.

  Here, the refrigeration apparatus having the liquid reservoir 35 has been described as an example, but other devices such as an air conditioner having the liquid reservoir 35 have the liquid reservoir 35 and store excess refrigerant in the liquid reservoir. Then, it goes without saying that the same effect can be achieved by the same principle. In addition, if the apparatus is configured to store excess refrigerant in the liquid reservoir, the same can be said regardless of other equipment configurations. For example, in a refrigeration apparatus having a liquid reservoir and an accumulator, the excess refrigerant is stored in the liquid reservoir. Therefore, the same effect is obtained by the same principle.

  Further, the Mahalanobis distance may be output as it is as the refrigerant leakage amount. The square root of the Mahalanobis distance is called the D value, and a D value corresponding to the limit refrigerant leakage amount is obtained, and this is corresponded to the maximum output voltage, for example, 5 V. As shown in FIG. A method is also conceivable in which the D value and the voltage are associated with each other and output from the output means 22 from a small amount, a medium amount of leakage, and a large amount of leakage to a critical refrigerant leakage amount. FIG. 9 shows the configuration of the refrigeration cycle apparatus as in FIG. 2, and a voltage indicating the level of the amount of leakage is output from the output means 22 as shown in the figure. The Mahalanobis distance described so far is a value proportional to the square of the deviation of each state quantity. However, since the D value is the square root of the Mahalanobis distance, it is a value proportional to the deviation of each state quantity. It is a value that is easy to handle to correspond to.

  FIG. 10 is a graph in which time is plotted on the horizontal axis and D value (square root of Mahalanobis distance) is plotted on the vertical axis, and shows a transition of the D value over time from a normal state when a certain abnormality occurs. It is. The D value is a value of 2 or less in a normal state, and the D value gradually changes to a larger value with the transition of time with respect to a certain abnormality as shown in the figure. Therefore, it is possible to estimate the time to failure from the relationship between the increasing tendency of the D value and the failure threshold value, and it is possible to prevent the device from being abnormally stopped by performing accurate maintenance before the estimated failure time. It becomes possible to prevent. For example, if it takes one month for the D value to reach half the threshold value from the initial normal state, it can be predicted that it will take another month for the D value to reach the threshold value and enter a failure state. Further, when the D value change method is not proportional, for example, when the increase rate of the D value in the last week has increased, the failure time is predicted using the change rate of the D value in the last week. This makes it possible to predict failure more accurately. Of course, the same can be said when the Mahalanobis distance is used instead of the D value.

  The refrigerant leakage will be described in more detail with an example. Once the refrigerant leak occurs, the expansion of the refrigerant leak will not stop unless the location of the refrigerant leak is closed or refilled, and the Mahalanobis distance and D value continue to increase. Therefore, if the Mahalanobis distance or D value continues to increase, it can be said that the possibility of refrigerant leakage is high. Even if the Mahalanobis distance or D value does not reach the threshold value, it can be determined that the refrigerant leaks. In addition, the time to reach the threshold, that is, the time to reach the limit amount of the refrigerant leakage can be predicted from the change speed of the distance. Since the state quantity of the refrigeration cycle is constantly changing, the Mahalanobis distance and the D value change even if the refrigerant leakage amount does not change. Therefore, the increasing tendency here does not have to be monotonous, but means that it is increasing as a whole except for a slight increase or decrease. Then, based on the prediction of the time until the refrigerant leakage reaches the limit amount, the time when the refrigerant leakage amount reaches the limit refrigerant leakage amount may be output from the output means as a voltage.

  For example, FIG. 11 shows a configuration diagram of another refrigeration cycle. FIG. 11 has the same structure as FIG. 2 and FIG. The state of refrigerant leakage can be set in proportion.

  In addition, here, it is described as if the data measured by each detecting means and used for the computing means is a constant value, but even if the data is changing, an average value of the data for a certain time can be taken. Needless to say, they can be handled in the same way and produce the same effect. It deals with physical quantities of fluids such as refrigerant pressure and temperature, and these physical quantities fluctuate with a time delay that can be handled as steady data even if there is a change in the state of the fluid circuit. Instead of handling feature data such as kilocycles, refrigerant leaks can be detected easily and accurately by averaging data detection results such as time intervals, for example, 1 minute, 10 minutes, hours, days, etc. .

  In addition, as an example of using multiple Mahalanobis distances as a method of capturing a plurality of state quantities as an aggregate, the method used here is another multivariate analysis or a method of obtaining a plurality of correlated detection data. May be used. As another method, for example, a method of calculating the heat exchange amount in the supercooling means is conceivable. Based on the configuration diagram of FIG. 2, a method of determining by a state quantity that is a calculation result that is not a distance will be described.

  The amount of heat exchange in the subcooling means 37 includes the flow rate and temperature of the refrigerant flowing through the main circuit, i.e., the flow path opening / closing means 36 and the expansion means 13, and the refrigerant flowing through the branch path, i.e., the branch path expansion means 37a. It is determined by the flow rate and temperature of the refrigerant flowing through. Now, the flow rate and temperature of the refrigerant flowing through the main circuit are set as GMR and TMR, the flow rate and temperature of the refrigerant flowing through the branch path are set as GBR and TBR, and the heat exchange amount in the liquid tube heat exchange means 37b is set as QSC. Assuming that the heat transfer area of 37b is ASC and the heat transfer rate is KSC, the following equation is simply established.

  Here, the heat transfer area ASC is a constant, and the heat passage rate KSC does not change so much, but has a relationship that increases as the refrigerant flow rate increases. The refrigerant temperature TMR of the main circuit is the liquid pipe temperature detected by the liquid pipe temperature detecting means 38 and has a strong correlation with the condensation temperature, which is the high pressure saturation temperature detected by the high pressure detecting means 16a. The refrigerant temperature TBR is the evaporation temperature which is the low-pressure saturation temperature detected by the low-pressure detection means 16b. Therefore, the heat exchange amount QSC in the liquid tube heat exchange means 37b changes according to the difference between the condensation temperature and the evaporation temperature, and increases as this difference increases, and is a value obtained by compounding these. The refrigerant flowing into the liquid tube heat exchanging means 37b is usually a liquid, but when the refrigerant leaks and decreases, it enters a two-phase state, and most of the heat is used to condense the two-phase refrigerant. For this reason, the subcool (the difference between the condensation temperature and the liquid tube temperature) at the outlet of the liquid tube heat exchange means 37b is reduced.

  Therefore, the subcool (or liquid tube temperature) in the normal state is learned by the relationship between the high pressure (or condensation temperature) and low pressure (or evaporation temperature) or the difference between high pressure and low pressure (or the difference between condensation temperature and evaporation temperature). The refrigerant leakage can be detected by memorizing and seeing the change. In other words, a change in a specific parameter or the like may be extracted and output without depending on the Mahalanobis distance described so far.

  In any method, any refrigerant may flow in the refrigeration cycle of the refrigeration apparatus. For example, a single-component refrigerant such as R22 or R32, a mixed refrigerant composed of three components such as R407C, R410A Thus, a mixed refrigerant composed of a two-component system, an HC refrigerant such as propane, a natural refrigerant such as CO2, and the like can be used. Refrigerants that have a negative impact on global environmental protection can be replaced if leakage begins even a little. In addition, the leakage of the flammable refrigerant can be processed in advance before the problem occurs if the safety limit value determined by the standard or the like is displayed. Furthermore, in a refrigeration apparatus that uses a flammable refrigerant or a refrigerant containing a flammable component such as propane, R32 or R410A, or a refrigerant harmful to the human body, refrigerant leakage is dangerous from the viewpoint of safety. When refrigerant leakage is detected and output as an electric signal such as voltage or a communication code, the safety is remarkably improved by giving priority to output of other refrigeration apparatus.

  FIG. 12 shows a configuration diagram of another refrigeration cycle apparatus. The output means 22 is connected to the alarm device 54 as a voltage output or a current output, and issues an alarm with sound or light, so that refrigerant leakage can be notified early. Since the alarm 54 is provided in the office 53, if it leaks, it can know immediately. According to such a configuration, even if the fluid is a flammable gas or a liquid harmful to the human body, for example, a chemical substance, the leak can be detected by the alarm device at an early stage while the influence is limited.

  In addition, here, a refrigeration apparatus having a liquid reservoir and a liquid pipe temperature detection means has been described as an example, but any refrigeration cycle abnormality can be similarly determined if the refrigeration cycle is similar regardless of the load side equipment. Needless to say, the present invention can also be applied to an air conditioner having a mechanism for accumulating excess refrigerant at high pressure or intermediate pressure. In addition to refrigeration cycles, for example, fluids in chemical manufacturing equipment and fuel depots, detect multiple measured quantities such as physical quantities of related fluid, and compare normal and abnormal conditions as state quantities calculated from these variables. Therefore, it is possible to determine an abnormality early.

  FIG. 13 is a configuration diagram of another refrigeration cycle. The same can be said for the air conditioner having the accumulator 10, the discharge temperature detecting means 61 and the suction temperature detecting means 62 as shown in FIG. In the case of the air conditioner having the configuration shown in FIG. 13, surplus refrigerant is stored in the accumulator 10, and when the surplus refrigerant is in the accumulator 10, the refrigerant flowing out of the accumulator 10 is saturated gas refrigerant, but refrigerant leakage occurs. When the surplus refrigerant decreases and the refrigerant liquid level in the accumulator falls below the outlet pipe position of the accumulator, the refrigerant gas flows out from the accumulator. Then, since the suction temperature 62 or the discharge temperature 61 of the detection means is increased, the same process as described above is performed using the high pressure or the condensation temperature, the low pressure or the evaporation temperature, the suction temperature or the discharge temperature as the characteristic amount, and thus the refrigerant leakage is prevented. Can be judged.

  In addition, in devices without the liquid reservoir 35 and accumulator 10, such as room air conditioners and chilling units, excess refrigerant accumulates in the condenser. Therefore, the refrigerant leakage can be determined by the same method. In other words, excess refrigerant usually accumulates in a part of the condenser, but when refrigerant leakage occurs, the amount of refrigerant accumulated in the condenser decreases, and the area contributing to the heat transfer of the condenser increases. High pressure drops slightly and subcooling decreases. Therefore, refrigerant leakage can be determined by performing the same processing as described above using the high pressure or condensing temperature, the low pressure or evaporating temperature, and the liquid pipe temperature as characteristic quantities. Further, since the discharge temperature is also lowered, the discharge temperature may be selected as the feature amount.

  In addition, here, the refrigerant leakage has been described as an example of the refrigeration cycle abnormality, but the behavior of the refrigeration cycle at the time of the abnormality occurrence can be predicted by simple calculation for other abnormality, and abnormality determination can be performed. . Abnormalities here include not only equipment failures but also changes over time such as equipment deterioration, and any equipment that changes operating conditions can be detected. 14 and 15 are configuration diagrams of another refrigeration cycle apparatus. In the refrigeration apparatus having the liquid reservoir 35 shown in FIG. 14 and the air conditioner having the accumulator shown in FIG. 15, deterioration due to the life of the compressor 11, liquid back, and heat exchange of the heat exchangers of the condenser 12 and the evaporator 14 are performed. Strainer 49a for removing dirt and damage on the surface to be performed, deterioration and failure of the blower 45a of the condenser 12 and the blower 46a of the evaporator, dust inside the circulating refrigerant as a fluid, and moisture prevention of the refrigerant A similar configuration is used for clogging of dryer 49b, broken or broken pipes, clogging, deterioration of refrigeration oil used in compressor 11 (detected by clogging of pipes, poor lubrication of compressor, change in heat transfer, etc.) Can be detected and discriminated.

  In addition, the unit space for calculation includes an average value, a standard deviation, and a correlation coefficient of each feature amount, and these are stored in a memory on a substrate in the refrigeration cycle apparatus. In order to learn all or a part of the actual machine, it must be stored in a rewritable memory. Moreover, by setting the unit space, it is possible to grasp an intermediate stage such as a distance between normal and abnormal. By providing this intermediate stage, it is possible to capture characteristics that gradually change like the refrigerant leakage already described, and to predict failure. Liquid back phenomenon with large or small liquid return amount in the compressor other than leakage, gradual decrease in electrical characteristics due to deterioration of electrical parts, partial deformation of mechanical parts and gradual damage of contact surfaces, related equipment and connection equipment Thus, it is possible to make a diagnosis that accurately distinguishes the degree of an abnormal state, which is a failure in the middle stage that cannot be divided into a normal state and a failure state, such as a failure in a high temperature, an expansion or deformation due to a high temperature, and an operation failure due to a low temperature.

  As apparent from the above, according to the configuration of the present invention, the high pressure measuring means for measuring the high pressure of the refrigeration cycle apparatus or the condensation temperature measuring means for measuring the high pressure saturation temperature, the low pressure measuring means for measuring the low pressure or the low pressure saturation. An evaporating temperature measuring means for measuring the temperature, a liquid temperature measuring means, a discharge temperature measuring means or an intake temperature measuring means, a computing means for obtaining a composite variable from these measured values, and a measured value of each measuring means or those Storage means for storing a calculated value such as a composite variable calculated from the above, a comparing means for comparing a value stored in the past with the storage means and a current measured value or calculated value, and judging refrigerant leakage based on the comparison result By providing the determination means, the refrigeration cycle abnormality such as refrigerant leakage can be accurately detected. Note that the presentation data measurement means such as temperature measurement may be other types, for example, the power supply current of the driving motor, etc., by changing the measurement data taken into the composite variable or by making more measurement data into the composite variable. The accuracy will be further increased.

  In addition, the calculation means calculates the degree of abnormality such as the refrigerant leakage amount in the refrigeration cycle, and predicts the time when the value reaches the abnormal limit at which the predetermined cooling capacity can be maintained from that value. Can be found in. Further, by providing output means for outputting the time when the predicted abnormality limit is reached by an electric signal such as a voltage or current magnitude, the detected abnormality can be transmitted at an early stage. In addition, the refrigerant is a refrigerant containing not only a flammable component, and an abnormality such as a found deterioration can be transmitted at an early stage by connecting an alarm device that emits an alarm by sound or light to the output means.

  The abnormality of the refrigeration cycle apparatus can be grasped to some extent by the change in Mahalanobis distance or D value, as already shown. However, in an actual machine, it is very difficult to identify what is the cause of the abnormality or to estimate the degree of abnormality such as the refrigerant leakage amount. Next, the present invention describes a method for identifying the cause of abnormality and estimating the degree of abnormality or normality. In the description, as already described, a description will be given of an example of refrigerant leakage mainly in a refrigeration apparatus having a liquid reservoir. First, there are three reasons why it is difficult to identify the cause of the abnormality.

  The first reason is that there are various abnormalities. A reference space is created for a normal state in which no abnormality has occurred, and the Mahalanobis distance or D value takes a small value in the reference space, so that an abnormal state, that is, an abnormality can be grasped by the change. However, abnormally, refrigerant leakage, liquid back to the compressor, dirt on the condenser or evaporator, deterioration or failure of the condenser or evaporator blower, clogged piping, dryer or strainer, broken or broken piping There are various types such as clogging, deterioration of refrigeration oil, and the Mahalanobis distance and D value become large regardless of which of these occurs. Therefore, it is difficult to specify the cause of the abnormality even if only the Mahalanobis distance or the D value is observed.

  The second reason is that the Mahalanobis distance or D value does not represent the degree of abnormality itself. If the cause of the abnormality can be estimated from the Mahalanobis distance or the D value, an increase in the value certainly indicates an increase in the degree of abnormality. However, taking refrigerant leakage as an example, it is not known from the value of Mahalanobis distance how many percent of refrigerant leaks when the Mahalanobis distance is 10. In order to specify this, for example, the correspondence between the Mahalanobis distance and the degree of abnormality must be clarified such that the Mahalanobis distance 50 is the limit refrigerant leakage amount. However, it is very difficult to reproduce all abnormalities in advance and quantify them.

  The third reason is that some installation work is performed locally, such as a refrigeration cycle apparatus. For example, taking a refrigeration unit installed in a supermarket as an example, the refrigeration unit and the showcase are not necessarily the same manufacturer, so what kind of showcase is connected as the refrigeration unit and how much is the internal volume? Yes, I can't figure out how many are connected. In addition, the distance between the refrigeration unit and the showcase is completely different depending on whether the store is a one-story store or in a building with many floors. Since the length is different, the amount of refrigerant to be filled is also different. Therefore, the refrigerant of the refrigeration apparatus is filled with such an amount that the refrigeration cycle operates properly after connecting the refrigeration apparatus, the load side device, and the extension pipe on site. Therefore, the reference space created without refrigerant leakage cannot be created at the factory shipment stage of the refrigeration apparatus, and must be created after system connection at the site. Therefore, the correspondence between the Mahalanobis distance or D value and the refrigerant leakage amount becomes more difficult.

  Next, a method for solving these problems will be described. FIG. 16 is a block diagram of the refrigeration cycle apparatus, in which 16a is a high pressure detecting means, 16b is a low pressure detecting means, 38 is a liquid pipe temperature detecting means, 61 is a discharge temperature detecting means, and 62 is an intake temperature detecting means. The subcool is calculated from the means 16a and the liquid pipe temperature detecting means 38, and the superheat is calculated from the low pressure detecting means 16b and the suction temperature detecting means 62. Others are the same as those in FIG.

  FIG. 17 is a diagram showing the relationship between the reference space obtained from the Mahalanobis distance and the abnormal space. Here, the reference space represents a unit space corresponding to the normal state of the refrigeration cycle apparatus, and the abnormal spaces 1 to 3 represent unit spaces corresponding to the state when another abnormality cause has occurred, respectively. Reference numeral 4 denotes a unit space corresponding to a case in which the same abnormality cause as that in the abnormal space 1 occurs and the degree of abnormality is smaller than that of the abnormal space 1. As already explained, the unit space can be treated as a collection with a certain distribution by means of a matrix showing mean values, standard deviations, and correlations. It is called unit space.

  Then, for the five state quantities of high pressure, low pressure, discharge temperature, superheat, and subcool, from the operation data for a certain period of time in the normal state, the average value of the data, the standard deviation as in equations 1 to 4, and the correlation of each state quantity Are stored as a reference space. Now, let us consider refrigerant leakage, liquid back, and piping clogging as abnormalities in the refrigeration cycle apparatus. And, the characteristic quantity in each abnormality is three in high pressure, low pressure and subcool in refrigerant leakage, high pressure, low pressure, discharge temperature and superheat in liquid back, and in pipe clogging. , High pressure, low pressure, and subcool are used as variables.

  Next, how to create an abnormal space is described. The refrigerant leakage in the refrigeration apparatus will be described as an example. In the refrigeration apparatus, when a refrigerant leak occurs, three states from the first stage to the third stage are conceivable depending on the amount of leakage as described above due to the presence of the liquid reservoir 35. In the second stage, the high pressure and the low pressure hardly change and only the subcool becomes small. Therefore, only the average value of the subcool is processed into a small value out of the matrix representing the correlation between the high pressure, the low pressure, the average value of the subcool, the standard deviation, and the state quantity stored in the normal state. Define. For example, the subcool in the refrigerant leakage state is set to 0.2 times normal. In this way, a unit section called an abnormal space 1 with respect to refrigerant leakage taking into account the data distribution is formed.

  Similarly, the high pressure, low pressure, discharge temperature, and super heat stored in the normal state are stored during liquid back, and the high pressure, low pressure, and subcool stored in the normal state are stored when piping is clogged. It processes so that it can do, and defines each as the abnormal space 2 and the abnormal space 3. Then, the distance from each abnormal space (Mahalanobis distance or D value that is the square root thereof) is obtained from the actual operation data thereafter. Then, for example, when a refrigerant leak occurs, the distance from the abnormal space 1 (Mahalanobis distance or D value) gradually decreases, but the distance from the other abnormal spaces does not decrease. It can be specified that the refrigerant leaks. Similarly, the liquid back and the pipe clogging can be similarly determined.

  Next, a processing procedure for determining the cause of abnormality will be described according to the operation flowchart shown in FIG. First, it is determined whether initial learning is necessary from the number of days elapsed since the refrigeration cycle device is installed, the learning state, etc. (ST81), and if initial learning is necessary, the reference space is learned from the normal operating state. (ST82). The reference space is a matrix that represents the average value, standard deviation, and correlation of each state quantity of all data necessary to discriminate each abnormality, as shown in FIG. Next, the state at the time of occurrence of each abnormality is estimated, the data in the reference space is forcibly processed, and an abnormal space is created (ST83). For example, considering the refrigerant leakage of the refrigeration system, the correlation coefficient is obtained by forcibly reducing only the subcool when the refrigerant leaks. Moreover, about what can reproduce an abnormal state with an actual machine, forced abnormal operation may be actually performed to learn the abnormal space. Next, the distance (D value) between the reference space and each abnormal space is calculated and stored as an initial D value (ST84). Although the Mahalanobis distance may be used as the distance, the D value, which is a primary value, is easier to handle, so the D value is used here. When the above operation completes sufficient data to configure each unit space, the initial learning is terminated.

  Next, in the actual operation, that is, the calculation from the state quantity of the current operation state is performed by the method already described. First, each data is measured every moment (ST85), and after standardization of these data (ST86), a D value (square root of Mahalanobis distance) for each abnormal space is calculated (ST87). Then, the occurrence probability of each abnormality is calculated using the following equation (8) (ST88). In addition, the subscript of the following formula has shown the value with respect to each abnormal space.

  Then, these abnormality occurrence probabilities are compared, the presence / absence of abnormality, the cause of abnormality are judged, and the cause of abnormality is displayed (ST89). FIG. 19 is a diagram for explaining the result of actually performing the refrigerant leakage test of the refrigeration apparatus according to the operation processing flowchart of FIG. 18 described above. The horizontal axis indicates the elapsed time of the operation of the refrigeration cycle apparatus. In the test, an empty cylinder was connected to the refrigeration apparatus via a valve, and a simulation was performed in which the refrigerant leaked by operating the valve and gradually collecting the refrigerant in the cylinder. The distance shown on the vertical axis of FIGS. 19 (1) and 19 (2) is the D value (square root of Mahalanobis distance). Further, the abnormal space is created in advance by virtually assuming the refrigerant leakage state. From this figure, as the time of the horizontal axis elapses and the amount of refrigerant leakage increases, the distance from the reference space increases, the distance from the abnormal space created by the refrigerant leakage decreases, and the refrigerant shown in FIG. It can be seen that the probability of occurrence of leakage increases and it can be determined that the abnormality is refrigerant leakage. In the figure, the D value and the probability of occurrence of abnormality vary, but this is because the refrigerator performs automatic control in order to stabilize the temperature on the load side. Even refrigerant leaks can be detected.

  Here, an example has been described in which anomalous spaces are created for different anomaly causes, but as shown in FIG. 17, two stages with different anomalies for the same anomaly are taken up. It is also possible to create anomalous spaces for each. In this way, there is an effect that the abnormality determination accuracy is improved when, for example, anomalous spaces created for different abnormality causes are close to each other. Here, the case where there are four abnormal spaces has been described as an example, but the number of abnormal spaces is not limited to this, and any number can be obtained by the method of the present invention.

  In addition, the data is explained as if all the five data of high pressure, low pressure, discharge temperature, superheat, and subcool are described, but the present invention is not limited to this. In some refrigeration cycle apparatuses, if the high pressure is too low, it is not preferable from the viewpoint of the reliability of the equipment, and some high pressure maintaining means are provided. In this case, whether or not the high-pressure maintaining means works is different in the summer when the high pressure is high and in the winter when the high pressure is low, and the operation of the refrigeration cycle is different. Therefore, if the same reference space and anomalous space are used throughout the year, anomaly discrimination accuracy may deteriorate. In such a case, as shown in FIG. 20, which is an explanatory diagram for selectively using a plurality of reference spaces, it is preferable to have a plurality of reference spaces and anomalous spaces for the year, and use them according to the season. Note that this season may be used depending on the outside air temperature, but the actual machine often does not have an outside air temperature detecting means, and in that case, judging from the detected high pressure range, which reference space is Use it properly or not. In FIG. 20, the vertical axis represents the outside air temperature and the horizontal axis represents the passage of time throughout the year. The reference space when installed in winter is 1 and the reference space when the outdoor temperature is high in summer is 4. Thus, an explanation is provided in which a plurality of reference spaces are provided in accordance with changes in the outside air temperature.

  In addition, although the refrigeration apparatus with a liquid reservoir has been described here, the estimation method of the abnormal state is slightly different even in other air conditioning apparatuses and devices without a liquid reservoir such as a chiller. Needless to say, it is possible to detect the occurrence of an abnormality such as refrigerant leakage, predict the abnormality limit time, and determine the cause of the abnormality by this method. In addition, any other device can be applied as long as it constitutes a refrigeration cycle, and the same effect can be obtained. Since the cause of the abnormality can be determined, the priority order of countermeasures can be determined in advance depending on the cause of the abnormality. For example, in a plant that uses a fluid that is harmful to the human body, in order to prioritize countermeasures against refrigerant leakage over other troubles, first, the cause of abnormality is measured, calculated, judged, and notified more frequently than other faults. If there is no special container for accumulating refrigerant anywhere like a home air conditioner, it should be measured at high pressure, low pressure, subcool or superheat or discharge temperature, these aggregates as characteristic quantities, ie state Obtained as a quantity. As a result of the determination at this time, the surplus refrigerant is only collected inside the condenser, so the physical quantity measured by the entire refrigeration cycle varies depending on the amount of refrigerant in the circuit. If the refrigerant leaks at this time, all the state quantities are affected, and the determination is made including the entire change.

  FIG. 21 is a block diagram of another remote monitoring system, in which 11 is a compressor, 12 is a condenser, 35 is a liquid reservoir, 37 is a supercooling means, 36 is a flow path opening / closing means, 13 is an expansion means, and 14 is an evaporator. These are connected by piping, and a refrigerant is circulated therein, so that a refrigeration cycle is configured in the same manner as in FIG. 2 and others. One or a plurality of compressors 11, flow path opening / closing means 36, expansion means 13, and evaporators 14 are installed. Condenser 12 is installed in a machine room or outdoors. Built in. 16a is a high pressure detection means, 16b is a low pressure detection means, 38 is a liquid pipe temperature detection means, 41 is a data collection means, 18 is a calculation means, 19 is a storage means, 20 is a comparison means, 21 is a determination means, 22 is an output means , 55 is a data transmission / reception means, and 56 is a network or a public line.

  The operation of the refrigeration cycle and the method for estimating the abnormality are the same as those described in FIG. In the configuration of FIG. 21, data exchange between the data collection unit 41 and the calculation unit 18 is performed via the data transmission / reception unit 55 and the network 56. As the measurement of the physical quantity of the refrigerant, the high pressure and the low pressure are obtained by measuring with a pressure sensor or a temperature sensor and calculating the saturation pressure. The subcool is obtained by calculating the condensation temperature, which is the saturation temperature, from the measurement value of the high pressure sensor or by measuring the condensation temperature and subtracting the condensation temperature from the temperature of the liquid pipe. Superheat is calculated by calculating the evaporation temperature, which is the saturation temperature, from the measured value of the low-pressure sensor or by measuring the evaporation temperature and subtracting the evaporation temperature from the intake temperature measured near the compressor inlet.

  The abnormality of the refrigeration cycle that can be detected by the configuration of FIG. 21 is a motor that drives a physical quantity of fluid, a compressor, a fan, etc., as long as the operating state changes such as failure and deterioration (change over time) of various devices. Can be detected from steady-state data of the drive current. For example, deterioration due to the life of the compressor, liquid back, dirt or damage to the condenser or evaporator, deterioration or malfunction of the condenser blower or evaporator blower, clogging of the strainer or dryer, broken or broken pipe, Clogging, deterioration of refrigeration oil (detected by clogging of piping, poor lubrication of compressor, change in heat transfer, etc.) can be detected and discriminated. Further, by transmitting the detected data via the data transmission / reception means 55, the network 56, etc., monitoring can be easily performed at a maintenance center or the like where the centralized monitoring apparatus is located.

  By configuring in this way, it is possible to remotely monitor equipment abnormalities (failures and degradation), so it is possible to detect equipment abnormalities without going to the site, and early detection of abnormalities is possible. It becomes. And in the past, it was necessary to go to the site first to understand the cause of the abnormality and then take countermeasures later. Therefore, it is possible to prepare in advance and go to the work site, and to shorten the time to recovery. For example, when a refrigerant leak occurs, it can be detected remotely, so a refrigerant cylinder and maintenance tools can be prepared and dispatched to the site.

  In FIG. 21, the calculation means 18, the storage means 19, the comparison means 20, the determination means 21, and the output means 22 are illustrated as separate, but may be combined into one. For example, when performing remote monitoring using a general-purpose computer such as a personal computer, all of these functions can be realized by computer software. In this case, the output is output to an external storage medium such as a display or a hard disk. Display is possible.

  The unit space is composed of the average value, standard deviation, and correlation coefficient of each feature quantity. In a remote monitoring system, these are the memory on the substrate of the refrigeration cycle apparatus or a remotely installed personal computer. Is remembered. When learning all or part of the actual data, the data that does not need to be learned may be stored in either the memory on the board of the refrigeration cycle device or a personal computer, but the data that needs to be learned is stored in the hard disk of the personal computer. To remember.

  In the refrigeration cycle apparatus of the present invention, a compressor, a condenser, an expansion means, and an evaporator are connected by piping, and a refrigerant is circulated therein to constitute a refrigeration cycle, and a flow from the discharge side of the compressor to the expansion means. High pressure measuring means for measuring the pressure of the refrigerant at any position in the passage, that is, high pressure, or condensing temperature measuring means for measuring the high pressure saturation temperature, and any position of the flow path from the expansion means to the suction side of the compressor Low pressure measuring means for measuring the pressure or low pressure of the refrigerant or evaporating temperature measuring means for measuring the saturation temperature of the low pressure, and liquid temperature measuring means or compression for measuring the temperature at any position in the flow path from the condenser to the expansion means A discharge temperature measuring means for measuring the temperature at any position in the flow path from the compressor to the condenser, or a suction temperature measuring means for measuring the temperature at any position in the flow path from the evaporator to the compressor. High Measuring means or condensing temperature measuring means, low pressure measuring means or evaporating temperature measuring means, liquid temperature measuring means or discharge temperature measuring means or suction temperature measuring means, computing means for obtaining a composite variable, and measured values of each measuring means or A storage means for storing a calculated value such as a composite variable calculated from them, a comparison means for comparing a value stored in the past with the storage means and a current measured value or a calculated value, and a refrigeration cycle based on the comparison result And a determination unit for determining abnormality, and a highly reliable apparatus can be obtained with a simple configuration.

  Further, the abnormality in the refrigeration cycle determined by the determining means is a refrigerant leakage, and a device with high environmental protection and safety can be obtained. In addition, there is a means for learning by extracting and learning the state in which the refrigeration cycle apparatus is operating normally from the measurement values stored in the storage means or the calculation values calculated from them. Is possible. The content learned by the learning means includes a numerical value representing a correlation between a plurality of state quantities of the refrigeration cycle.

  Any one of the measured values stored in the storage means of the present invention or the calculated values calculated from them is forcibly converted into another value, and a new compound variable is calculated after the conversion. Then, since the newly calculated composite variable is set as a threshold value when the determination means determines refrigerant leakage, the condition for refrigerant leakage can be easily set. The value converted into another value includes a value measured by the liquid temperature measuring means or a value calculated from the measured value. In addition, the value converted into another value may be one, and may be two or more.

  The degree of abnormality of the refrigeration cycle is judged from the value calculated by the calculation means of the present invention, and the limit time when the refrigeration cycle cannot continue stable operation is predicted, so that reliability is improved and safe operation can be performed. For example, the limit of the amount of refrigerant in the refrigeration cycle, the amount of refrigerant leakage, or the corresponding calculation value calculated by the calculation means, and the cooling capacity stored in advance can be maintained from the calculated refrigerant leakage amount or the calculation value corresponding to them. Predicts the time to reach the amount of refrigerant, and includes output means for outputting the predicted limit time as an electrical signal such as the magnitude of voltage or current. The electrical signal output by this output means has a predetermined cooling capacity. It is a voltage output or current output according to the degree of abnormality with the maximum limit abnormality amount that can be maintained as the maximum value, and anyone can know the state of abnormality, and maintenance becomes easy.

  The refrigeration cycle apparatus of the present invention comprises a compressor, a condenser, an expansion means, and an evaporator connected by piping, and a refrigerant is circulated therein to constitute a refrigeration cycle. The refrigerant includes not only flammable components. From the expansion means, a high-pressure measuring means for measuring the pressure or high pressure of the refrigerant at any position in the flow path from the discharge side of the compressor to the expansion means, or a condensing temperature measuring means for measuring a high-pressure saturation temperature. Low pressure measuring means for measuring the refrigerant pressure or low pressure at any position in the flow path leading to the suction side of the compressor, or evaporating temperature measuring means for measuring the low pressure saturation temperature, and the flow path from the condenser to the expansion means Either a liquid temperature measuring means for measuring the temperature at any position or a discharge temperature measuring means for measuring the temperature at any position of the flow path from the compressor to the condenser, or a flow path from the evaporator to the compressor of Suction temperature measurement means for measuring the temperature of the storage device, storage means for storing the measurement values of each measurement means or calculation values calculated therefrom, values stored in the past by the storage means and current measurement values or calculation values A communication means for calculating a refrigerant amount or refrigerant leakage amount in the refrigeration cycle or a calculation value corresponding to them, and an abnormality of the refrigeration cycle as an electric signal or for communication with others as a communication code When the refrigerant leak is detected, the output is given priority over the abnormality of other refrigeration cycles, so that a safe operation can be performed with a simple device regardless of the refrigerant used. The output means is a voltage output or a current output so that an alarm device that issues an alarm by sound or light can be connected to the output means.

  The device diagnostic apparatus according to the present invention includes a means for storing a measured amount when the device is operating normally or a calculated value from the measured amount, and a state amount or state amount in an abnormal state where the device has an abnormality. Means for estimating the calculated value or means for reproducing the abnormal state of the device, means for calculating the distance between the normal state, the abnormal state, and the current operating state of the device, and the distance between the current operating state of the device and the normal state And a means for estimating the normal state, abnormal state, abnormal degree, or abnormal cause of the device from the change in distance from the abnormal state, it is possible to make a highly accurate diagnosis.

  In addition, a plurality of means for storing the measured amount when the device is operating normally or a state amount that is a calculated value from the measured amount, and from the measured amount or measured amount in the abnormal state where the device is abnormal Means for estimating the calculated value or means for reproducing the abnormal state of the device, means for calculating the distance between the normal state, the abnormal state, and the current operating state of the device, and the distance between the current operating state of the device and the normal state In addition, since the apparatus includes a means for estimating the normal state, abnormal state, abnormality degree, or abnormality cause of the device from the change in distance from the abnormal state, highly reliable abnormality diagnosis is possible.

  Also, by defining multiple abnormal states according to the degree of abnormality of the device for one abnormality cause, and estimating the degree of abnormality of the device from the change in distance between the current operating state of the device and the plurality of abnormal states An easy-to-use diagnostic device such as continuation of driving in various states can be obtained. Furthermore, it has a means for extracting and learning the normal state of the equipment from the actual operation data, so that a reliable judgment can be obtained. In the case of a composite variable or a refrigeration cycle apparatus, the calculated value or distance corresponding to the refrigerant amount is a numerical value obtained by processing the Mahalanobis distance or Mahalanobis distance, and can be determined from highly accurate data.

  The remote monitoring system of the present invention expands from the discharge side of the compressor to a refrigeration cycle apparatus that connects a compressor, a condenser, an expansion means, and an evaporator with piping and circulates a refrigerant therein to constitute a refrigeration cycle. Any of the high-pressure measuring means for measuring the pressure of the refrigerant at any position in the flow path leading to the means, the condensing temperature measuring means for measuring the high-pressure saturation temperature, and the flow path from the expansion means to the suction side of the compressor A low-pressure measuring means for measuring the pressure of the refrigerant at that position, that is, a low pressure, an evaporating temperature measuring means for measuring a low-pressure saturation temperature, and a liquid temperature for measuring the temperature at any position of the flow path from the condenser to the expansion means Measuring means or suction temperature measurement measuring the temperature at any position in the flow path from the compressor to the condenser or measuring the temperature at any position in the flow path from the evaporator to the compressor. A computing means for obtaining a composite variable from the measured values of the high pressure measuring means or the condensation temperature measuring means, the low pressure measuring means or the evaporation temperature measuring means, the liquid temperature measuring means or the discharge temperature measuring means or the suction temperature measuring means, Storage means for storing the measurement values of each measurement means or calculation values such as composite variables calculated from them, comparison means for comparing the values stored in the past with the storage means and the current measurement values or calculation values; Judgment means for judging an abnormality of the refrigeration cycle based on the comparison result is provided in the vicinity of the refrigeration cycle apparatus or remotely via a network or a public line so that measurement data or a calculated value is transmitted via the network or the public line. Because it is configured, it is easy to deal with any problems that occur and is effective for continuation of driving.

  The remote monitoring system of the present invention is a refrigeration cycle apparatus that constitutes a refrigeration cycle by connecting a compressor, a condenser, an expansion means, and an evaporator with piping, and circulating a refrigerant containing not only a combustible component therein. , A high-pressure measuring means for measuring the pressure of the refrigerant at any position in the flow path from the discharge side of the compressor to the expansion means, that is, a high-pressure measuring means for measuring the high-pressure saturation temperature; One of the low-pressure measuring means for measuring the pressure or low pressure of the refrigerant at any position in the flow path leading to the suction side, or the evaporating temperature measuring means for measuring the low-pressure saturation temperature, and any of the flow paths leading from the condenser to the expansion means Liquid temperature measuring means for measuring the temperature of the position or any one of the discharge temperature measuring means for measuring the temperature at any position of the flow path from the compressor to the condenser or any position of the flow path from the evaporator to the compressor And a storage means for storing the measured value of each measuring means or a calculated value calculated from them, and a value stored in the past by the storing means and a current measured value or Comparing means for comparing the calculated values, calculating means for calculating the refrigerant amount or refrigerant leakage amount in the refrigeration cycle or a calculated value corresponding to them, and communicating with others as abnormalities of the refrigeration cycle as electrical signals or as communication codes Output means for performing the operation in the vicinity of the refrigeration cycle apparatus or remotely via a network or public line, and transmitting measured data or calculated values via the network or public line to detect other refrigerant when a refrigerant leak is detected. Safe output is possible because the output is given priority over the cycle abnormality.

  Means for storing the measured value when the device is operating normally or a calculated value from the measured amount, and means for estimating the measured value or the calculated value from the measured amount in an abnormal state where the device is abnormal Or means for reproducing the abnormal state of the device, means for calculating the distance between the normal state, the abnormal state, and the current operating state of the device, and the distance between the current operating state of the device and the normal state and the distance between the abnormal state A device that estimates the normal state, abnormal state, abnormality level, or cause of an abnormality from a change in the temperature is provided near the refrigeration cycle apparatus or remotely via a network or public line, and measured data or computation via the network or public line Since it is configured to transmit values, maintenance is easy.

  In addition, multiple means for storing the measured value or the calculated value from the measured value when the device is operating normally, and the estimated value from the measured value or measured value in the abnormal state when the device is abnormal Means for reproducing the abnormal state of the device or the device, means for calculating the distance between the normal state, the abnormal state and the current operating state of the device, and the distance or the abnormal state between the current operating state of the device and the normal state A device that estimates the normal state, abnormal state, degree of abnormality, or cause of abnormality of a device from a change in the distance between the refrigeration cycle device or remotely via a network or public line, and measurement data via the network or public line Alternatively, since the operation value is transmitted, the device is easy to handle.

  Although the D value is used as the distance in the flowchart of FIG. 18, the Mahalanobis distance D2 for the reference space and each anomalous space is first obtained, and then the square root of D2 is calculated by the following equation (6). The occurrence probability of each abnormality is calculated at, and the cause of failure is evaluated and estimated from the probability of occurrence of each abnormality. Here, the reason why the Mahalanobis distance D2 is raised to the 1/2 power in the equation (6) is that the distance D2 is a square value, and the value increases quadratically as the distance increases. This is because the distance increases linearly according to the degree of abnormality by using D, and the increase in the distance and the increase in the degree of abnormality are proportional and easy to handle. In Expression (8), “Initial D” is the Mahalanobis distance when the abnormal space is applied to the initial normal state data. In the initial normal state, it represents the distance to normal based on the abnormality. “Current D” represents a distance when an anomalous space is applied to current measurement data. “Current D” takes a large value in the initial normal state (because the difference between the abnormal state and the normal state is large), but “current D” becomes a small value as the degree of abnormality progresses (gradually from normal to abnormal) The probability of occurrence of anomaly approaches 100%.

  If the determination means of the present invention, that is, from the relationship between the distance and the threshold shown in the flowchart, cannot be determined normal, a fault screen display, sound notification, abnormality notification to a remote location, and the like are output. Then, the service person who has been notified of the failure performs repairs such as failure repair and overhaul, and the equipment is restored to a normal state. Each process in the flowchart of this description is performed by the other calculation means 18, storage means 19, comparison means 20, judgment means 21, and output means 22 in FIG. The initial learning presence / absence determination ST81 is processed by the determination means 21, and the learning-related processes ST82 and 83 are calculated by the calculation means 18 and stored in the storage means 19. The Mahalanobis distance calculation processing ST84, 86, 87 is performed based on the data of the reference space and the abnormal space stored in the storage means 19 in the calculation means 18, and the failure determination ST88, 89 is the comparison means 20 and determination. The output is performed by the output means 22. Of course, the failure may be determined from the relationship of the distance between the reference space and the abnormal space without using the threshold.

  In the above description, the learning operation of learning the reference space for the normal state or the abnormal space for each abnormal state calculates the reference value necessary for calculating the Mahalanobis distance from the measurement data and stores it as the reference value. Specifically, calculating the average value m of the formula (1), the standard deviation σ of the formula (2), and the inverse matrix R-1 of the correlation matrix of the formula (4). Show.

  In each abnormal space, the average value and standard deviation of each parameter and the correlation coefficient of each parameter are stored. The distance between the reference space and each abnormal space can be obtained by obtaining the Mahalanobis distance from the normal reference space using the average value of each parameter of each abnormal space, and this can be set as a threshold value. For example, in actual machine operation, first, data measurement is performed to determine whether or not there is a failure, and the distance (square root of Mahalanobis distance) between each abnormal space and the normal reference space is set as initial D1 and initial D2. Next, the distance D0 between the measured current operating state quantity data and the normal reference space, and the distances D1 and D2 between the abnormal spaces are obtained. Note that D0 takes a value of 2 or less in the initial state. Then, the degree of approach to each abnormal space is calculated from Equation (8), and the occurrence probability of each abnormality is obtained. Then, the abnormality occurrence probabilities are compared to determine the cause of the failure.

  As described above, by defining the normal reference space and the abnormal space and determining the probability of occurrence of each abnormality, grasp the degree of abnormality by increasing the distance to the normal reference space (Mahalanobis distance or square root of Mahalanobis distance). It is possible to identify the cause of the abnormality by reducing the distance (Mahalanobis distance or the square root of the Mahalanobis distance) to each abnormal space. Although the concept of the Mahalanobis distance between the abnormal space and the normal space has been described with reference to FIG. 17, the normal reference space is an image diagram in which each abnormal space exists at a position away from the origin at the coordinate center. Since the Mahalanobis distance is actually a multidimensional space, FIG. 17 is an image diagram representing this two-dimensionally. The normal reference space and the abnormal space each have a region with variations, and it is possible to determine whether the current operating state is normal or abnormal by determining which space it belongs to It becomes possible. The distance between each abnormal space and the normal space can be calculated by obtaining the Mahalanobis distance between the normal reference space and the representative data (average value data) of the abnormal space. For example, if this distance is 1000, the current refrigeration cycle operating state quantity is calculated using the normal reference space, and the distance is 1000. If the distance from the abnormal space is close to zero, this may be abnormal. Is expensive. As for the threshold for each abnormality, the distance between the normal reference space in each abnormality and the Mahalanobis between each abnormality space is calculated as described above. For example, if it is desired to detect the abnormality early, 1/10 is set as the threshold for the abnormality. A threshold value may be set as described above.

  In addition, in the failure simulation test at the installation site, the test cannot be performed in extremely bad operating conditions that lead to compressor failure, so the failure condition is divided into several levels and the abnormal space is learned according to each level. It may be. This level division will be described with reference to FIG. 22 which is a multidimensional space conceptual diagram of Mahalanobis distance. In FIG. 22, the abnormal space 1 represents an example. In this example, the abnormal space 1 is divided into an abnormal level 1 to an abnormal level 3 according to the degree of abnormality, and the level 1 and level 2 abnormal spaces are learned in the installation site test. Do. Level 3 is a level that actually causes the compressor to break, and is an abnormal space in which measurement is performed in advance in the test room and learning is performed.

  In this way, by classifying the abnormalities according to the abnormalities, it is possible to create an abnormal space that matches the actual equipment on-site in the area where the abnormalities that can be simulated by the actual equipment are low. It is possible to detect early abnormalities in line with.

  In addition, by classifying the level of abnormality and creating an abnormal space for each abnormal level, accurate failure prediction is possible even when the abnormal level is low, and it is easy to distinguish from other abnormalities, It is possible to predict failure and identify the cause of failure at an early stage before an abnormality occurs and the refrigeration cycle apparatus breaks down.

  Next, anomalous space learning will be described. There are two types of anomaly space: a method of learning with an actual machine after installing the equipment at the installation site, and a method of creating an anomaly space using data obtained by simulating the failure state of the same model in the test room in advance. There is. The former is intended for a failure state that can simulate a failure state at the installation site. For example, in addition to the refrigerant leakage described above, the refrigerant liquid bag, the refrigeration machine oil depletion, and the like are targeted. For these failures, simulate the refrigerant back-up state by opening the expansion valve of the refrigeration cycle, or temporarily evacuating oil from the bottom of the compressor. Create an anomalous space from operating conditions. The created abnormal space is stored in the storage means, and is used to determine an abnormal state.

  The latter method of performing a failure simulation test in advance in the test room is intended for failures that are difficult to simulate at the installation site. For these failures, create a refrigeration cycle device that can simulate an abnormal condition, test this refrigeration cycle device in a laboratory, collect abnormal operating state data, and create an abnormal space using this data. To do. The abnormal space prepared in advance is stored in the storage unit in advance when the refrigeration cycle apparatus is shipped, so that it can be applied to an actual machine. Also, a part of the fault simulation test can be substituted by simulation.

  In addition, as another learning method for anomalous space, when parameters that show signs when a target failure occurs are clear in advance, after normal reference space learning, the data of each parameter used for the normal reference space On the other hand, a method has already been described in which only the value of a parameter in which a sign appears remarkably when an abnormality occurs is changed to a value estimated when a failure occurs forcibly, and new abnormal operation state quantity data is created. In addition, the value to be converted separately may be one or two or more. This makes it possible to create an anomaly space based on the normal state of the actual machine, and to completely absorb individual differences due to variations in the actual machine, if the parameters that show signs in the event of an abnormality are clear in advance. It becomes possible to do.

  On the other hand, when the operation of the refrigeration cycle apparatus is continued, an unexpected failure that cannot be covered in the initially predicted abnormal space may occur. As a countermeasure for such a case, there is a new abnormality learning function, and its concept is shown in the flowchart of FIG. In the figure, ST51 is the detection of the occurrence of an abnormality, and the cause of the failure cannot be specified in the failure cause evaluation determination flow, but the Mahalanobis distance is increased and it can be determined that the refrigeration cycle apparatus is abnormal. In such a state, first, the time zone in which the abnormality has occurred is selected from the past time zones displayed on the display means 6 in FIG. 1 by the operation of the input device 7 in FIG. Note that the data for the past several days is always stored in the storage means, and in ST52, an arbitrary location is selected from this data. In ST53, the abnormal space is learned using the operation data (abnormal data) in the selected time zone. In ST54, the learned abnormal space is stored in the storage means as a new abnormal space. In the failure cause evaluation after the new abnormal space is stored, the new abnormal space can also be determined.

  In addition, although the said description demonstrated learning operation in the operating device of the input means of an actual refrigeration cycle apparatus, the same learning operation by information terminals, such as a remote personal computer, in a remote monitoring means is also possible. Alternatively, the input means does not need to be permanently installed in the refrigeration cycle apparatus, and in the event of an abnormality, a maintenance tool can be installed so that a service person can download data from the refrigeration cycle apparatus, analyze it, and write information to the refrigeration cycle apparatus You may be allowed to go to maintenance with a personal computer. If the learning method described with reference to FIG. 23 is used, information at the time of manufacture or installation becomes unknown, and the present invention can be applied to an existing machine that is currently operating normally. First, the normal learning described with reference to FIG. 8 is performed, and then this data is processed to learn the abnormal space. Next, it may be set so that the new abnormality learning of FIG. 23 can be performed by storing data during operation. That is, the present invention can be applied to any apparatus that is already in operation. Therefore, by providing a remote monitoring device such as FIG. 21 of the present invention, maintenance can be performed simply by having data transmitted from a device such as a refrigeration cycle device owned by a contracted user via the Internet or the like. I can do it.

  First, a maintenance department or person in charge receives a maintenance order from a new maintenance ordering person using the network 56 in FIG. 21 or the telephone line 3 in FIG. The measuring means as described above is attached to a fluid circuit that is a refrigeration cycle provided at a site such as a supermarket where the refrigeration cycle apparatus 1 of FIG. This measured amount is stored in a storage means provided in the microcomputer 2. The maintenance staff can draw out the measured amount measured by this measuring means via the communication means, and the physical quantity of the fluid sucked and discharged by the device circulating in the fluid circuit thus stored is measured by a plurality of measuring means. It is possible to obtain a calculation result obtained by calculating a measurement amount measured and stored or a plurality of parameters obtained from the measurement amount as a plurality of variables and calculating an aggregate related to each other. If the calculation is performed on site, the calculation result may be read out via communication. A refrigeration cycle apparatus by determining whether a calculation result obtained by calculating a plurality of parameters obtained by combining a plurality of parameters obtained from a read calculation result or a measured amount as a plurality of variables is within a preset range. The current state quantity can be grasped. Continuing accumulation of the current state quantity, it is normal or abnormal based on the flow charts of FIGS. 8, 18, and 23, the normal state and the abnormal state, the distance between the normal space and the abnormal space, etc., the degree of abnormality, leakage Judge the time until the tolerance limit and the cause of the abnormality. The determined result is communicated to the maintenance orderer, and the determined result includes a plurality of proposals regarding the content and timing of the maintenance. That is, because the maintenance contents differ depending on the degree of abnormality and the cause of the abnormality, the system of the present invention capable of predicting the abnormality can propose the maintenance contents at each stage by dividing the timing up to the allowable limit into a plurality of times. This proposal includes an estimated cost for the maintenance, and the maintenance ordering side knows the degree of abnormality, and can determine when and what kind of maintenance will be performed from the time, cost, and contents. If such a maintenance system can be adopted, the operation of the apparatus and equipment can be performed with no risk. Moreover, since the operation history and trouble contents can be automatically recorded, it is possible to easily deal with reports whenever necessary. In this way, even for existing machines and devices that exist in remote locations such as overseas, it is only necessary to obtain measured quantities via communication means, or via communication Diagnosis can be made by obtaining specifications, installation status, operation history, etc., and maintenance recommendations and judgments can be made easily and quickly. It is also possible to perform a task of performing a fault diagnosis using the Internet or the like independently of a task of operating facilities using devices or equipment, a task of maintenance, and the like. It is convenient for accurate maintenance including failure prediction to include not only the use of the apparatus but also a history such as past operation records, failure records, and maintenance records. Furthermore, by providing an additional learning function even for a new failure, it is possible to deal with an accurate failure determination by post-processing even for a failure that could not be predicted at the beginning of design. In addition, the learned information on the new abnormal space is stored in the device diagnostic device and the remote monitoring means. By using these information, it is added to the storage means of the same model that is newly shipped or a similar different model. It is also possible to deploy to many models.

  In the above description, the Mahalanobis distance is used as an abnormality determination means, and a method of performing abnormality determination by converting a multi-item parameter into one index has been described. In addition, for example, an item that exhibits abnormality is specified in advance. If possible, attention may be paid to a specific item such as a standard deviation, and an abnormality determination may be performed depending on whether this item exceeds a threshold. The state quantities described above are calculated by measuring physical quantities related to the refrigerant having a large time delay of change, current effective values, and the like to obtain measurement quantities such as currents unrelated to instantaneous values. By combining many variables obtained from such data, it is possible to diagnose a failure as a whole including mechanical, electrical, or other influences that are not caused by an accident. The compressor used in the refrigeration cycle discharges, sucks and circulates the refrigerant flowing through the refrigeration cycle, and it is effective for practical diagnosis to use variables including the physical quantity of the refrigerant. The same applies to fluid machinery such as blowers related to physical quantities of wind flow and pumps related to water, food, and chemical liquids, and devices that move objects such as fax machines, printers, and production lines. It can also be used with other drive devices. In particular, in the case of a blower used in a refrigeration cycle, it is obvious from the fact that the performance and characteristics of the refrigeration cycle change that the physical quantity of the refrigerant other than the flow of wind as the fluid may be measured as described above.

  We have mentioned the use of motor-driven current as one of the state quantities to measure as a variable, but other electrical quantities, such as electromagnetic forces between the stator rotors of the motor, which are related to the drive torque, Measurement data of different phenomena such as current, noise radio waves leaking to the surroundings, or shaft voltage are not only electrically related to each other, but multiple measurements may be made to distinguish them from accidents such as mechanical systems. . For example, when the motor is an induction motor and a DC brushless motor, the way of generating harmonics changes, and the steady earth current, noise radio wave, shaft voltage, etc. are different. Further, when an abnormality is to be notified at the installation site, either or both of the method of notifying the abnormality with the warning lamp 8 or the speaker 9 of FIG. 1 and the method of displaying the abnormality content on the display device 6 such as a liquid crystal display are used. Is possible. When the abnormal situation is urgent and serious, the combined use of the warning lamp 8, the speaker 9 and the display device 6 is effective. In the stage where the abnormality is small or the prediction stage, only the display device 6 is used for notification, and a serviceman is used during maintenance. If it is configured so that the abnormal tendency can be confirmed, it is possible to grasp an appropriate maintenance time. As for the notification to the remote monitoring room, the contents and degree of abnormality are notified to the remote monitoring room by communication means such as a telephone line, LAN, and radio. In the remote monitoring room, a service person is dispatched according to the state of the abnormality, but if the cause of the abnormality can be grasped remotely at this time, the necessary parts can be prepared to deal with the corresponding abnormality before going to the site, Rapid maintenance can be performed. In addition, it is also possible to notify the information directly to the information receiving means such as the mobile phone of the service person at the same time as informing the remote monitoring room.

  Although it has already been explained that the motor-driven power supply current is one of the measured quantities, it is natural that the power supply current itself or the direct measurement need not be measured. A current flowing through the motor such as a coil around the motor may be picked up by an induced voltage, or an unbalanced current flowing through each layer of the motor winding destination may be picked up as a state quantity. In the case of a compressor, the driving torque related to the motor current has a large torque pulsation due to refrigerant compression, and the influence of the failure is buried. In the compressor, the torque varies greatly depending on the compression ratio, that is, the ratio between the high pressure and the low pressure. Therefore, it is necessary not only to measure the current but also to measure the high pressure and the low pressure together, and to calculate and judge these correlations. For example, the high pressure and low pressure of the refrigeration cycle are not stable for several tens of minutes after starting the compressor. Therefore, when using steady data as the state quantity described in the present invention, it is better to start measurement after the physical quantity of the refrigerant is stabilized. On the other hand, when the physical quantity of the refrigerant is not stable, the signal caused by the compressor torque Since the signal changes during the failure such as the tooth contact affected by the torque or the torque, it is possible to distinguish the failure of the electric system such as the capacitor not affected by the torque at this time. Even if the frequency of the compressor does not change due to control of load side devices such as opening and closing of the solenoid valve of the showcase, the state quantity of the refrigeration cycle such as high pressure and low pressure changes and the torque fluctuates. For this, for example, the reference state may be stored in relation to the torque or the compression ratio, or an average for a certain time may be taken.

  The refrigeration cycle apparatus diagnosis method according to the present invention extracts the state in which the refrigeration cycle apparatus is operating normally from the measurement values stored by the storage means and the state feature values calculated from them. And learning. In the refrigeration cycle apparatus diagnosis method of the present invention, any one of a learned value measured by each measurement amount detecting means during normal operation or a state feature value calculated from them is forcibly set to another value. And a step of newly calculating a composite variable after the conversion, and a step of setting the newly calculated composite variable as a threshold when the determination unit determines that the compressor is abnormal. Thus, it is possible to learn by assuming an abnormal state based on the normal state without learning by causing an abnormal state. The refrigeration cycle apparatus diagnosis method according to the present invention is further characterized in that the degree of abnormality is a threshold value based on a composite variable value in a normal state and a current composite variable computed value and threshold value or a threshold value and elapsed time set in advance by a user. A step of calculating a time until the failure is reached, that is, a step of predicting a failure.

  The refrigeration cycle apparatus according to the present invention includes a high pressure measuring means for measuring the high pressure of the refrigeration apparatus or a condensing temperature measuring means for measuring the high pressure saturation temperature, a low pressure measuring means for measuring the low pressure, or an evaporation temperature for measuring the low pressure saturation temperature. A measuring means, a liquid temperature measuring means, a discharge temperature measuring means or an intake temperature measuring means, a calculating means for obtaining a composite variable from these measured values, a measured value of each measuring means or a composite variable calculated from them, etc. Storage means for storing the calculated value, comparison means for comparing the value stored in the past with the storage means and the current measured value or calculated value, and determination means for determining the refrigerant leakage based on the comparison result. Thus, it is possible to accurately detect refrigeration cycle abnormalities such as refrigerant leakage.

  In addition, the calculation means calculates the degree of abnormality such as the refrigerant leakage amount in the refrigeration cycle, and predicts the time when the value reaches the abnormal limit at which the predetermined cooling capacity can be maintained from that value. Can be found in. Further, by providing output means for outputting the time when the predicted abnormality limit is reached by an electric signal such as a voltage or current magnitude, the detected abnormality can be transmitted at an early stage. In addition, the refrigerant is a refrigerant containing not only a combustible component, but the detected abnormality can be transmitted at an early stage by connecting an alarm device that emits an alarm with sound or light to the output means. In addition, abnormalities can be detected early by monitoring and judging data remotely.

  As an example of the abnormality of the refrigeration cycle that can be detected by the present invention, any abnormality can be detected as long as the operation state changes, such as failure and deterioration (change with time) of various devices. For example, deterioration due to the life of the compressor, liquid back, dirt or damage to the condenser or evaporator, deterioration or malfunction of the condenser blower or evaporator blower, clogging of the strainer or dryer, broken or broken pipe, Clogging, deterioration of refrigeration oil (detected by clogging of piping, poor lubrication of compressor, change in heat transfer, etc.) can be detected and discriminated.

  Since the present invention is configured in this way, it is possible to remotely monitor the abnormality (failure and deterioration) of the device. Therefore, the abnormality of the device can be found without going to the site, and the abnormality can be detected early. Detection is possible. And in the past, it was necessary to go to the site first to understand the cause of the abnormality and then take countermeasures later. Therefore, it is possible to prepare in advance and go to the work site, and to shorten the time to recovery. For example, when a refrigerant leak occurs, it can be detected remotely, so a refrigerant cylinder can be prepared and dispatched to the site.

  As described above, the refrigeration cycle determined by the determining means according to the present invention can detect refrigerant leakage from the flow path, so that a device that can be relieved by monitoring the flow of flammable refrigerant or liquid harmful to the human body can be obtained. . Moreover, since it has means for extracting and learning the state in which the refrigeration cycle apparatus is operating normally from the measured values of the respective measuring means stored in the storage means or the calculated values calculated from them, stable data is always obtained. Is obtained. Furthermore, since the content learned by the learning means includes a numerical value representing a correlation between a plurality of state quantities of the refrigeration cycle, a highly accurate diagnosis is possible. Further, a step of forcibly converting any one of the measured values stored in the storage means or the calculated values calculated from them into another value, and after the conversion, newly adding the composite variable Since there is a step of calculating, and a step of setting the newly calculated composite variable as a threshold value when the determination means determines fluid leakage, an abnormality can be easily set, and an abnormal state is caused in the actual machine. Without learning, it is possible to learn by assuming an abnormal state based on the normal state.

  The degree of abnormality of the refrigeration cycle can be determined from the value calculated by the calculation means of the present invention, and the critical time when the refrigeration cycle cannot continue stable operation can be predicted, and a highly reliable device and operation can be obtained. The refrigerant, fluid amount or refrigerant or fluid leakage amount in the flow path cycle or a calculation value corresponding to them is calculated by the calculation means, and the pre-stored cooling is calculated from the calculated leakage amount or the calculation value corresponding to them. Predicting the time to reach the limit amount that can maintain the capacity and supply, you can get a safe one. In addition, output means for outputting the predicted limit time as an electrical signal such as a voltage or current magnitude is provided, and the electrical signal output by the output means has a degree of abnormality that maximizes the limit at which a predetermined device capability can be maintained. Since it is a voltage output or a current output according to, it is easy to monitor.

  In the present invention, a compressor, a condenser, an expansion means, and an evaporator are connected by piping, and a refrigerant is circulated therein to constitute a refrigeration cycle. The refrigerant contains not only a combustible component but is compressed. High pressure measuring means for measuring the pressure or high pressure of the refrigerant at any position in the flow path from the discharge side of the machine to the expansion means, or a condensing temperature measuring means for measuring the saturation temperature of the high pressure, and the suction side of the compressor from the expansion means Low pressure measuring means for measuring the pressure or low pressure of the refrigerant at any position in the flow path leading to the evaporating temperature measuring means for measuring the low pressure saturation temperature, and any position in the flow path from the condenser to the expansion means. The liquid temperature measurement means for measuring the temperature or the temperature at any position of the flow path from the compressor to the condenser to measure the temperature at any position of the discharge temperature measurement means or the flow path from the evaporator to the compressor Sucking to measure Temperature measuring means; storage means for storing measured values of each measuring means or a calculated value calculated therefrom; comparison means for comparing a value stored in the past with the storage means and a current measured value or calculated value; A calculation means for calculating a refrigerant amount or a refrigerant leakage amount in the refrigeration cycle or a calculation value corresponding thereto, and an output means for outputting an abnormality of the refrigeration cycle as an electrical signal or communicating with others as a communication code, When refrigerant leakage is detected, output is given priority over other refrigeration cycle abnormalities, so that reliable maintenance is possible and a highly reliable one can be obtained at low cost.

  The refrigeration cycle of the present invention stores a measured amount when the device is operating normally or a calculated value from the measured amount, and a calculated value from the measured amount or the measured amount in an abnormal state where the device is abnormal. Means for estimating the device or means for reproducing the abnormal state of the device, means for calculating the distance between the normal state and the abnormal state and the current operating state of the device, the distance between the current operating state and the normal state of the device, and Since a device for estimating the normal state, abnormal state, abnormality degree, or abnormality cause of the device from the change in distance from the abnormal state is provided, a highly accurate and easy-to-use failure diagnosis apparatus can be obtained.

  The present invention can create a plurality of abnormal states according to the degree of abnormality of the device for one abnormality cause, and estimate the degree of abnormality of the device from the change in the distance between the current operating state of the device and the plurality of abnormal states To do. The calculated value or distance corresponding to the composite variable or the refrigerant amount is a numerical value obtained by processing the Mahalanobis distance or the Mahalanobis distance. The present invention also provides a flow from the discharge side of the compressor to the expansion means by connecting the compressor, the condenser, the expansion means, and the evaporator with a pipe and circulating a refrigerant therein to constitute a refrigeration cycle. High pressure measuring means for measuring the pressure of the refrigerant at any position in the passage, that is, high pressure, or condensing temperature measuring means for measuring the high pressure saturation temperature, and any position of the flow path from the expansion means to the suction side of the compressor Low pressure measuring means for measuring the pressure or low pressure of the refrigerant or evaporating temperature measuring means for measuring the saturation temperature of the low pressure, and liquid temperature measuring means or compression for measuring the temperature at any position in the flow path from the condenser to the expansion means A discharge temperature measuring means for measuring the temperature at any position in the flow path from the compressor to the condenser, or a suction temperature measuring means for measuring the temperature at any position in the flow path from the evaporator to the compressor. , Calculation means for obtaining a composite variable from the measured values of pressure measuring means or condensing temperature measuring means, low pressure measuring means or evaporating temperature measuring means, liquid temperature measuring means or discharge temperature measuring means or suction temperature measuring means, and measured values of each measuring means Or storage means for storing a calculated value such as a composite variable calculated from them, comparison means for comparing a value stored in the past with the storage means and a current measured value or calculated value, and a refrigeration cycle based on the comparison result Since it is configured to determine whether there is an abnormality in the vicinity of the refrigeration cycle device or remotely via a network or public line, and to transmit measurement data or calculation values via the network or public line, monitoring is inexpensive. Can be done.

  The present invention relates to a refrigeration cycle apparatus that connects a compressor, a condenser, an expansion means, and an evaporator with pipes, and circulates a refrigerant containing not only flammable components in the refrigeration cycle to form a refrigeration cycle. High pressure measuring means for measuring the pressure of the refrigerant at any position in the flow path from the discharge side to the expansion means, that is, a high pressure measuring means for measuring the high pressure saturation temperature, and a condensing temperature measuring means for measuring the high pressure saturation temperature, and the expansion means to the suction side of the compressor The low pressure measuring means for measuring the pressure of the refrigerant at any position of the flow path, that is, the low pressure, the evaporating temperature measuring means for measuring the low pressure saturation temperature, and the temperature at any position of the flow path from the condenser to the expansion means. Measure the temperature of either the liquid temperature measuring means to measure or the temperature of any position of the flow path from the compressor to the condenser, or the temperature of any position of the discharge temperature measuring means or the flow path from the evaporator to the compressor Connects to the input temperature measuring means, and stores the measured values of each measuring means or the calculated values calculated from them, and compares the values stored in the past with the current measured values or calculated values. Comparison means, calculation means for calculating the refrigerant amount or refrigerant leakage amount in the refrigeration cycle or a calculation value corresponding thereto, output means for outputting a refrigeration cycle abnormality as an electric signal or communicating with others as a communication code In the vicinity of the refrigeration cycle system or remotely via a network or public line, and when measured data or calculation values are transmitted via the network or public line and refrigerant leakage is detected, priority is given to other refrigeration cycle abnormalities. Output.

  The present invention relates to a means for storing a measured amount when a device is operating normally or a calculated value from the measured amount, and to estimate a measured value or a calculated value from the measured amount in an abnormal state where the device is abnormal. Means for reproducing the abnormal state of the device or the device, means for calculating the distance between the normal state, the abnormal state and the current operating state of the device, the distance between the current operating state of the device and the normal state and the abnormal state, A device that estimates the normal state, abnormal state, degree of abnormality, or cause of abnormality of a device from a change in the distance between the refrigeration cycle device or remotely via a network or public line, and measurement data via the network or public line Or it is comprised so that a calculation value may be transmitted.

  The present invention provides a plurality of means for storing a measured amount when a device is operating normally or a calculated value from the measured amount, and a calculated value from the measured amount or measured amount in an abnormal state where the device is abnormal. Means for estimating the device or means for reproducing the abnormal state of the device, means for calculating the distance between the normal state, the abnormal state, and the current operating state of the device, and the distance or abnormality between the current operating state of the device and the normal state Means for estimating the normal state, abnormal state, degree of abnormality, or cause of abnormality of a device from the change in distance from the state, provided in the vicinity of the refrigeration cycle apparatus or remotely via a network or public line, and via the network or public line It is configured to transmit measurement data or calculation values.

  The refrigeration cycle apparatus according to the present invention measures the high pressure measuring means for measuring the high pressure of the refrigeration apparatus or the condensation temperature measuring means for measuring the high pressure saturation temperature, the low pressure measuring means for measuring the low pressure or the low pressure saturation temperature. An evaporating temperature measuring means, a liquid temperature measuring means, a discharge temperature measuring means or an intake temperature measuring means, a computing means for obtaining a composite variable from these measured values, and a measured value of each measuring means or a value calculated from them Storage means for storing a calculated value such as a composite variable; comparison means for comparing a value stored in the past by the storage means with a current measured value or calculated value; and determination for determining refrigerant leakage based on the comparison result The refrigeration cycle abnormality such as refrigerant leakage can be accurately detected.

  In addition, the calculation means calculates the degree of abnormality such as the refrigerant leakage amount in the refrigeration cycle, and predicts the time when the value reaches the abnormal limit at which the predetermined cooling capacity can be maintained from that value. Can be found in. The computing means 22, the storage means 23, the comparing means 24, the judging means 25, and the output means 26 may be combined. For example, when performing remote monitoring using a general-purpose computer such as a personal computer, all these functions are performed. It can be realized by computer software, and the output in this case is output to an external storage medium such as a display or a hard disk.

  The unit space is composed of an average value, a standard deviation, and a correlation coefficient of each feature amount, but other conditions may be added. In the remote monitoring system, these are on the substrate of the refrigeration cycle apparatus. It is stored in a memory or a remotely installed personal computer. When learning all or part of the actual data, the data that does not need to be learned may be stored in either the memory on the board of the refrigeration cycle device or a personal computer, but the data that needs to be learned is stored in the hard disk of the personal computer. To remember.

  In the present invention, a compressor, a condenser, an expansion means, and an evaporator are connected by piping, and a refrigerant is circulated therein to constitute a refrigeration cycle, and any one of flow paths from the discharge side of the compressor to the expansion means High pressure measuring means for measuring the pressure or high pressure of the refrigerant at the position or condensing temperature measuring means for measuring the high pressure saturation temperature, and the pressure or low pressure of the refrigerant at any position in the flow path from the expansion means to the suction side of the compressor Low pressure measuring means for measuring the evaporating temperature measuring means for measuring the low pressure saturation temperature, liquid temperature measuring means for measuring the temperature at any position in the flow path from the condenser to the expanding means, or the condenser from the compressor A discharge temperature measuring means for measuring the temperature at any position in the flow path leading to the suction, or a suction temperature measuring means for measuring the temperature at any position in the flow path from the evaporator to the compressor. Or Calculation means for obtaining a composite variable from the measurement values of the contraction temperature measurement means, the low pressure measurement means or the evaporation temperature measurement means, the liquid temperature measurement means, the discharge temperature measurement means or the suction temperature measurement means, and the measurement values of each measurement means or the calculation from them Storage means for storing calculated values such as composite variables, comparison means for comparing a value stored in the past with the storage means and a current measured value or calculated value, and determining a refrigeration cycle abnormality based on the comparison result And a judging means for performing.

  Furthermore, by providing an output means for outputting a time when the predicted abnormality limit is reached by an electric signal such as a voltage or current magnitude, it is possible to transmit an abnormality such as degradation or leakage discovered at an early stage. In addition, the refrigerant is a refrigerant containing not only flammable components, but the detected abnormality can be transmitted at an early stage by connecting an alarm device that issues an alarm by sound or light to the output means. In addition, abnormalities can be detected early by monitoring and judging data remotely.

It is a whole conceptual diagram of Embodiment 1 of this invention. It is a block diagram of the refrigerating cycle apparatus of Embodiment 1 of this invention. It is a Mollier diagram which shows operation | movement of the refrigerating cycle of Embodiment 1 of this invention. It is explanatory drawing explaining the relationship between the distance of Mahalanobis of Embodiment 1 of this invention, and its appearance rate. It is a calculation flowchart of the Mahalanobis distance of Embodiment 1 of the present invention. It is a figure which shows the concept of the Mahalanobis distance of Embodiment 1 of this invention. It is a figure which shows the relationship between the refrigerant | coolant leakage degree of Embodiment 1 of this invention, and the distance of Mahalanobis. It is an operation | movement flowchart of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is explanatory drawing showing the time transition of the Mahalanobis distance of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is a figure which shows the relationship between the reference | standard space and abnormal space of Embodiment 1 of this invention. It is an operation | movement flowchart of Embodiment 1 of this invention. It is a figure which shows the test result of the refrigerant | coolant leakage of Embodiment 1 of this invention. It is a figure which shows the division | segmentation method of the reference space in the year of Embodiment 1 of this invention. It is another block diagram of the refrigerating-cycle apparatus of Embodiment 1 of this invention. It is explanatory drawing showing the concept of the Mahalanobis distance of the abnormal space of Embodiment 1 of this invention, and normal space. It is a flowchart showing the novel abnormality learning function content of Embodiment 1 of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Refrigerating-cycle apparatus, 2 Microcomputer, 3 Telephone line or LAN, 4 Remote monitoring room, 5 Computer, 6 Display apparatus, 7 Input apparatus, 8 Warning lamp, 9 Speaker, 10 Accumulator, 11 Compressor, 12 Condenser, 13 Expansion Valve, 14 Evaporator, 35 Liquid reservoir, 36 Flow path opening / closing means, 37 Supercooling means, 38 Liquid pipe temperature detecting means, 41 Data collecting means, 45 Condensing fan, 48 Oil separator, 53 Office, 54 Alarm 55 Data transmission / reception means, 56 Network or public line, 61 Blowing temperature detection means, 62 Inhalation temperature detection means

Claims (6)

A refrigerant in any position of a refrigeration cycle that forms a fluid circuit in which a refrigerant flows by connecting a compressor, a condenser, an expansion means, and an evaporator with piping, and a flow path from the discharge side of the compressor to the expansion means Any one of a high-pressure side measuring unit that is at least one of a high-pressure measuring unit that measures a high pressure and a condensation temperature measuring unit that measures the high-pressure saturation temperature, and a flow path from the expansion unit to the suction side of the compressor and the low-pressure side measuring means at least either of the low pressure measurement means and the evaporation temperature measurement means for measuring the saturation temperature of the low-pressure measuring low pressure is the pressure of the refrigerant in Kano position, leading to the expansion means from said condenser liquid temperature measuring means for measuring the refrigerant temperature at any position of the flow path, discharge temperature measurement means and the evaporator to measure the discharge temperature of any position of the flow path leading to the condenser from the compressor A refrigerant temperature measurement means at least either of the suction temperature measurement means for measuring the intake temperature of any position of the flow passage in al the compressor, the high pressure side measurement means, said low pressure side measurement means, the refrigerant temperature Using the measured value measured by the measuring means and the calculated value calculated from the measured value as variables, state quantities having the characteristics of the plurality of measured values, which are aggregates having a distribution due to at least deviation of these variables. A calculating means for calculating, and a state quantity calculated from a measured value that is measured when the refrigeration cycle is determined to be abnormal or set to obtain an abnormal condition, A state quantity storage means for classifying as an abnormal degree of the abnormal state of the refrigeration cycle and setting it as a plurality of state quantities in comparison with the state quantity of the refrigeration cycle; Comparison means for comparing the operation state quantity calculated from the measured value and the initial state quantity or the plurality of state quantities stored in the state quantity storage means, the operation measurement value, the operation state quantity, and the comparison Transmission means formed by wire or wirelessly transmitting at least one of the comparison results compared by the means, and the state quantity calculated and set by the calculation means is a change in the outside air temperature, the detected high pressure A refrigeration cycle monitoring system having different settings depending on the range of the refrigeration. In order to classify as the degree of abnormality, a measured value that was measured when the refrigeration cycle was determined to be in an abnormal state or a level set to obtain an abnormal state was calculated and calculated from this measured value 2. The refrigeration cycle monitoring system according to claim 1, wherein the calculated value is a value obtained by setting at least one of the high pressure, the low pressure, the discharge temperature, the subcool, and the superheat as another value . In order to classify the degree of abnormality, the calculated value calculated from the measured value that is measured when the refrigeration cycle is determined to be in an abnormal state or the level set to obtain the abnormal state is The refrigeration cycle monitoring system according to claim 2 , wherein the average value of the subcool is processed to a small value . 2. The refrigeration cycle according to claim 1, wherein a determination result is transmitted by determining which one of the plurality of state quantities in which the operation state quantity is set is close based on a comparison result compared by the comparison unit. Monitoring system. The comparison of the difference between the operation state quantity and the abnormality degree is repeated, and the elapsed time and the difference from the operation state quantity to the abnormality degree or the difference between the operation state quantity to be repeatedly compared and the abnormality degree change. The refrigeration cycle monitoring system according to claim 1 , further comprising: a failure prediction unit that estimates a time from a speed until a failure of the refrigeration cycle is likely to occur, and transmitting the estimated time . A state quantity calculated by at least a deviation of the variable based on a plurality of the measurement values and the like by the calculation means, and is calculated and stored by a combination of a plurality of types selected from the variables. A plurality of types of state quantities having the following characteristics: the comparison means compares the plurality of types of state quantities with the operation state quantity to determine the cause of abnormality, and transmits the determination result. The refrigeration cycle monitoring system according to claim 1 or 4 .

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