WO2018220760A1

WO2018220760A1 - Air conditioner failure diagnosing device

Info

Publication number: WO2018220760A1
Application number: PCT/JP2017/020309
Authority: WO
Inventors: 赳弘古谷野; 航祐田中
Original assignee: 三菱電機株式会社
Priority date: 2017-05-31
Filing date: 2017-05-31
Publication date: 2018-12-06
Also published as: JPWO2018220760A1

Abstract

This air conditioner failure diagnosing device is provided with: a diagnosis processing device which performs processing related to a failure diagnosis of an air conditioner on data that indicates a state of the air conditioner and data about a control of the air conditioner, wherein the diagnosis processing device includes: a deviation degree calculation unit which calculates the degrees of deviation from criteria for air conditioning characteristics with respect to at least one or more air conditioning characteristics that are indications for indicating the performance of the air conditioner; and a degradation influence calculation unit which performs, on a plurality of predetermined failure factors that cause failure of the air conditioner, a failure diagnosis processing that diagnoses, on the basis of the degrees of deviation, a degradation degree caused by the failure factors.

Description

Air conditioner failure diagnosis device

The present invention relates to an air conditioner failure diagnosis apparatus for diagnosing deterioration or failure of an air conditioner. In particular, it enables evaluation of failure factors that cause failures and the like.

Air conditioners that control at least one of the temperature and humidity of a space have become widespread and have become indispensable for producing a comfortable space. For this reason, the failure of the air conditioner is directly connected to the user's discomfort. In an environment such as a server room or a freezer warehouse, a failure of an air conditioner can lead to a fatal loss in business. Therefore, in recent years, attention has been paid to periodic maintenance of air conditioners, diagnosis of failure, etc. (hereinafter referred to as failure diagnosis).

However, the air conditioner is configured by combining a plurality of functional parts and equipment. For this reason, specialized knowledge is required to identify the maintenance location and failure location.

Therefore, for example, there is one that reduces the load for identifying the cause of failure by displaying the inspection location, part replacement rate, etc. on the display unit (see, for example, Patent Document 1).

JP 2007-192492 A

However, in Patent Document 1 described above, it is impossible to evaluate the influence of the failure factor on the performance of the air conditioner. For this reason, as a result of exchanging parts, it is impossible to quantitatively evaluate how much the merit relating to the exchange can be enjoyed or how the deterioration proceeds.

The present invention has been made in view of the above circumstances, and an air conditioner failure diagnosis apparatus capable of quantitatively evaluating the degree of deterioration of a failure factor in an air conditioner based on the performance of the air conditioner. The purpose is to obtain.

In order to achieve the above object, an air conditioner failure diagnosis apparatus according to the present invention performs diagnosis related to air conditioner failure diagnosis from data indicating the state of an air conditioner and data relating to control of the air conditioner. The diagnostic processing device includes a processing device, and the diagnostic processing device performs a process of calculating a degree of divergence of the air conditioning characteristics from the air conditioning characteristics with respect to at least one of the air conditioning characteristics, which is an index indicating the performance of the air conditioner. And a deterioration influence calculation unit that performs failure diagnosis processing for diagnosing the degree of deterioration due to the failure factor for a plurality of predetermined failure factors that cause the failure of the air conditioner based on the degree of deviation Is.

According to the present invention, the degree of deterioration leading to a failure can be quantitatively expressed by a common term called air conditioning characteristics for a plurality of failure factors that cause the failure of the air conditioner. It is possible to easily determine the repair timing, replacement, and repair priority for parts.

It is a figure which shows the structural example of the air conditioner fault diagnostic system 000 centering on the air conditioner fault diagnostic apparatus 400 in Embodiment 1 of this invention. It is a figure which shows the example of an output of the failure diagnosis result of each failure factor influence comparison in Embodiment 1 of this invention. It is a figure which shows the example of an output which concerns on the secular change of the failure factor in Embodiment 1 of this invention. It is a figure which shows the structural example of the air conditioner fault diagnostic system 000 centering on the air conditioner fault diagnostic apparatus 400 in Embodiment 2 of this invention. It is a figure which shows the example of an output of the failure diagnosis result of each failure factor influence comparison in Embodiment 3 of this invention. It is a figure which shows the example of an output which concerns on the secular change of the failure factor in Embodiment 3 of this invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Here, in each of the drawings to be referred to, elements such as common devices are denoted by the same reference numerals. Further, the present invention is not limited to the following embodiments, and various modifications can be made without departing from the spirit of the present invention.

Embodiment 1 FIG.
<Configuration of Air Conditioner Failure Diagnosis System 000>
FIG. 1 is a diagram illustrating a configuration example of an air conditioner failure diagnosis system 000 centering on an air conditioner failure diagnosis apparatus 400 according to Embodiment 1 of the present invention. In FIG. 1, an air conditioner failure diagnosis system 000 includes an air conditioner 100, an external terminal device 200, an external cloud device 300, and an air conditioner failure diagnosis device 400.

External terminal device 200 has at least a device that realizes a display function, a notification function, and a communication function. For example, a smart phone, a tablet terminal, etc. become the external terminal device 200.

Further, the external cloud device 300 is an external processing storage device outside the air conditioner 100 provided by a cloud service, for example. The external cloud device 300 is communicatively connected to the external terminal device 200 and the air conditioner failure diagnosis device 400 via, for example, an electric communication line (network) 500. The external cloud device 300 is a database that stores and accumulates various types of data such as failure diagnosis result data obtained by processing by the air conditioner failure diagnosis device 400. Also, arithmetic processing and the like are performed based on the stored data. The external cloud device 300 includes a cloud communication device 320, a machine learning device 310, and a cloud storage device 330.

The cloud communication device 320 is an interface when devices in the external cloud device 300 such as the machine learning device 310 and the cloud storage device 330 communicate with devices outside the cloud communication device 320 via the electric communication line 500, for example. Then, signal conversion is performed. The machine learning device 310 is a device that performs processing by machine learning on input data. Machine learning is a process in which a functional unit improves its performance by acquiring new knowledge and skills, or by reconstructing existing knowledge and skills. Here, the coefficient used for the arithmetic processing when the air conditioner failure diagnosis apparatus 400 performs failure diagnosis is calculated from the data of the result of the failure diagnosis performed in the air conditioner failure diagnosis apparatus 400. The cloud storage device 330 stores, as data, a coefficient related to the calculation of the machine learning device 310, a result of failure diagnosis from the air conditioner failure diagnosis device 400, and the like.

The air conditioner 100 is an apparatus that performs air conditioning of a target space by connecting a device such as a compressor, a heat exchanger, an expansion valve, and the like to form a refrigerant circuit and circulating the refrigerant enclosed in the refrigerant circuit. It is. Here, the air conditioner 100 includes the air conditioning control device 110, the sensors 130a to 130n, and the actuators 120a to 120n as devices and devices related to control.

Actuators 120a to 120n are drive devices such as a compressor, an electronic expansion valve, and a wind direction control device. The actuators 120a to 120n are devices that are driven and controlled based on control-related data sent from the air conditioning controller 110. The sensors 130a to 130n detect physical quantities such as the temperature distribution of the target space such as the temperature and pressure of the refrigerant in the refrigerant circuit. The detected temperature, pressure, and the like are data indicating the state of the air conditioner 100. Then, a signal including data related to detection is output. Here, the sensors 130a to 130n are devices such as a temperature detection device, a pressure detection device, and an infrared camera, for example. The air conditioning control device 110 is a device that controls the air conditioner 100. Based on the data included in the signals sent from the sensors 130a to 130n, the air conditioning control apparatus 110 sends a signal including data related to the control to the actuators 120a to 120n, for example, to control driving. Here, the sensors 130a to 130n and the actuators 120a to 120n will be described as the sensor 130 and the actuator 120, respectively, unless otherwise specified.

The air conditioner failure diagnosis device 400 performs processing based on various data included in signals sent from the air conditioner control device 110, the sensor 130, etc. of the air conditioner 100, and diagnoses the failure of the air conditioner 100 to be diagnosed. And so on. In Embodiment 1, the air conditioner failure diagnosis apparatus 400 is installed in the air conditioner 100 to be diagnosed.

The air conditioner failure diagnosis device 400 includes a diagnosis processing device 410, an operation device 420, a display device 430, a communication device 440, and a notification device 450. The operation device 420 sends a signal including an instruction input by an operator such as a user or a maintenance company to the diagnosis processing device 410. The display device 430 performs display based on a display signal sent from the diagnostic processing device 410, for example. The notification device 450 is a device that notifies a user or the like based on a signal related to notification sent from the diagnostic processing device 410, for example. As the notification device, for example, there is a light-emitting device that performs visual notification by light emission or blinking. In addition, there is a sounding device that makes an audible notification by generating a warning sound. The display device 430 may be a notification device.

The communication device 440 serves as an interface when the diagnostic processing device 410 communicates with devices outside the air conditioner failure diagnosis device 400 such as the external terminal device 200 and the external cloud device 300, and performs signal conversion and the like. In Embodiment 1, the communication device 440 includes a terminal communication unit 441 and a line communication unit 442. The terminal communication unit 441 performs communication with the external terminal device 200. In addition, the line communication unit 442 performs communication with the external cloud device 300 via the electric communication line 500.

Here, when the communication device 440 communicates with the external cloud device 300, the communication device 440 may perform communication via the external terminal device 200. For example, the communication device 440 communicates with the external terminal device 200 using a short-range communication method such as Wi-Fi or Bluetooth (registered trademark). The external terminal device 200 serves as a relay device that transmits and receives signals on the telecommunications line 500 and communicates with the external cloud device 300 connected to the telecommunications line 500. In this case, the line communication unit 442 may be omitted.

As described above, the air conditioner failure diagnosis apparatus 400 is installed in the air conditioner 100. Therefore, for example, the operation device, the display device, the communication device, and the notification device included in the remote controller installed in the air conditioner 100 may be the operation device 420, the display device 430, the communication device 440, and the notification device 450. .

The diagnosis processing apparatus 410 includes a divergence degree calculation unit 415, a deterioration influence calculation unit 411, a calculation coefficient storage unit 412, a diagnosis result storage processing unit 413, and a deterioration progress prediction unit 414. The divergence degree calculation unit 415 and the deterioration influence calculation unit 411 include, for example, data related to the control of the air conditioner 100 included in the signal sent from the air conditioning control device 110 and the signals sent from the sensors 130a to 130n. Various detection data indicating the state of the air conditioner 100 is input. The divergence degree calculation unit 415 performs processing for calculating the degree of divergence of the air conditioning characteristics from the reference of the air conditioning characteristics. The deterioration influence calculation unit 411 further calculates the influence degree of failure, deterioration, etc. due to the failure factor on the air conditioning characteristics from the data including the divergence degree for each failure factor.

Here, the air conditioning characteristics are the performance (specifications) of the air conditioner 100. In the first embodiment, COP (coefficient of performance), which is one of the indexes expressing energy consumption efficiency, is set as the air conditioning characteristic. The failure factor is an element that causes the air conditioner 100 to fail. Further, the failure factor becomes a factor that deteriorates the air conditioning characteristics. The failure factors include, for example, insufficient refrigerant amount in the refrigerant circuit in the air conditioner 100, abnormal operation of the blower fan, fouling or corrosion of the heat exchanger, abnormal operation of the compressor, stuck electronic expansion valve, filter clogging, etc. There is. For this reason, the deterioration degree in each failure factor can be evaluated by the common term of influence on air conditioning characteristics.

The calculation coefficient storage unit 412 stores, as data, one or a plurality of coefficients used when the deterioration influence calculation unit 411 performs calculation in the processing. The calculation coefficient storage unit 412 stores data of initial coefficients that are determined in advance at the time of product shipment, for example. The initial coefficient can be used as it is, but the coefficient data may be rewritten and updated. For example, the external cloud device 300 performs processing by machine learning to determine the coefficient using various data relating to the operation of the air conditioner 100 at normal time and abnormal time as input. Then, the coefficient data transmitted from the external cloud device 300 is rewritten and stored in the calculation coefficient storage unit 412 via the communication device 440.

The diagnosis result storage processing unit 413 stores failure diagnosis result data obtained by the calculation processing by the deterioration influence calculation unit 411 for at least the past certain period. In addition, a display signal for displaying the deterioration of the deterioration factor due to the failure factor in time series with the failure diagnosis result data is sent. The degradation progress prediction unit 414 performs a process of predicting the transition of the future air-conditioning characteristics and the degree of influence of each failure factor based on the data stored in the diagnosis result storage processing unit 413.

Here, the diagnosis processing device 410 is constituted by, for example, a microcomputer having a control arithmetic processing device such as a CPU (Central Processing Unit). Further, it has a storage device (not shown), and has data in which a processing procedure related to control or the like is a program. Then, based on the program data, the control arithmetic processing device executes the processes of the deterioration influence calculation unit 411 and the deterioration progress prediction unit 414 to realize control. In addition, each unit may be configured by a different dedicated device (hardware).

In particular, it is assumed that a neural network is used for the calculation in the divergence degree calculation unit 415 and the deterioration influence calculation unit 411 in the first embodiment. A neural network is, for example, a processing mechanism that is configured by modeling and networking nerve cells (neurons) that make up the brain. For this reason, in the divergence degree calculation unit 415 and the degradation influence calculation unit 411 of the first embodiment, a plurality of neurons are conceptually connected to the network, and based on data sent from the air conditioning control device 110 and the sensors 130a to 130n. Assume that final calculation result data is output while sending and receiving calculation results between neurons. For example, the control data from the air conditioning control device 110 and various detection data from the sensors 130a to 130n can be used for a large amount of data by using a neural network even when about 20 data are input. The accuracy of calculation can be improved.

<Operation of fault diagnosis>
Next, the operation | movement which concerns on the failure diagnosis which the air conditioner failure diagnosis apparatus 400 performs is demonstrated. The failure diagnosis processing is mainly performed by the deterioration influence calculation unit 411 of the diagnosis processing device 410. As described above, the deterioration influence calculation unit 411 determines, based on the data sent from the air conditioning controller 110 and the sensors 130a to 130n, the degree of influence that the failure factor deterioration has on the air conditioning characteristics for each failure factor. Calculate. As the calculation contents, for example, the deterioration influence calculation unit 411 calculates how far the COP deviates from the reference. For example, it is based on the rated value described in the product catalog. This is the influence of the entire air conditioner 100 due to the deterioration of the failure factor. The deterioration influence calculation unit 411 further calculates how much each failure factor contributes to the overall influence degree, and outputs the influence degree of each failure factor as a failure diagnosis result.

FIG. 2 is a diagram showing an output example of a failure diagnosis result of each failure factor influence comparison in the first embodiment of the present invention. FIG. 2 shows a case where the remote controller of the air conditioner 100 displays on the display device 430. The deterioration influence calculation unit 411 transmits a display signal related to the failure diagnosis result to the display device 430 to display it. Therefore, each failure factor can be evaluated by the degree of influence on a common air conditioning characteristic called COP. Therefore, as shown on the right half side of the screen shown in FIG. 2, the degree of deterioration of each failure factor can be displayed as a numerical value called the degree of influence on COP. Further, as displayed on the left half side of the screen shown in FIG. 2, the degree of deterioration of each failure factor can be associated with each other and expressed as, for example, a radar chart. In the radar chart of FIG. 2, the point of the failure factor having the greatest influence is located at the top of the outermost shell, and the points of the other failure factors are relative to the influence of the failure factor having the greatest influence. The position is determined. In FIG. 2, it can be visually understood that the decrease in COP of the air conditioner 100 is most affected by deterioration due to filter clogging or the like. Here, not only the evaluation result is displayed on the display device 430 but also a signal including the result data may be sent from the communication device 440 and displayed on the display device of the external terminal device 200.

As described above, the diagnosis result storage processing unit 413 of the diagnosis processing apparatus 410 stores data obtained as a result of the failure diagnosis processing performed by the past deterioration influence calculation unit 411. As described above, the deterioration progress prediction unit 414 performs the deterioration prediction process in the device related to the failure factor based on the result data stored in the diagnosis result storage processing unit 413. The content of the prediction process is not particularly limited. For example, for a failure factor having a theoretical formula related to prediction, the result data may be applied to the theoretical formula, and a predicted value may be calculated by performing an operation. Further, a predicted value or the like may be calculated by machine learning or the like.

FIG. 3 is a diagram showing an output example related to the secular change of the failure factor in the first embodiment of the present invention. FIG. 3 shows a case where the remote controller of the air conditioner 100 displays on the display device 430. The deterioration progress prediction unit 414 transmits a display signal related to the prediction process to the display device 430 together with the past calculation result data stored in the diagnosis result storage processing unit 413. As shown in FIG. 3, the change over time in the degree of influence of COP due to failure factors and the progress of deterioration in the future are visually displayed. Here, not only the display device 430 but also the signal transmitted from the communication device 440 may be displayed on the display device of the external terminal device 200. As described above, a user, a maintenance contractor, or the like can visually grasp the progress of deterioration of each failure factor. And it becomes easy to determine the timing of maintenance, part replacement, and the like.

The diagnostic processing conditions and result data stored in the diagnostic result storage processing unit 413 are transmitted to the external cloud device 300 via the communication device 440 and stored therein, for example, at regular intervals. Based on these data, the machine learning device 310 of the external cloud device 300 performs machine learning processing to calculate the coefficient, whereby the coefficient necessary for the calculation of the deterioration influence calculation unit 411 can be improved.

If the deterioration influence calculation unit 411 determines that the degree of deterioration of one or more failure factors exceeds a predetermined deterioration value based on the failure diagnosis result, the deterioration influence calculation unit 411 sends a signal related to notification to the notification device 450. Let me know. Here, a signal indicating that an abnormality has occurred in the external terminal device 200 is sent via the communication device 440, and the display device of the external terminal device 200 notifies that there is an abnormality in the air conditioner 100. You may do it. As for the notification, there is a visual notification by light emission or blinking in the display device 430 and the external terminal device 200 as described above. In addition, there is an audible notification that generates a warning sound from the sound generation device.

In addition, for example, a signal indicating that an abnormality has occurred in the air conditioner 100 may be sent to a maintenance service company that maintains the air conditioner 100 via the communication device 440 so as to notify the maintenance service company. . Here, the notification to the maintenance service company may be notified by sending a signal from the communication device 440 to the maintenance service company via the external terminal device 200.

<Diagnosis execution timing>
The failure diagnosis process performed by the air conditioner failure diagnosis apparatus 400 is executed based on a diagnosis execution request signal input via the operation device 420 by a user, a maintenance company, or the like, for example. In addition to the diagnosis execution request, the failure diagnosis process may be executed periodically. By performing the failure diagnosis process periodically, it can be expected that the function of the air conditioner 100 is maintained and the effect on maintenance can be expected.

Further, there is a possibility of abnormality, for example, when it is determined that the temperature of the refrigerant sealed in the refrigerant circuit of the air conditioner 100 exceeds a predetermined temperature value based on the data detected by the sensors 130a to 130n. At some time, a failure diagnosis process may be executed. Thereby, when the air conditioner 100 confirms an abnormality, a failure factor that causes the abnormality can be analyzed. Further, when determining whether or not to execute the failure diagnosis process, it is not only determined based on the data related to the detection of one sensor 130 but also determined by combining the data related to the detection of a plurality of sensors 130. Also good. Here, the air-conditioning control device 110 may determine whether to execute the failure diagnosis process based on the detection values of the sensors 130a to 130n.

Here, in the description of the first embodiment described above, COP is used as an air conditioner characteristic influenced by a failure factor. COP is one index expressing energy consumption efficiency, but in the present invention, it is not limited to COP. For example, another energy consumption efficiency such as APF (annual energy consumption efficiency) may be used as the air conditioner characteristic.

Embodiment 2. FIG.
<Configuration of Air Conditioner Failure Diagnosis System 000>
FIG. 4 is a diagram illustrating a configuration example of an air conditioner failure diagnosis system 000 centering on the air conditioner failure diagnosis apparatus 400 according to Embodiment 2 of the present invention. In FIG. 4, the same reference numerals as those in FIG. 1 perform the same operations as those in the first embodiment.

In the air conditioner failure diagnosis system 000 of the first embodiment, the air conditioner failure diagnosis apparatus 400 is installed in the air conditioner 100. In the air conditioner failure diagnosis system 000 of the second embodiment, the air conditioner failure diagnosis device 400 is installed in the external cloud device 300. Here, in the second embodiment, only the diagnosis processing device 410 of the air conditioner failure diagnosis device 400 is installed in the external cloud device 300. Then, the operation device, the display device, the communication device, and the notification device installed in the air conditioner 100 operate as the operation device 420, the display device 430, the communication device 440, and the notification device 450, respectively.

Therefore, in the first embodiment, the signal including the instruction from the operation device 420, the control data from the air conditioning control device 110, and the detection data from the sensors 130a to 130n, which are directly input to the diagnosis processing device 410. Are input via the communication device 440 in the air conditioner 100 and the cloud communication device 320 of the external cloud device 300. Further, the display signal output from the diagnostic processing device 410 is sent to the display device 430 in the air conditioner 100 via the cloud communication device 320 and the communication device 440.

The operation of failure diagnosis of each device in the air conditioner failure diagnosis system 000, the diagnosis execution timing of failure diagnosis processing, and the like are the same as described in the first embodiment.

As described above, according to the second embodiment, since the air conditioner failure diagnosis apparatus 400 is installed in the external cloud apparatus 300, in the air conditioner 100, the burden on the failure determination process is reduced. Can do.

Embodiment 3 FIG.
In the first embodiment described above, the processing and operation in the air conditioner failure diagnosis apparatus 400 when the air conditioning characteristic is energy consumption efficiency have been described. In the third embodiment, processing and operation in the air conditioner failure diagnosis apparatus 400 when the air conditioning characteristic is the magnitude of the air conditioning load will be described. Here, the diagnosis processing device 410 in the air conditioner failure diagnosis device 400 according to the third embodiment performs a failure determination process based on the maximum capacity as an index expressing the magnitude of the air conditioning load. Here, the configuration of the system will be described as being the same as that of the air conditioner failure diagnosis system 000 of the first embodiment.

<Operation of fault diagnosis>
The operation of failure diagnosis of each device in the air conditioner failure diagnosis system 000 is basically the same as that described in the first embodiment. In Embodiment 3, instead of COP, the maximum capacity is the air conditioning characteristic.

In the third embodiment, the deterioration influence calculation unit 411 of the diagnostic processing device 410 is based on the data sent from the air conditioning control device 110 and the sensors 130a to 130n to what extent the maximum capacity deviates from the reference. Is calculated. The standard for the maximum capacity in the third embodiment is, for example, a rated value described in a catalog or the like. This is the influence of the entire air conditioner 100 due to the deterioration of the failure factor. The deterioration influence calculation unit 411 further calculates how much each failure factor contributes to the overall influence degree, and outputs the influence degree of each failure factor as a failure diagnosis result.

FIG. 5 is a diagram showing an output example of a failure diagnosis result of each failure factor influence comparison in the third embodiment of the present invention. FIG. 5 shows a case where the remote controller of the air conditioner 100 displays on the display device 430. The deterioration influence calculation unit 411 transmits a display signal related to the failure diagnosis result to the display device 430 to display it. Therefore, each failure factor can be evaluated based on the degree of influence on the common air-conditioning characteristic of maximum capacity. For this reason, as shown in the right half side of the screen shown in FIG. 5, the degree of deterioration of each failure factor can be displayed as a numerical value called the degree of influence on the maximum capacity. Further, as displayed on the left half side of the screen shown in FIG. 5, the degree of deterioration of each failure factor can be associated with other failure factors, for example, expressed as a radar chart. Here, not only the evaluation result is displayed on the display device 430 but also a signal including the result data may be sent from the communication device 440 and displayed on the display device of the external terminal device 200.

FIG. 6 is a diagram showing an output example related to the secular change of the failure factor in the third embodiment of the present invention. FIG. 6 shows a case where the remote controller of the air conditioner 100 displays on the display device 430. The deterioration progress prediction unit 414 transmits a display signal related to the prediction process to the display device 430 together with the past calculation result data stored in the diagnosis result storage processing unit 413. As shown in FIG. 3, the influence of the failure factor on the maximum capacity over time and the progress of deterioration in the future are visually displayed. Here, not only the display device 430 but also the signal transmitted from the communication device 440 may be displayed on the display device of the external terminal device 200.

<Diagnosis execution timing>
The failure diagnosis process performed by the air conditioner failure diagnosis apparatus 400 may be performed in the case of a diagnosis execution request, a periodic diagnosis, an abnormal state, etc., as described in the first embodiment.

Here, the maximum capacity of the air conditioner 100 is one index that expresses the air conditioner characteristic (the size of the air conditioner load that can be processed by the air conditioner 100), which is an air conditioner characteristic. Not exclusively. For example, the failure determination process is performed using the air conditioning capability of the other air conditioner 100 such as the air conditioning capability when the frequency of the compressor included in the air conditioner 100 is constant as the air conditioner characteristics. It may be.

Embodiment 4 FIG.
In the first to third embodiments described above, the energy consumption efficiency and the air conditioning capability of the air conditioner 100 are used as the air conditioner characteristics affected by the failure factor. However, the present invention is not limited to this, For example, the power consumption of the air conditioner 100, the magnitude of noise, and the like may be used as the air conditioner characteristics.

In addition, the air conditioner failure diagnosis apparatus 400 may perform failure determination processing for a plurality of air conditioner characteristics as well as failure determination processing for one air conditioner characteristic.

000 air conditioner failure diagnosis system, 100 air conditioner, 110 air condition control device, 120, 120a-120n actuator, 130, 130a-130n sensor, 200 external terminal device, 300 external cloud device, 310 machine learning device, 320 cloud Communication device, 330 Cloud storage device, 400 Air conditioner failure diagnosis device, 410 Diagnosis processing device, 411 Deterioration influence calculation unit, 412 Operation coefficient storage unit, 413 Diagnosis result storage processing unit, 414 Deterioration progress prediction unit, 415 Deviation degree calculation Unit, 420 operation device, 430 display device, 440 communication device, 441 terminal communication unit, 442 line communication unit, 450 notification device, 500 electric communication line.

Claims

From the data indicating the state of the air conditioner and the data relating to the control of the air conditioner, a diagnosis processing device that performs processing related to the failure diagnosis of the air conditioner,
The diagnostic processing device comprises:
A divergence degree calculation unit that performs a process of calculating a divergence degree from a reference of the air conditioning characteristics for at least one air conditioning characteristic of an air conditioning characteristic that is an index indicating the performance of the air conditioner;
An air conditioner having a deterioration influence calculation unit that performs a failure diagnosis process for diagnosing the degree of deterioration due to the failure factor for a plurality of predetermined failure factors that cause a failure of the air conditioner based on the degree of deviation. Machine fault diagnosis device.
The air conditioner failure diagnosis apparatus according to claim 1, wherein the air conditioning characteristic is energy consumption efficiency.
The air conditioner failure diagnosis apparatus according to claim 1, wherein the air conditioning characteristic is a size of an air conditioning load.
The air conditioner failure diagnosis apparatus according to any one of claims 1 to 3, wherein a result processed by the diagnosis processing apparatus is displayed on a display device.
A diagnosis result storage processing unit is further provided that stores data related to the result of the failure diagnosis processing for at least a predetermined period, and causes the display device to display a secular change in the degree of deterioration due to the failure factor based on the stored data. 4. The air conditioner failure diagnosis device according to 4.
Based on the data stored in the diagnostic result storage processing unit, further comprising a deterioration progress prediction unit for predicting the transition of the degree of deterioration due to the failure factor,
The air conditioner failure diagnosis apparatus according to claim 5, wherein the deterioration progress prediction unit causes the display device to display a result of the prediction process.
The air conditioner failure diagnosis apparatus according to any one of claims 1 to 6, wherein processing of the divergence degree calculation unit and the deterioration influence calculation unit is performed using a neural network.
The air conditioner failure according to claim 7, wherein a coefficient used for calculation when the divergence degree calculation unit and the deterioration influence calculation unit perform processing is derived by machine learning based on a result of the failure diagnosis processing. Diagnostic device.
A communication device having a terminal communication unit for communicating with the external terminal device;
The air according to any one of claims 1 to 8, wherein the diagnostic processing device causes the communication device to transmit a signal including data relating to a result of the failure diagnostic processing to the external terminal device. Harmonic machine fault diagnosis device.
A communication device having a line communication unit for communicating with the external processing storage device;
9. The diagnosis processing device according to claim 1, wherein a signal including data relating to conditions and results of the failure diagnosis processing is transmitted to the communication device and transmitted to the external processing storage device for storage. The air conditioner failure diagnosis device according to one item.
A communication device that communicates with at least one of the air conditioner and the external terminal device;
The diagnostic processing device is installed outside the air conditioner,
The air conditioner failure diagnosis device according to any one of claims 1 to 9, wherein a result processed by the diagnosis processing device is sent to at least one of a display device of the air conditioner and the external terminal device. .
The diagnostic processing device includes:
The air conditioner failure diagnosis apparatus according to claim 8, wherein the coefficient is updated when the coefficient is input from the outside.
10. The air conditioner failure diagnosis device according to claim 9, wherein the diagnosis processing device communicates with an external processing storage device connected to the external terminal device via the terminal communication unit.
Data related to the state of the air conditioner
The temperature detection device that detects the temperature of the refrigerant that the air conditioner has, the pressure detection device that detects the pressure of the refrigerant, and data related to detection by at least one of the infrared cameras. The air conditioner failure diagnosis apparatus according to any one of the above.
15. The air conditioner failure diagnosis apparatus according to claim 1, wherein the divergence degree calculation unit and the deterioration influence calculation unit execute a process when an instruction is input.
The air conditioner failure diagnosis apparatus according to any one of claims 1 to 15, wherein the divergence degree calculation unit and the deterioration influence calculation unit execute processing every predetermined period.
16. The method according to claim 1, wherein the divergence degree calculation unit and the deterioration influence calculation unit execute processing based on a comparison between data relating to the state of the air conditioner and a predetermined value. The air conditioner failure diagnosis device according to Item.
Further comprising a notification device for performing notification based on a signal related to notification;
The deterioration influence calculation unit, when determining that the degree of deterioration due to a plurality of failure factors exceeds a predetermined deterioration value determined for each failure factor, sends a signal related to the notification to the notification device. The air conditioner failure diagnosis apparatus according to any one of claims 1 to 17.
When the deterioration influence calculation unit determines that the degree of deterioration due to the plurality of failure factors exceeds a predetermined deterioration value determined for each failure factor, a maintenance service company indicates that the air conditioner has an abnormality. The air conditioner failure diagnosis apparatus according to any one of claims 1 to 18, which reports to the air conditioner.