JPWO2020075262A1 - Failure sign detector - Google Patents

Abstract

The failure precursor detection device detects the precursor of failure in equipment related to air conditioning, which is operated by the power supplied from the power supply via the power conversion device, and is related to the equipment related to the equipment input from the equipment. A feature quantity acquisition unit that acquires the feature quantity of the equipment based on the information, a temperature rise estimation unit that estimates the temperature rise amount of the internal structure of the equipment based on the acquired feature quantity, and a threshold value for the temperature rise amount. It is provided with a storage unit for storing and a determination unit for determining the possibility of failure of equipment and the degree of damage to the internal structure based on the comparison result between the estimated amount of temperature rise and the threshold value.

Description

The present invention relates to a failure precursor detection device that detects a precursor of a failure in equipment mounted on a refrigerating and air-conditioning device.

Conventionally, various methods for detecting abnormalities in refrigerating and air-conditioning equipment have been proposed. For example, Patent Document 1 discloses a method of estimating a motor temperature using the current, voltage, and control constant of a motor driving a compressor, and detecting an abnormality inside the compressor based on the estimation result.

Patent Document 2 describes a method of detecting a pulsation value with respect to a current average value of a motor driving a compressor and a rotation speed of the motor, and detecting an abnormality inside the compressor based on the detected pulsation value and the rotation speed. It is disclosed. In this method, the internal state of the compressor is estimated by analyzing the magnitude and phase of the current of each phase of the three-phase current output to the motor of the compressor and estimating the torque or rotation speed of the motor. ..

In Patent Document 3, a weighting coefficient is arranged on a map with the suction pressure of the refrigerant in the compressor as the horizontal axis and the discharge pressure as the vertical axis, and the weighting coefficient is determined by the suction pressure and the discharge pressure of the acquired refrigerant. Based on this, a method for diagnosing an abnormality inside the compressor is disclosed. In this method, when the temperature rises inside the compressor due to an abnormality such as poor lubrication, the temperature inside the compressor is estimated by utilizing the influence of the temperature rise on the temperature and pressure of the refrigerant circuit. To.

Japanese Unexamined Patent Publication No. 2004-201425 International Publication No. 2017/042949 Japanese Unexamined Patent Publication No. 2004-85088

By the way, the motor that drives the compressor is affected by heat dissipation due to constant contact with the refrigerant and the heat capacity of the motor material itself. Therefore, the motor temperature does not rise instantly when an abnormality occurs. That is, when the motor temperature rises due to an abnormality inside the compressor, it is considered that the abnormality continues to occur at least every few minutes. Therefore, as described in Patent Document 1, the method of detecting an abnormality inside the compressor using the motor temperature can detect an abnormality that continues until the motor temperature rises. Anomalies that do not continue until the motor temperature rises may be overlooked.

Further, the current value of the motor differs depending on the motor specifications, load conditions, and the like. Therefore, in order to set the threshold value for detecting an abnormality with reference to the normal time, it is necessary to measure the normal value of the entire operating condition range for each model of the motor using an actual machine. Therefore, as described in Patent Document 2, a method of detecting an abnormality inside the compressor with high accuracy by using a pulsation value with respect to the current average value of the motor requires a huge development load.

Further, the temperature rise inside the compressor that causes changes in the temperature and pressure of the refrigerant circuit occurs when the inside of the compressor is already in a serious failure state. Therefore, as described in Patent Document 3, the method of detecting an abnormality inside the compressor based on the suction pressure and the discharge pressure of the compressor cannot detect the abnormality before a serious abnormality occurs. ..

Further, in order to place the weighting coefficient on the map based on the suction pressure and the discharge pressure of the refrigerant in the compressor, it is necessary to measure the entire range of the map using an actual machine. That is, a method of detecting an abnormality inside the compressor using the weighting coefficient arranged on the map based on the suction pressure and the discharge pressure of the refrigerant requires a huge development load.

The present invention has been made in view of the above problems, and quickly and surely detects a sign of failure in equipment related to air conditioning such as a compressor, and accurately determines the degree of damage to the internal structure of the equipment. It is an object of the present invention to provide a failure precursor detection device which can be used.

The failure precursor detection device of the present invention is a failure precursor detection device that detects a failure precursor in equipment related to air conditioning, which is operated by electric power supplied from a power source via a power conversion device, and is a failure precursor detection device from the equipment. Based on the input equipment-related information about the equipment, the feature amount acquisition unit that acquires the feature amount of the equipment, and the temperature rise amount of the internal structure of the equipment is estimated based on the acquired feature amount. Based on the result of comparison between the temperature rise estimation unit, the storage unit that stores the threshold value for the temperature rise amount, and the estimated temperature rise amount and the threshold value, the possibility of failure of the equipment and damage to the internal structure It is provided with a determination unit for determining the degree.

According to the present invention, the feature amount of the equipment is extracted based on the input equipment-related information, and the temperature rise amount of the internal structure of the equipment is estimated based on the extracted feature amount. Then, by comparing the estimated temperature rise amount with the threshold value, the possibility of failure of the equipment and the degree of damage are determined. Therefore, it is possible to quickly and surely detect a sign of failure in equipment related to air conditioning, and accurately determine the degree of damage to the internal structure of equipment.

It is the schematic which shows an example of the structure of the air-conditioning apparatus to which the failure precursor detection apparatus which concerns on Embodiment 1 is applied. It is a block diagram which shows an example of the structure of the failure precursor detection apparatus which concerns on Embodiment 1. FIG. It is a hardware block diagram which shows an example of the structure of the failure precursor detection device of FIG. It is a hardware block diagram which shows another example of the structure of the failure precursor detection device of FIG. It is a flowchart which shows an example of the flow of the failure precursor detection processing by the failure precursor detection apparatus which concerns on Embodiment 1. FIG.

Embodiment 1.
Hereinafter, the failure precursor detection device according to the first embodiment of the present invention will be described. The failure sign detection device according to the first embodiment is applied to, for example, an air conditioner, and detects a failure sign of equipment related to air conditioning such as a compressor.

[Structure of air conditioner 100]
First, the configuration of the air conditioner 100 to which the failure sign detection device 1 according to the first embodiment is applied will be described. FIG. 1 is a schematic view showing an example of the configuration of an air conditioner 100 to which the failure precursor detection device 1 according to the first embodiment is applied. The air conditioner 100 of FIG. 1 performs a cooling operation or a heating operation by a heat pump system.

As shown in FIG. 1, the air conditioner 100 includes a compressor 101, a condenser 102, an expansion device 103, an evaporator 104, a control device 105, and a power conversion device 110. In the air conditioner 100, the compressor 101, the condenser 102, the expansion device 103, and the evaporator 104 are sequentially connected by the refrigerant pipes to form a refrigerant circuit in which the refrigerant circulates in the refrigerant pipes.

Of these, the compressor 101 has a compression element 101a that compresses the refrigerant, and a motor 101b that is connected to the compression element 101a and to which power is supplied by the power conversion device 110. The electric power conversion device 110 receives electric power from the power source 200 and supplies the converted electric power to the motor 101b to rotate and drive the motor 101b. The rotation speed of the motor 101b is controlled by the control device 105.

The condenser 102 exchanges heat between the refrigerant and air to condense the refrigerant. The expansion device 103 expands the refrigerant. The opening degree of the expansion device 103 is controlled by the control device 105. The evaporator 104 exchanges heat between the refrigerant and air to evaporate the refrigerant.

The control device 105 controls the operation of the entire air conditioner 100 based on information received from various sensors (not shown) provided in each part of the air conditioner 100. In the first embodiment, the control device 105 controls the motor 101b of the compressor 101 based on the information received from the failure precursor detection device 1 described later. The control device 105 is composed of hardware such as a circuit device that realizes various functions by executing software on an arithmetic unit such as a microcomputer.

(Failure sign detection device 1)
Further, in the first embodiment, the air conditioner 100 includes a failure sign detection device 1. FIG. 2 is a block diagram showing an example of the configuration of the failure precursor detection device 1 according to the first embodiment. As shown in FIG. 2, the failure precursor detection device 1 includes a feature amount acquisition unit 11, a temperature rise estimation unit 12, a determination unit 13, a storage unit 14, and a notification unit 15. The failure sign detection device 1 is composed of hardware such as a circuit device that realizes various functions by executing software on an arithmetic unit such as a microcomputer.

The feature amount acquisition unit 11 receives device-related information from the outside and acquires the feature amount based on the device-related information. The feature quantity is a physical quantity having characteristics related to a precursor of failure of the compressor 101, such as the power consumption of the motor 101b for driving the compressor 101. The feature amount is acquired by using, for example, an arithmetic expression corresponding to the input device-related information. The device-related information is a physical quantity related to the operation of equipment such as the compressor 101, which is necessary for acquiring the feature amount, and is, for example, information obtained when the compressor 101 operates. The device-related information is, for example, a primary input from the power supply 200 input to the power converter 110, a secondary input output from the power converter 110 and input to the motor 101b for driving the compressor 101, and the like. is there.

The temperature rise estimation unit 12 estimates the temperature rise amount of the internal structure of the compressor 101 based on the feature amount acquired by the feature amount acquisition unit 11. The amount of temperature rise is estimated using, for example, an arithmetic expression according to the acquired feature amount.

The determination unit 13 compares the amount of temperature increase estimated by the temperature increase estimation unit 12 with the lower limit threshold value stored in the storage unit 14, and determines the possibility of failure of the compressor 101 based on the comparison result. Further, when the determination unit 13 determines that the compressor 101 may fail, the temperature rise amount is compared with the determination threshold value stored in the storage unit 14, and the degree of damage inside the compressor 101 is determined. judge. The determination unit 13 outputs information indicating the determination result to the notification unit 15 and the control device 105.

The lower limit threshold value is a threshold value indicating a boundary as to whether or not the compressor 101 may fail. The determination threshold value is used to determine the degree of damage inside the compressor 101 when it is determined that the compressor 101 "may break down". The determination threshold is a value larger than the lower limit threshold and is set stepwise.

The storage unit 14 stores in advance various types of information used when processing is performed by each unit of the failure precursor detection device 1. In the first embodiment, the storage unit 14 stores in advance a lower limit threshold value set for the temperature rise amount used in the determination unit 13 and one or a plurality of determination threshold values.

The notification unit 15 notifies the possibility of failure and the degree of damage to the compressor 101 according to the determination result by the determination unit 13. As the notification unit 15, for example, a display means such as a display and an LED (Light Emitting Diode), or an audio output means such as a speaker is used. When the notification unit 15 is a display, information according to the determination result is displayed in characters, figures, or the like. When the notification unit 15 is an LED, information according to the determination result is displayed by turning on, blinking, turning off, or the like. When the notification unit 15 is a speaker, information according to the determination result is notified by voice.

FIG. 3 is a hardware configuration diagram showing an example of the configuration of the failure precursor detection device 1 of FIG. When various functions of the failure sign detection device 1 are executed by hardware, the failure sign detection device 1 of FIG. 2 includes a processing circuit 21 and an output device 22 as shown in FIG. Each function of the feature amount acquisition unit 11, the temperature rise estimation unit 12, the determination unit 13, and the storage unit 14 of FIG. 2 is realized by the processing circuit 21. The notification unit 15 is the output device 22 of FIG.

When each function is executed in hardware, the processing circuit 21 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), or an FPGA (Field-Programmable Gate). Array) or a combination of these is applicable. The functions of the feature amount acquisition unit 11, the temperature rise estimation unit 12, the determination unit 13, and the storage unit 14 may be realized by the processing circuit 21, or the functions of each part may be realized by one processing circuit 21. Good.

FIG. 4 is a hardware configuration diagram showing another example of the configuration of the failure precursor detection device 1 of FIG. When various functions of the failure sign detection device 1 are executed by software, the failure sign detection device 1 of FIG. 2 includes a processor 31, a memory 32, and an output device 33, as shown in FIG. Each function of the feature amount acquisition unit 11, the temperature rise estimation unit 12, the determination unit 13, and the storage unit 14 is realized by the processor 31 and the memory 32. The notification unit 15 in FIG. 2 is the output device 33 in FIG.

When each function is executed by software, the functions of the feature amount acquisition unit 11, the temperature rise estimation unit 12, and the determination unit 13 are realized by software, firmware, or a combination of software and firmware. The software and firmware are written as a program and stored in the memory 32. The processor 31 realizes the functions of each part by reading and executing the program stored in the memory 32.

As the memory 32, for example, RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable and Programmable ROM), EEPROM (Electrically Erasable Memory, etc.) Is used. Further, as the memory 32, for example, a removable recording medium such as a magnetic disk, a flexible disk, an optical disk, a CD (Compact Disc), an MD (Mini Disc), and a DVD (Digital Versaille Disc) may be used.

[Operation of air conditioner 100]
The operation of the air conditioner 100 will be described with reference to FIG. When the motor 101b of the compressor 101 is rotationally driven by the power converter 110, the compression element 101a of the compressor 101 connected to the motor 101b compresses the low-temperature low-pressure refrigerant, and the compressor 101 discharges the high-temperature and high-pressure gas refrigerant. To do. The high-temperature and high-pressure gas refrigerant discharged from the compressor 101 flows into the condenser 102.

The high-temperature and high-pressure gas refrigerant flowing into the condenser 102 condenses while exchanging heat with air and dissipating heat, becomes a high-pressure liquid refrigerant, and flows out of the condenser 102. The high-pressure liquid refrigerant flowing out of the condenser 102 is expanded and depressurized by the expansion device 103 to become a low-temperature low-pressure gas-liquid two-phase refrigerant, which flows into the evaporator 104.

The low-temperature low-pressure gas-liquid two-phase refrigerant that has flowed into the evaporator 104 cools the air by exchanging heat with the air, absorbing heat and evaporating, and becomes a low-temperature low-pressure gas refrigerant that flows out of the evaporator 104. The low-temperature low-pressure gas refrigerant flowing out of the evaporator 104 is sucked into the compressor 101 and compressed again. Hereinafter, the above-mentioned operation is repeated.

Although the air conditioner 100 has been described as an example in FIG. 1, the description is not limited to this, and for example, a heat pump device, a refrigeration device, and other refrigeration cycle devices may be generally applied.

[Failure sign detection processing]
Next, the failure precursor detection process by the failure precursor detection device 1 according to the first embodiment will be described. In the compressor 101 as equipment related to air conditioning, it is generally known that the temperature of the internal structure rises when a failure occurs due to insufficient or depleted oil for sliding parts such as bearings. .. This is because heat is generated due to friction due to the lack of oil and the increase in frictional resistance of the sliding portion.

On the other hand, the temperature rise of the internal structure affects the device-related information which is a physical quantity having characteristics related to the precursor of the failure of the compressor 101. For example, an increase in the frictional resistance between the shaft and the bearing of the compressor 101 as the temperature of the internal structure rises causes a change in the input to the compressor 101 and the torque of the motor 101b that drives the compressor 101, etc. Occurs.

As described above, there is a correlation between the amount of temperature rise in the internal structure of the compressor 101 and the amount of features. Then, the feature quantity can be acquired from the device-related information which is a physical quantity related to the operation of the compressor 101. Therefore, if the amount of temperature rise can be estimated based on the device-related information affected by the temperature rise, a failure in the compressor 101 can be detected.

Further, the temperature rise of the internal structure of the compressor 101 occurs not at the time when the compressor 101 completely fails, but at the stage of a precursor of the failure, and as the amount of temperature rise increases, the degree of damage inside the compressor 101 increases. Will be higher. That is, the degree of damage inside the compressor 101 can be determined from the magnitude of the amount of temperature rise.

Therefore, in the first embodiment, the feature amount for the failure of the equipment such as the compressor 101 is acquired, and the temperature rise amount of the internal structure of the equipment is estimated from the acquired feature amount. Then, based on the estimated amount of temperature rise, the precursor of failure of the equipment and the degree of damage are detected.

FIG. 5 is a flowchart showing an example of the flow of the failure precursor detection process by the failure precursor detection device 1 according to the first embodiment. First, when device-related information is input to the feature amount acquisition unit 11 from the outside, the feature amount acquisition unit 11 acquires the feature amount based on the input device-related information in step S1. In step S2, the temperature rise estimation unit 12 estimates the temperature rise amount of the internal structure of the compressor 101 based on the feature amount acquired by the feature amount acquisition unit 11.

In step S3, the determination unit 13 compares the amount of temperature rise estimated in step S2 with the lower limit threshold value stored in the storage unit 14 and determines whether or not the compressor 101 may fail. .. As a result of the comparison, when the amount of temperature rise exceeds the lower limit threshold value (step S3; Yes), the determination unit 13 determines in step S4 that the compressor 101 "may fail".

Next, the determination unit 13 determines the degree of damage inside the compressor 101 in step S5. One or more determination thresholds stored in the storage unit 14 are used to determine the degree of damage to the compressor 101, and the degree of damage to the compressor 101 is determined based on the relationship between the amount of temperature rise and the one or more determination thresholds. Is determined.

The determination unit 13 outputs information indicating the possibility of failure of the compressor 101 and the degree of damage to the notification unit 15 and the control device 105 of the air conditioner 100. As a result, the notification unit 15 notifies the possibility of failure of the compressor 101 and the degree of damage in step S6. At this time, the notification unit 15 may perform different notifications according to the determined damage degree so that the damage degree determined in step S5 can be identified. Specifically, when the notification unit 15 is a display, the notification unit 15 displays information indicating the possibility of failure of the compressor 101, such as "the compressor 101 may fail", and the degree of damage in that case. Display the information to be shown.

On the other hand, in step S3, when the amount of temperature rise is equal to or less than the lower limit threshold value (step S3; No), the determination unit 13 determines that the compressor 101 is “normal” in step S7.

As described above, in the failure precursor detection device 1 according to the first embodiment, the temperature rise amount of the internal structure of the compressor 101 is estimated based on the feature amount acquired from the device-related information. Then, based on the estimated amount of temperature rise, the possibility of failure of the compressor 101 and the degree of damage to the internal structure of the compressor 101 are determined. Thereby, the possibility of failure and the degree of damage of the compressor 101 can be determined without actually measuring the temperature of the internal structure of the compressor 101. Therefore, it is possible to reliably detect the failure of the compressor 101 before the operation of the compressor 101 becomes impossible due to the actual damage. In addition, the failure of the compressor 101 can be quickly detected before the compressor 101 completely fails.

In the first embodiment, the estimated temperature rise amount and the preset lower limit threshold value are compared, and it is determined that the compressor 101 may fail when the temperature rise amount exceeds the lower limit threshold value. To. Thereby, the possibility of failure of the compressor 101 can be easily determined.

In the first embodiment, when it is determined that the compressor 101 may fail, the temperature increase amount is compared with one or more determination threshold values, and based on the relationship between the temperature increase amount and the determination threshold value. , The degree of damage to the internal structure of the compressor 101 is determined. This makes it possible to easily determine the degree of damage to the compressor 101.

Embodiment 2.
Next, Embodiment 2 of the present invention will be described. In the second embodiment, the case where the power consumption of the motor 101b of the compressor 101 is applied as a feature amount will be described. In the following description, the parts common to the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

[Structure of air conditioner 100]
The configuration of the air conditioner 100 according to the second embodiment is the same as that of the air conditioner 100 according to the first embodiment shown in FIG. Further, the configuration of the failure sign detection device 1 is the same as that of the failure sign detection device 1 according to the first embodiment shown in FIG.

In the second embodiment, the feature amount acquisition unit 11 of the failure precursor detection device 1 of FIG. 2 receives a primary input (primary current, primary) input from the power supply 200 to the power conversion device 110 as device-related information. Voltage), as well as the number of revolutions of the compressor 101, the discharge pressure and the suction pressure are input. These device-related information is measured using an external measuring device or the like, and the measurement result is input to the feature amount acquisition unit 11.

The feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount based on the input primary input, the rotation speed of the compressor 101, the discharge pressure, and the suction pressure.

The temperature rise estimation unit 12 estimates the temperature rise amount of the internal structure of the compressor 101 based on the power consumption acquired by the feature amount acquisition unit 11 and the specification information stored in the storage unit 14. The estimation of the amount of temperature rise will be described later. The specification information is various parameters determined by the specifications of the internal structure of the compressor 101. For example, the specification information includes the volume of the bearing which is a sliding portion in the compressor 101, the specific heat and density of the material used for the bearing, and the like.

Similar to the first embodiment, the storage unit 14 stores the lower limit threshold value and one or a plurality of determination threshold values in advance. Further, in the second embodiment, the storage unit 14 stores in advance the specification information used when the temperature rise estimation unit 12 estimates the temperature rise amount.

[Estimation of temperature rise]
As described in the first embodiment, the temperature rise of the internal structure of the compressor 101 is generated by the increase of the frictional resistance of the sliding portion. As a result, the torque of the motor 101b of the compressor 101 changes differently from the normal time.

Here, the torque of the motor 101b is proportional to the input power. Specifically, when the torque of the motor 101b changes, the primary input input from the power supply 200 to the power conversion device 110 also changes accordingly. Further, when the primary input from the power supply 200 changes, the power consumption of the motor 101b obtained from the primary current and the primary voltage, which are the primary inputs, also changes.

Therefore, in the second embodiment, the power consumption of the motor 101b that drives the compressor 101 is applied as a feature amount, and the amount of temperature rise that occurs in response to the change in power consumption is estimated. Then, based on the estimated amount of temperature rise, the possibility of failure and the degree of damage of the compressor 101 are determined.

(Acquisition of features)
First, the power consumption of the motor 101b as a feature amount in the second embodiment is calculated based on the equation (1). In the formula (1), the "output" is the output power from the power supply 200. "Efficiency" is the compressor efficiency of the compressor 101.

The output power from the power source 200 can be obtained by multiplying the primary current input from the power source 200 to the power conversion device 110 by the primary voltage. Further, the efficiency of the compressor 101 can be obtained by obtaining a function determined by the rotation speed of the compressor 101 and the differential pressure between the discharge pressure and the suction pressure of the refrigerant.

(Estimation of temperature rise)
Next, the temperature rise amount ΔT [° C.] is calculated using the equation (2) based on the power consumption and the specification information. In the formula (2), the power difference ΔP [W] indicates the difference in power consumption at the two measurement time points. The duration t [sec] indicates the time difference between the two measurement time points when calculating the power difference ΔP. The specific heat c [kJ / kg · ° C.] indicates the specific heat of the material used for the sliding portion of the bearing or the like in the compressor 101. The density ρ [kg / m ³ ] indicates the density of the material used for the sliding portion in the compressor 101. The volume V [m ³ ] indicates the volume of the sliding portion in the compressor 101. The specific heat c, the density ρ, and the volume V are information included in the specification information stored in the storage unit 14.

Here, the power difference ΔP is obtained by taking the difference in power sampled at set intervals at adjacent time points. Specifically, the power difference ΔP is the difference in power between the time point n and the time point n-1. Further, the duration t is the length of adjacent sampling times, and specifically, is the time difference between the time point n and the time point n-1.

[Failure sign detection processing]
As shown in the flowchart of FIG. 5, in step S1, the feature amount acquisition unit 11 inputs the primary current and the primary voltage as device-related information, and the rotation speed, discharge pressure, and suction pressure of the compressor 101. Will be done. Based on these device-related information, the feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount using the equation (1).

In step S2, the temperature rise estimation unit 12 uses the equation (2) based on the power consumption as the feature amount acquired by the feature amount acquisition unit 11 and the specification information, and uses the equation (2) to increase the temperature of the internal structure of the compressor 101. Calculate ΔT. Each process of steps S3 to S7 is the same as that of the first embodiment.

(First modification)
A first modification of the second embodiment will be described. In the first modification, as device-related information, a secondary input (secondary power) input from the power converter 110 to the motor 101b of the compressor 101, and the rotation speed, discharge pressure, and suction pressure of the compressor 101. Is input to the failure sign detection device 1. The secondary input (secondary power) as device-related information is acquired using a three-phase wattmeter or a two-power meter method. Based on these device-related information, the feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount using the equation (1).

(Failure sign detection processing)
As shown in the flowchart of FIG. 5, in step S1, the secondary power as device-related information, the rotation speed of the compressor 101, the discharge pressure, and the suction pressure are input to the feature amount acquisition unit 11. Based on these device-related information, the feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount using the equation (1). Each process of steps S2 to S7 is the same as that of the second embodiment.

(Second modification)
A second modification of the second embodiment will be described. In the second modification, the q-axis current Iq and the q-axis voltage Vq in the power conversion device 110, and the rotation speed, discharge pressure, and suction pressure of the compressor 101 are input to the failure precursor detection device 1 as device-related information. To. The q-axis current Iq and the q-axis voltage Vq as device-related information can be obtained from the power converter 110. Based on these device-related information, the feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount using the equation (1).

(Failure sign detection processing)
As shown in the flowchart of FIG. 5, in step S1, the feature amount acquisition unit 11 has the q-axis current Iq and the q-axis voltage Vq as device-related information, and the rotation speed, discharge pressure, and suction pressure of the compressor 101. Is entered. Based on these device-related information, the feature amount acquisition unit 11 acquires the power consumption of the motor 101b as a feature amount using the equation (1). Each process of steps S2 to S7 is the same as that of the second embodiment.

As described above, in the failure precursor detection device 1 according to the second embodiment, the specification information indicating the specifications of the internal structure of the compressor 101 is stored in advance, and the power consumption of the compressor 101 is acquired as a feature amount. Will be done. Then, the amount of temperature rise in the internal structure of the compressor 101 is estimated based on the power consumption and the specification information. As a result, the amount of temperature rise according to the amount of material of the compressor 101 and the like can be estimated, and the possibility of failure and the degree of damage of the compressor 101 can be accurately estimated.

At this time, the power consumption as the feature amount may be acquired based on the primary power supplied from the power source 200 to the power conversion device 110, or may be supplied from the power conversion device 110 to the motor 101b of the compressor 1012. It may be acquired based on the next power. Further, the power consumption may be acquired based on the q-axis current and the q-axis voltage in the power converter 110.

Embodiment 3.
Next, Embodiment 3 of the present invention will be described. In the third embodiment, of the three-phase electric power supplied to the motor 101b of the compressor 101, for example, a case where the electric power ratio between frames based on the U-phase current is applied as a feature amount will be described. In the following description, the parts common to the first and second embodiments are designated by the same reference numerals, and detailed description thereof will be omitted.

[Structure of air conditioner 100]
The configuration of the air conditioner 100 according to the third embodiment is the same as that of the air conditioner 100 according to the first and second embodiments shown in FIG. Further, the configuration of the failure precursor detection device 1 is the same as that of the failure precursor detection device 1 according to the first and second embodiments shown in FIG.

In the third embodiment, the U-phase current of the three-phase power supplied from the power conversion device 110 is input to the feature amount acquisition unit 11 of the failure precursor detection device 1 of FIG. 2 as device-related information. .. The U-phase current as device-related information is measured using an external measuring device or the like, and the measurement result is input to the feature amount acquisition unit 11.

The feature amount acquisition unit 11 acquires the power ratio Energy_d as a feature amount based on the input U-phase current. The power ratio Energy_d indicates the ratio of the power value Energy (τ) and the power value Energy (τ-1) in each frame of the frame τ, which is a set of preset number of samples, and the immediately preceding frame τ-1. ..

The temperature rise estimation unit 12 estimates the temperature rise amount of the internal structure of the compressor 101 based on the power ratio Energy_d acquired by the feature amount acquisition unit 11 and the specification information stored in the storage unit 14. The estimation of the amount of temperature rise will be described later.

Similar to the first embodiment, the storage unit 14 stores the lower limit threshold value and one or a plurality of determination threshold values in advance. Further, in the third embodiment, the storage unit 14 stores in advance the specification information used when the temperature rise estimation unit 12 estimates the temperature rise amount, as in the second embodiment.

[Estimation of temperature rise]
The torque of the motor 101b in the compressor 101 is proportional to the current of one phase of the three-phase current without step-out, for example, the U-phase current. Specifically, when the torque of the motor 101b changes, the U-phase current supplied to the motor 101b also changes accordingly. Further, when the U-phase current changes, the power ratio Energy_d of the motor 101b obtained from the U-phase current also changes. Note that "step-out" means that the indicated frequency for the motor 101b and the actual frequency deviate from each other.

Therefore, in the third embodiment, the power ratio Energy_d of the motor 101b that drives the compressor 101 is applied as a feature amount, and the amount of temperature rise generated according to the power ratio Energy_d is estimated. Then, based on the estimated amount of temperature rise, the possibility of failure and the degree of damage of the compressor 101 are determined.

(Acquisition of features)
First, in order to calculate the power ratio Energy_d of the motor 101b as the feature amount in the third embodiment, the power value Power (τ) in the frame τ is calculated. The power value Power (τ) is calculated based on the equation (3). Here, the frame τ is a set of a preset number of samples, and x _τ (n) in the equation (3) indicates the U-phase current at the sampling time n in the frame τ.

Next, the power value Energy (τ) obtained by logarithmically converting the power value Power (τ) is calculated. The power value Energy (τ) is calculated based on the equation (4).

Then, from the power value Energy (τ) in the frame τ and the power value Energy (τ-1) in the immediately preceding frame τ-1, the power ratio Energy_d of the power value Energy (τ) to the power value Energy (τ-1). Is calculated based on the equation (5).

(Estimation of temperature rise)
Next, the temperature rise amount ΔT is estimated based on the power ratio Energy_d and the specification information. In the third embodiment, a map is created in which the horizontal axis represents the rotation speed of the compressor 101 and the vertical axis represents the differential pressure of the refrigerant in the compressor 101 for each preset power ratio. The map shows the amount of heat generated by the torque fluctuation of the motor 101b estimated from the fluctuation range of the power ratio Energy_d. Therefore, the temperature rise amount ΔT corresponding to the calorific value can be estimated by referring to the material physical properties of the sliding portion such as the bearing in the compressor 101 based on the specification information.

[Failure sign detection processing]
As shown in the flowchart of FIG. 5, the feature amount acquisition unit 11 is input with the U-phase current as device-related information in step S1. The feature amount acquisition unit 11 acquires the power ratio Energy_d as a feature amount using the equations (3) to (5) based on the U-phase current.

In step S2, the temperature rise estimation unit 12 creates a map based on the power ratio Energy_d as the feature amount acquired by the feature amount acquisition unit 11, and based on the calorific value and the specification information described in the created map. , The temperature rise amount ΔT of the internal structure of the compressor 101 is estimated. Each process of steps S3 to S7 is the same as that of the first embodiment.

(Third variant)
A third modification of the third embodiment will be described. In the third modification, as in the third embodiment, the U-phase current supplied from the power converter 110 to the motor 101b of the compressor 101 is input to the failure precursor detection device 1 as device-related information. Then, based on the input U-phase current, the power ratio Power_d between frames is acquired as a feature amount.

(Failure sign detection processing)
As shown in the flowchart of FIG. 5, the feature amount acquisition unit 11 is input with the U-phase current as device-related information in step S1. The feature amount acquisition unit 11 calculates the power value Power (τ) in the frame τ using the equation (3) based on the U-phase current. Then, the feature amount acquisition unit 11 acquires the power ratio Power_d as the feature amount based on the calculated power value Power (τ) in the frame τ and the power value Power (τ-1) in the immediately preceding frame τ-1. ..

In step S2, the temperature rise estimation unit 12 creates a map based on the power ratio Power_d as a feature amount, and based on the calorific value and the specification information described in the created map, the temperature rise estimation unit 12 creates a map, as in the third embodiment. The temperature rise amount ΔT of the internal structure of the compressor 101 is calculated. Each process of steps S3 to S7 is the same as that of the third embodiment.

(Fourth modification)
A fourth modification of the third embodiment will be described. In the fourth modification, as in the third and third modifications, the U-phase current supplied from the power conversion device 110 to the motor 101b of the compressor 101 is the failure precursor detection device 1 as device-related information. Is entered in. Then, based on the input U-phase current, the differential effective value RMS_d, which is the difference value of the effective value (RMS) of the U-phase current between frames, is acquired as a feature amount.

(Failure sign detection processing)
As shown in the flowchart of FIG. 5, the feature amount acquisition unit 11 is input with the U-phase current as device-related information in step S1. The feature amount acquisition unit 11 calculates the effective value RMS (τ) of the U-phase power in the frame τ based on the U-phase current. Then, the feature amount acquisition unit 11 acquires the difference effective value RMS_d as the feature amount based on the calculated effective value RMS (τ) in the frame τ and the effective value RMS (τ-1) in the immediately preceding frame τ-1. To do.

In step S2, the temperature rise estimation unit 12 creates a map based on the differential effective value RMS_d as the feature amount, and based on the calorific value and the specification information described in the created map, as in the third embodiment. , The temperature rise amount ΔT of the internal structure of the compressor 101 is calculated. Each process of steps S3 to S7 is the same as that of the third embodiment.

(Fifth variant)
A fifth modification of the third embodiment will be described. In the fifth modification, as in the third modification, the third modification, and the fourth modification, the U-phase current supplied from the power converter 110 to the motor 101b of the compressor 101 as device-related information. Is input to the failure sign detection device 1. Then, based on the input U-phase current, the difference amplitude value A_d, which is the difference value of the amplitude of the U-phase current between the frames, is acquired as the feature amount. The amplitude value is the maximum amplitude value obtained from the maximum value in the positive direction and the maximum value in the negative direction of one wavelength.

(Failure sign detection processing)
As shown in the flowchart of FIG. 5, the feature amount acquisition unit 11 is input with the U-phase current as device-related information in step S1. The feature amount acquisition unit 11 calculates the amplitude A (τ) of the U-phase power in the frame τ based on the U-phase current. Then, the feature amount acquisition unit 11 acquires the difference amplitude value A_d as the feature amount based on the calculated amplitude A (τ) in the frame τ and the amplitude A (τ-1) in the immediately preceding frame τ-1.

In step S2, the temperature rise estimation unit 12 creates a map based on the difference amplitude value A_d as a feature amount, and based on the calorific value and specification information described in the created map, the internal structure of the compressor 101. The temperature rise amount ΔT is calculated. Each process of steps S3 to S7 is the same as that of the third embodiment.

As described above, in the failure precursor detection device 1 according to the third embodiment, the feature amount is acquired based on the U-phase current supplied to the compressor 101. As the feature amount in this case, the power ratio, which is the ratio of the power value in the set frame to the power value in the immediately preceding frame, is used.

Further, as the feature amount, a differential effective value which is a difference between the effective value of the U-phase current in the set frame and the effective value of the U-phase current in the immediately preceding frame may be used. Further, as the feature amount, the difference amplitude value A_d, which is the difference between the amplitude of the U-phase current in the set frame and the amplitude of the U-phase current in the immediately preceding frame, may be used.

Embodiment 4.
Next, Embodiment 4 of the present invention will be described. In the fourth embodiment, a case where the difference value of the q-axis current in the power conversion device 110 is applied as a feature amount will be described. In the following description, the parts common to the first to third embodiments are designated by the same reference numerals, and detailed description thereof will be omitted.

[Structure of air conditioner 100]
The configuration of the air conditioner 100 according to the fourth embodiment is the same as that of the air conditioner 100 according to the first to third embodiments shown in FIG. Further, the configuration of the failure sign detection device 1 is the same as that of the failure sign detection device 1 according to the first to third embodiments shown in FIG.

In the fourth embodiment, the q-axis current Iq in the power conversion device 110 is input to the feature amount acquisition unit 11 of the failure precursor detection device 1 of FIG. 2 as device-related information. The feature amount acquisition unit 11 acquires the difference value ΔIq of the q-axis current at the sampling interval as the feature amount based on the input q-axis current Iq. The temperature rise estimation unit 12 estimates the temperature rise amount ΔT of the internal structure of the compressor 101 based on the difference value ΔIq of the q-axis current acquired by the feature amount acquisition unit 11. The estimation of the temperature rise amount ΔT will be described later.

[Estimation of temperature rise]
It is known that the torque of the motor 101b is equal to the q-axis current Iq in the power converter 110. Therefore, since the difference value ΔIq of the q-axis current Iq at the sampling interval is a work as it is, the temperature rise amount ΔT at the sampling interval can be estimated by using this difference value ΔIq and the equation (2). it can. In this case, the difference value ΔIq is used instead of the power difference ΔP in the equation (2).

[Failure sign detection processing]
As shown in the flowchart of FIG. 5, the q-axis current Iq as the device-related information is input to the feature amount acquisition unit 11 in step S1. The feature amount acquisition unit 11 calculates the difference value ΔIq at the sampling interval as the feature amount based on the q-axis current Iq.

In step S2, the temperature rise estimation unit 12 calculates the temperature rise amount ΔT of the internal structure of the compressor 101 using the equation (2) based on the difference value ΔIq as the feature amount acquired by the feature amount acquisition unit 11. To do. Each process of steps S3 to S7 is the same as that of the first embodiment.

As described above, in the failure precursor detection device 1 according to the fourth embodiment, based on the difference value between the q-axis current of the power conversion device 110 in the setting frame and the q-axis current in the immediately preceding frame, and the specification information. , The amount of temperature rise in the internal structure of the compressor 101 can be calculated.

1 Failure sign detection device, 11 feature quantity acquisition unit, 12 temperature rise estimation unit, 13 judgment unit, 14 storage unit, 15 notification unit, 21 processing circuit, 22 output device, 31 processor, 32 memory, 33 output device, 100 air Harmonizer, 101 compressor, 101a compression element, 101b motor, 102 condenser, 103 expander, 104 evaporator, 105 controller, 110 power converter, 200 power supplies.

Claims (13)

A failure precursor detection device that detects precursors of failure in equipment related to air conditioning, which is operated by electric power supplied from a power source via a power conversion device.
Based on the equipment-related information about the equipment input from the equipment, the feature acquisition unit that acquires the feature about the equipment, and the feature acquisition unit.
A temperature rise estimation unit that estimates the temperature rise of the internal structure of the equipment based on the acquired features, and a temperature rise estimation unit.
A storage unit that stores a threshold value for the amount of temperature rise,
A failure precursor detection device including a determination unit for determining the possibility of failure of the equipment and the degree of damage to the internal structure based on the result of comparison between the estimated amount of temperature rise and the threshold value. The threshold is
Includes a lower threshold that indicates the boundary of the presence or absence of failure
The determination unit
The failure precursor detection device according to claim 1, wherein the temperature rise amount is compared with the lower limit threshold value, and when the temperature rise amount exceeds the lower limit threshold value, it is determined that the equipment may fail. .. The threshold is
It has a value larger than the lower limit threshold value and further includes one or more determination threshold values set in stages.
The determination unit
When it is determined that the equipment may break down,
The failure precursor detection device according to claim 2, wherein the degree of damage to the internal structure of the equipment is determined based on the relationship between the temperature rise amount and the one or a plurality of determination threshold values. The feature amount acquisition unit
Acquiring the power consumption of the equipment as the feature amount,
The storage unit
Specification information indicating the specifications of the internal structure of the equipment is stored in advance.
The temperature rise estimation unit
The failure precursor detection device according to any one of claims 1 to 3, which estimates the amount of temperature rise of the internal structure of the equipment based on the power consumption of the equipment and the specification information. The feature amount acquisition unit
The failure precursor detection device according to claim 4, wherein the power consumption is acquired based on the primary power output from the power source to the power conversion device. The feature amount acquisition unit
The failure precursor detection device according to claim 4, wherein the power consumption is acquired based on the secondary power supplied from the power conversion device to the equipment. The feature amount acquisition unit
The failure precursor detection device according to claim 4, wherein the power consumption is acquired based on the q-axis current and the q-axis voltage of the power conversion device. The feature amount acquisition unit
The failure precursor detection device according to any one of claims 1 to 3, which acquires the feature amount based on the current of any one phase of the three-phase electric power supplied from the power conversion device to the equipment. The feature amount acquisition unit
Based on the one-phase current, the power ratio indicating the ratio between the power value in the set frame and the power value in the frame immediately before the set frame is acquired as a feature amount.
The storage unit
Specification information indicating the specifications of the internal structure of the equipment is stored in advance.
The temperature rise estimation unit
The failure precursor detection device according to claim 8, wherein the temperature rise amount of the internal structure of the equipment is estimated based on the power ratio and the specification information. The feature amount acquisition unit
Based on the one-phase current, a difference effective value indicating the difference between the effective value of the current in the set frame and the effective value of the current in the frame immediately before the set frame is acquired as a feature amount.
The storage unit
Specification information indicating the specifications of the internal structure of the equipment is stored in advance.
The temperature rise estimation unit
The failure precursor detection device according to claim 8, wherein the temperature rise amount of the internal structure of the equipment is estimated based on the difference effective value and the specification information. The feature amount acquisition unit
Based on the one-phase current, a difference amplitude value indicating the difference between the amplitude of the current in the set frame and the amplitude of the current in the frame immediately before the set frame is acquired as a feature amount.
The storage unit
Specification information indicating the specifications of the internal structure of the equipment is stored in advance.
The temperature rise estimation unit
The failure precursor detection device according to claim 8, wherein the temperature rise amount of the internal structure of the equipment is estimated based on the difference amplitude value and the specification information. The feature amount acquisition unit
The difference between the q-axis current in the setting frame of the power conversion device and the q-axis current in the frame immediately before the setting frame is acquired as a feature amount.
The storage unit
Specification information indicating the specifications of the internal structure of the equipment is stored in advance.
The temperature rise estimation unit
The failure precursor detection device according to claim 8, wherein the amount of temperature rise in the internal structure of the equipment is estimated based on the difference in the q-axis current and the specification information. The failure precursor detection device according to any one of claims 1 to 12, further comprising a notification unit that notifies the possibility of failure and the degree of damage to the equipment according to the determination result by the determination unit.

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