Remote monitoring device and remote monitoring method

Abstract

For refrigeration and air conditioning equipment not connected to a remote monitoring system, the system should be able to diagnose malfunctions more accurately than on-site inspections by technicians. [Solution] This disclosure provides a remote monitoring device 10 for refrigeration and air conditioning equipment comprising a control unit 11, wherein the control unit 11 performs a fault diagnosis of the monitored refrigeration and air conditioning equipment 20 based on health indicator values ​​of the monitored refrigeration and air conditioning equipment 20 that is continuously connected via a network N and a learned model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment 20, and performs a fault diagnosis of the unmonitored refrigeration and air conditioning equipment 30 based on health indicator values ​​of the unmonitored refrigeration and air conditioning equipment 30 that is temporarily connected and the learned model for performing fault diagnosis of the unmonitored refrigeration and air conditioning equipment 30.

Description

Technical Field

[0001] The present disclosure relates to a remote monitoring device and a remote monitoring method.

Background Art

[0002] A system is widespread in which a refrigeration and air conditioning device is connected to a communication line and operation data during operation is transmitted to a server installed at a location remote from the installation location of the refrigeration and air conditioning device, and the operation state of the refrigeration and air conditioning device is remotely monitored based on the received operation data. In such a remote monitoring system, various services such as a service for detecting component failures and refrigerant leaks of the refrigeration and air conditioning device are provided.

[0003] Patent Document 1 discloses a technique for acquiring operation data of a refrigeration and air conditioning device on a cloud server remote from the refrigeration and air conditioning device, inferring a refrigerant amount index value from the operation data, and comparing the inferred refrigerant amount estimated value with the refrigerant amount index value in a normal state to determine refrigerant leakage.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In a refrigeration and air conditioning device that has contracted a remote monitoring service, for example, based on past operation data and current data accumulated in a cloud server using the technique described in Patent Document 1, failure diagnosis based on long-term trend changes is constantly performed. However, in a refrigeration and air conditioning device that has not contracted a remote monitoring service, an inspector visits the installation location of the refrigeration and air conditioning device for inspection regularly or in response to a request from a user.

[0006] The inspections of refrigeration and air conditioning equipment conducted on-site by inspectors typically involve very basic items such as measuring operating pressure, current and voltage values, indoor unit outlet temperature, checking for scratches and dirt on various parts of the equipment, and checking for abnormalities in operating noise and vibration levels. With such limited data, accurate fault diagnosis at the stage of minor malfunctions is difficult. Therefore, in recent years, inspectors have been connecting their laptops to the refrigeration and air conditioning equipment, acquiring short-term operating data on the laptops during inspections, and using that data to diagnose malfunctions and determine refrigerant leaks.

[0007] Compared to the basic inspections described above, this method acquires more data items and information, but it has several drawbacks. For example, it cannot utilize past operating data, meaning that trends from past operations to the time of inspection cannot be considered. Furthermore, it cannot compensate for the influence of climate and operating conditions on the behavior of operating data during inspection, and abnormal conditions may not be reproducible during inspection due to differences in climate and operating conditions compared to when the failure occurred. Therefore, it is difficult to perform fault diagnosis at the same level as that provided by remote monitoring systems.

[0008] This disclosure provides a technology that enables more accurate fault diagnosis of refrigeration and air conditioning equipment that is not connected to a remote monitoring system by temporarily connecting it to a remote monitoring system. [Means for solving the problem]

[0009] The first aspect of this disclosure is, A remote monitoring device for refrigeration and air conditioning equipment, which includes a control unit, The control unit, Based on health indicator values ​​of the monitored refrigeration and air conditioning equipment, which are continuously connected via a network, and a trained model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment, fault diagnosis of the monitored refrigeration and air conditioning equipment is performed. Based on health indicator values ​​from temporarily connected unmonitored refrigeration and air conditioning equipment and the learned model used to diagnose the failure of said unmonitored refrigeration and air conditioning equipment, a failure diagnosis of said unmonitored refrigeration and air conditioning equipment is performed.

[0010] A second aspect of this disclosure is a remote monitoring device as described in the first aspect, The aforementioned health indicator value represents a deviation from the normal state of the refrigeration and air conditioning equipment, and is calculated based on operating data obtained from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment.

[0011] A third aspect of this disclosure is a remote monitoring device as described in the first aspect, The sampling interval when acquiring the operation data from the monitored refrigeration and air conditioning equipment is: This interval differs from the sampling interval used when acquiring the operating data from the aforementioned non-monitored refrigeration and air conditioning equipment.

[0012] A fourth aspect of this disclosure is a remote monitoring device as described in the first aspect, The sampling interval for the health index values ​​calculated based on the operating data obtained from the monitored refrigeration and air conditioning equipment is: The sampling interval for the health index values ​​calculated based on the operating data obtained from the aforementioned non-monitored refrigeration and air conditioning equipment is different.

[0013] A fifth aspect of this disclosure is a remote monitoring device as described in the first aspect, The control unit, Based on the averaged data of the aforementioned health indicator values, the leakage of refrigerant from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment is determined. The number of health indicator data used in the averaging process for the health indicator values ​​of the monitored refrigeration and air conditioning equipment is different from the number of health indicator data used in the averaging process for the health indicator values ​​of the non-monitored refrigeration and air conditioning equipment.

[0014] A sixth aspect of this disclosure is a remote monitoring device as described in the first aspect, The control unit, Based on the threshold values ​​of the aforementioned health indicators, a determination is made regarding refrigerant leakage. The threshold value for the health indicator of the monitored refrigeration and air conditioning equipment is different from the threshold value for the health indicator of the non-monitored refrigeration and air conditioning equipment.

[0015] A seventh aspect of the present disclosure is the remote monitoring device described in the first aspect, wherein the operating conditions of the non-monitored refrigeration and air conditioning equipment when acquiring the operation data are different from the operating conditions during normal operation, the operating conditions for acquiring the operation data include at least one of the number of operating outdoor units of the non-monitored refrigeration and air conditioning equipment, the number of operating indoor units, the set value of the room temperature set by the remote control, the setting of the air volume of the fan, and the operation mode of heating and cooling.

[0016] An eighth aspect of the present disclosure is the remote monitoring device described in the first aspect, wherein the control unit compares the health index value of the non-monitored refrigeration and air conditioning equipment with the health index value of the same or similar models as the non-monitored refrigeration and air conditioning equipment extracted from the past data of the monitored refrigeration and air conditioning equipment stored in advance, and based on this, determines whether there is a refrigerant leak in the non-monitored refrigeration and air conditioning equipment.

[0017] A ninth aspect of the present disclosure is the remote monitoring device described in the first aspect, wherein the control unit stores the operation data and the calculated health index value obtained from the non-monitored refrigeration and air conditioning equipment, and the next time it determines whether there is a refrigerant leak in the non-monitored refrigeration and air conditioning equipment, it determines whether there is a refrigerant leak in the non-monitored refrigeration and air conditioning equipment based on the stored operation data and health index value and the acquired operation data and calculated health index value.

[0018] A tenth aspect of the present disclosure is the remote monitoring device according to any one of the first to ninth aspects, wherein the health index value is an estimated value of the refrigerant amount calculated based on the operation data obtained from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment, or a refrigerant amount index value having a strong correlation with the refrigerant amount. The failure diagnosis performed by the control unit is a determination of the monitored refrigeration and air-conditioning equipment and the amount of refrigerant possessed by the monitored refrigeration and air-conditioning equipment.

[0019] The 11th aspect of the present disclosure is a remote monitoring device for a refrigeration and air-conditioning equipment provided with a control unit, The control unit Based on the health index value of the monitored refrigeration and air-conditioning equipment continuously connected via the network and the learned model for performing failure diagnosis of the monitored refrigeration and air-conditioning equipment, performs failure diagnosis of the monitored refrigeration and air-conditioning equipment, Based on the health index value of the refrigeration and air-conditioning equipment outside the monitoring target that is temporarily connected and a learned model different from the learned model for performing failure diagnosis of the refrigeration and air-conditioning equipment outside the monitoring target, performs failure diagnosis of the refrigeration and air-conditioning equipment outside the monitoring target.

[0020] The 12th aspect of the present disclosure is A remote monitoring method executed by a remote monitoring device, Based on the refrigerant amount index value of the monitored refrigeration and air-conditioning equipment continuously connected via the network and the learned model for determining refrigerant leakage of the monitored refrigeration and air-conditioning equipment, determining the refrigerant leakage of the monitored refrigeration and air-conditioning equipment; Based on the refrigerant amount index value of the refrigeration and air-conditioning equipment outside the monitoring target that is temporarily connected and the learned model for determining refrigerant leakage of the refrigeration and air-conditioning equipment outside the monitoring target, determining the refrigerant leakage of the refrigeration and air-conditioning equipment outside the monitoring target.

[0021] According to the 12th aspect of the present disclosure, by temporarily connecting a refrigeration and air-conditioning equipment not connected to the network to the network, it is possible to more accurately determine refrigerant leakage than when not connected.

Brief Description of the Drawings

[0022] [Figure 1] It is a configuration diagram of a refrigeration and air-conditioning remote monitoring system according to an embodiment of the present disclosure. [Figure 2] It is a configuration diagram of the monitored refrigeration and air-conditioning equipment and the refrigeration and air-conditioning equipment outside the monitoring target according to an embodiment of the present disclosure. [Figure 3] This is a hardware configuration diagram of a remote monitoring device according to one embodiment of the present disclosure. [Figure 4] This figure illustrates a method for determining refrigerant leakage based on a refrigerant quantity index value using a remote monitoring device according to one embodiment of the present disclosure. [Figure 5] This figure illustrates the operating conditions for detecting refrigerant leakage of unmonitored refrigeration and air conditioning equipment, which are set when acquiring operating data from unmonitored refrigeration and air conditioning equipment in a remote monitoring device according to one embodiment of the present disclosure. [Figure 6] This diagram illustrates the relationship between monitored refrigeration and air conditioning equipment, non-monitored refrigeration and air conditioning equipment, a remote monitoring device, and a learning device according to one embodiment of the present disclosure. [Figure 7] This is a functional block diagram of a learning device according to one embodiment of the present disclosure. [Figure 8] This is a functional block diagram illustrating the refrigerant leakage determination process in a remote monitoring device according to one embodiment of the present disclosure. [Figure 9] This is a flowchart of a remote monitoring method according to one embodiment of the present disclosure. [Modes for carrying out the invention]

[0023] The embodiments for carrying out the invention will be described below with reference to the drawings. In each drawing, the same reference numerals are used for identical components, and redundant explanations may be omitted.

[0024] [First Embodiment] <Configuration of Refrigeration and Air Conditioning Remote Monitoring System 1> The configuration of the refrigeration and air conditioning remote monitoring system 1 according to the first embodiment of this disclosure will be described below with reference to Figure 1. Figure 1 is a configuration diagram of the refrigeration and air conditioning remote monitoring system 1 according to one embodiment of this disclosure.

[0025] The refrigeration and air conditioning remote monitoring system 1 comprises a remote monitoring device 10, monitored refrigeration and air conditioning equipment 20, a data communication device 24, non-monitored refrigeration and air conditioning equipment 30, a data communication device 34, and a terminal device 40. The remote monitoring device 10, monitored refrigeration and air conditioning equipment 20, data communication device 24, non-monitored refrigeration and air conditioning equipment 30, data communication device 34, and terminal device 40 are connected to each other via a network N, such as the Internet. The network N is, for example, a wired LAN (Local Area Network) or a wireless LAN, and may include both wired and wireless communication.

[0026] The remote monitoring device 10 can continuously connect the monitored refrigeration and air conditioning equipment 20 to the network N via the data communication device 24 to acquire operating data and monitor its operating status. On the other hand, the remote monitoring device 10 can temporarily connect non-monitored refrigeration and air conditioning equipment 30 to the network N via the data communication device 34 to acquire operating data.

[0027] The data communication device 34 may temporarily use a device installed at the location of the refrigeration and air conditioning equipment 30 that is not subject to monitoring. Alternatively, a device brought by the inspector during maintenance services may be used. The data communication devices 24 and 34 are, for example, a central controller or edge computer that manages multiple refrigeration and air conditioning equipment.

[0028] The monitored refrigeration and air conditioning equipment 20 may be equipment subject to, for example, equipment monitoring services and remote operation services that allow for remote operation of the equipment. The non-monitored refrigeration and air conditioning equipment 30 may be equipment that is not subject to these services and whose operating data is acquired only during, for example, maintenance services. The operating data of the non-monitored refrigeration and air conditioning equipment 30 may be acquired and stored by a terminal device 40 held by an inspector, etc., and then transmitted to the remote monitoring device 10.

[0029] The remote monitoring device 10 includes a control unit 11. The control unit 11 performs fault diagnosis of the monitored refrigeration and air conditioning equipment 20 based on the calculated health index values ​​and a first judgment logic. The control unit 11 also performs fault diagnosis of the non-monitored refrigeration and air conditioning equipment 30 based on the calculated health index values ​​and a second judgment logic. The "first judgment logic" and "second judgment logic" are examples of trained models. The fault detected by the control unit 11 is, for example, refrigerant leakage. In the following explanation, the fault will be described assuming that it is refrigerant leakage. In the following explanation, the functions and operations implemented by the control unit 11 may be described using "remote monitoring device 10" as the subject. The health index values ​​are calculated based on operating data sampled from the monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30. The health index values ​​are estimated values ​​of the calculated refrigerant amount or refrigerant amount index values, which have a strong correlation with the refrigerant amount. The fault diagnosis performed by the control unit 11 involves determining the monitored refrigeration and air conditioning equipment 20 and the amount of refrigerant contained within it. Hereafter, the health indicator value will also be referred to as the "refrigerant amount indicator value."

[0030] The remote monitoring device 10 can remotely monitor and control the operating status of the monitored refrigeration and air conditioning equipment 20 via the network N. The remote monitoring device 10 receives operating data transmitted by the monitored refrigeration and air conditioning equipment 20 via the network N. The remote monitoring device 10 also transmits data to be sent to the monitored refrigeration and air conditioning equipment 20 via the network N. The remote monitoring device 10 may be implemented using two or more devices, or it may be implemented as a cloud computing service.

[0031] The control unit 11 of the remote monitoring device 10 can monitor and control the operating status of the unmonitored refrigeration and air conditioning equipment 30, which is temporarily connected to the network N. The remote monitoring device 10 receives operating data transmitted by the unmonitored refrigeration and air conditioning equipment 30 via the network N. The remote monitoring device 10 also transmits data to be sent to the unmonitored refrigeration and air conditioning equipment 30 via the network N.

[0032] The control unit 11 acquires operating data from the monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30 at predetermined sampling intervals. If a refrigerant leak is detected, the control unit 11 calculates a refrigerant amount index value, which is an index value for the amount of refrigerant, based on the operating data. The predetermined sampling interval may be, for example, 1 hour for the monitored refrigeration and air conditioning equipment 20 and 1 minute for the non-monitored refrigeration and air conditioning equipment 30, but is not limited to these.

[0033] The refrigerant quantity index value is a parameter that has a strong correlation with the amount of refrigerant contained in the refrigeration and air conditioning equipment. For example, it may be a parameter obtained by calculating the relationship between parameters included in operating data such as the degree of subcooling of the refrigeration cycle, the degree of compressor suction superheating, and the degree of compressor discharge superheating. Alternatively, the refrigerant quantity index value may be obtained by directly using specific parameters included in operating data such as the opening of the outdoor unit main expansion valve, the opening of the subcooling heat exchanger expansion valve, and the opening of the indoor heat exchanger expansion valve.

[0034] The second judgment logic used to determine refrigerant leakage in the unmonitored refrigeration and air conditioning equipment 30 differs from the first judgment logic in terms of the sampling interval, number of data points, and threshold values ​​for operating data. Since the connection time between the remote monitoring device 10 and the unmonitored refrigeration and air conditioning equipment 30 is temporary, the time available for acquiring operating data is limited. Therefore, the second judgment logic, as will be explained later using Figures 4 and 5, is a logic that more efficiently utilizes the operating data acquired in a limited short time and the calculated refrigerant amount index value to determine refrigerant leakage.

[0035] The control unit 11 may store the operating data acquired from the monitored refrigeration and air conditioning equipment 20 and the calculated refrigerant quantity index value. The control unit 11 can determine refrigerant leakage based on the refrigerant quantity index value of the unmonitored refrigeration and air conditioning equipment 30 and the refrigerant quantity index value of the same or similar model as the unmonitored refrigeration and air conditioning equipment 20, which is extracted from past data of the monitored refrigeration and air conditioning equipment 20 that has been stored in advance. Therefore, even if the quality of the operating data of the unmonitored refrigeration and air conditioning equipment 30 acquired temporarily is poor due to environmental conditions or load conditions, and the reliability of the calculated refrigerant quantity index value is low, refrigerant leakage can be accurately determined by also referring to the data of the monitored refrigeration and air conditioning equipment 20 of the same or similar model as the unmonitored refrigeration and air conditioning equipment.

[0036] Furthermore, the control unit 11 can determine whether there is a refrigerant leak in the unmonitored refrigeration and air conditioning equipment 30 based on the previously stored past operating data and calculated refrigerant quantity index value of the unmonitored refrigeration and air conditioning equipment 30, as well as the currently acquired operating data and calculated refrigerant quantity index value. Therefore, various diagnoses, such as determining whether there is a refrigerant leak in the unmonitored refrigeration and air conditioning equipment 30, can be performed based on long-term changes in the refrigerant quantity index value.

[0037] The monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30 may have the same configuration or different configurations. In the following description, the monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30 will be described assuming they have the same configuration.

[0038] The monitored refrigeration and air conditioning equipment 20 comprises an indoor unit 21, an outdoor unit 22, and a control unit 23. The indoor unit 21 and the outdoor unit 22 are connected in a communicative manner. The indoor unit 21 is installed, for example, inside a building. The indoor unit 21 may also be equipped with sensors capable of measuring indoor temperature and humidity. The outdoor unit 22 may be equipped with sensors capable of measuring outside temperature.

[0039] The control unit 23 of the monitored refrigeration and air conditioning equipment 20 may determine the operation content based on the indoor and outdoor environment measured by sensors provided in the indoor unit 21 and the outdoor unit 22, the set temperature and set humidity entered by the user via the remote control, the start time of operation of the monitored refrigeration and air conditioning equipment 20, and the operation mode such as cooling operation, heating operation, or dehumidification operation.

[0040] The non-monitored refrigeration and air conditioning equipment 30 comprises an indoor unit 31, an outdoor unit 32, and a control unit 33. The indoor unit 31 and the outdoor unit 32 are connected in a communicative manner. The indoor unit 31 is installed, for example, inside a building. The indoor unit 31 may also be equipped with sensors capable of measuring indoor temperature and humidity. The outdoor unit 32 may be equipped with sensors capable of measuring outside temperature.

[0041] The control unit 33 of the non-monitored refrigeration and air conditioning equipment 30 may determine the operation content based on the indoor and outdoor environment measured by sensors provided in the indoor unit 31 and the outdoor unit 32, the set temperature and set humidity entered by the user via the remote control, the start time of operation of the monitored refrigeration and air conditioning equipment 20, and the operation mode such as cooling operation, heating operation, or dehumidification operation.

[0042] The terminal device 40 is operated by an inspector who performs maintenance on the refrigeration and air conditioning equipment 30 that is not subject to monitoring. The terminal device 40 displays data received from the remote monitoring device 10 or the refrigeration and air conditioning equipment 30 that is not subject to monitoring and notifies the inspector.

[0043] The terminal device 40 is a device such as a smartphone, tablet, or PC (Personal Computer). The terminal device 40 stores various programs, including application programs related to maintenance work on the unmonitored refrigeration and air conditioning equipment 30, and identification information that identifies the unmonitored refrigeration and air conditioning equipment 30 to be operated on.

[0044] The remote monitoring device 10, the monitored refrigeration and air conditioning equipment 20, the non-monitored refrigeration and air conditioning equipment 30, and the terminal device 40 all have programs installed for acquiring operational data during maintenance work. The remote monitoring device 10 can function as a control unit 11 when the program is executed. Similarly, the monitored refrigeration and air conditioning equipment 20 can function as a control unit 23 when the program is executed. Furthermore, the non-monitored refrigeration and air conditioning equipment 30 can function as a control unit 33 when the program is executed.

[0045] Note that the refrigeration and air conditioning remote monitoring system 1 is not limited to the configuration shown in Figure 1. The refrigeration and air conditioning remote monitoring system 1 may include multiple remote monitoring devices 10, monitored refrigeration and air conditioning equipment 20, non-monitored refrigeration and air conditioning equipment 30, and terminal devices 40. The configuration of the refrigeration and air conditioning remote monitoring system 1 shown in Figure 1 can take various forms depending on the application and purpose.

[0046] Figure 2 is a configuration diagram of a monitored refrigeration and air conditioning unit 20 and an unmonitored refrigeration and air conditioning unit 30 according to one embodiment of the present disclosure. The monitored refrigeration and air conditioning unit 20 and the unmonitored refrigeration and air conditioning unit 30 can each have various configurations, but in this embodiment, for the sake of simplicity of explanation, they are assumed to have the same configuration.

[0047] Therefore, in the following explanation, the indoor unit 21 of the monitored refrigeration and air conditioning equipment 20 and the indoor unit 31 of the non-monitored refrigeration and air conditioning equipment 30 will be referred to as "indoor units 21, 31," and the outdoor unit 22 of the monitored refrigeration and air conditioning equipment 20 and the outdoor unit 32 of the non-monitored refrigeration and air conditioning equipment 30 will be referred to as "outdoor units 22, 32." In addition, the control unit 23 of the monitored refrigeration and air conditioning equipment 20 and the control unit 33 of the non-monitored refrigeration and air conditioning equipment 30 will be referred to as "control units 23, 33."

[0048] The monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30 each have outdoor units 22, 32 and one or more indoor units 21, 31. The multiple indoor units 21, 31 may include indoor units 21, 31 with different performance characteristics, indoor units 21, 31 with the same performance characteristics, or indoor units 21, 31 that are currently stopped.

[0049] In the illustrated example, the outdoor heat exchanger 201, the outdoor unit main expansion valve 205, the subcooling heat exchanger 203, the indoor heat exchanger expansion valve 302, the indoor heat exchanger 301, the four-way switching valve 206, the high-pressure receiver 100, and the compressor 202 are connected by refrigerant piping to form the main refrigerant circuit. The four-way switching valve 206 is configured to supply the discharge gas from the compressor 202 to the outdoor heat exchanger 201.

[0050] Furthermore, a subcooled heat exchanger expansion valve 204 is provided in a bypass pipe connected from the piping between the outdoor heat exchanger 201 and the subcooled heat exchanger 203 to the suction side piping of the compressor 202. The subcooled heat exchanger 203 is a heat exchanger that exchanges heat between the refrigerant that has passed through the subcooled heat exchanger expansion valve 204, which is provided in the bypass pipe connected from between the outdoor heat exchanger 201 and the subcooled heat exchanger 203 to the suction side piping of the compressor 202, and the refrigerant in the main refrigerant circuit. Note that the illustrated bypass example is just one example and is not limited to this.

[0051] On the outdoor unit 22,32 side, the outdoor heat exchanger 201, compressor 202, subcooled heat exchanger 203, subcooled heat exchanger expansion valve (bypass circuit) 204, and outdoor unit main expansion valve (main refrigerant circuit) 205 are connected to the piping. The outdoor units 22,32 have various sensors (temperature sensors (e.g., thermistors) (1), (3), (4), (6), (7) and pressure sensors (2), (5), etc.).

[0052] On the indoor units 21 and 31, the indoor heat exchanger 301 and the indoor heat exchanger expansion valve 302 are connected to the piping. The indoor units 21 and 31 are equipped with various sensors (temperature sensors (e.g., thermistors) (8), (9), etc.).

[0053] The high-pressure receiver 100 is a refrigerant container capable of storing excess refrigerant as liquid refrigerant. Excess refrigerant is the surplus of refrigerant that is generated in refrigeration and air conditioning equipment due to changes in the set temperature, etc.

[0054] <Explanation of Terms> Herein, we will explain the terminology used in this disclosure. First, "operational data" refers to any data that may be acquired during the operation of the equipment. For example, operational data for equipment (e.g., refrigeration and air conditioning equipment) is as follows: This relates to the refrigerant state, including the temperature (condenser and evaporator inlet / outlet temperatures, compressor suction temperature, compressor discharge temperature, etc.), pressure (condensation pressure, evaporation pressure), and circulation rate of the refrigerant circulating inside the refrigeration and air conditioning equipment. • Values ​​calculated from refrigerant temperature and pressure data (e.g., condenser outlet supercooling degree, supercooled heat exchanger outlet supercooling degree, compressor suction superheating degree, compressor discharge superheating degree, etc.). • The operating amount and control command values ​​of the actuators that control the state of the refrigerant (opening degree of each expansion valve in the outdoor and indoor units, compressor rotation speed, fan rotation speed, target value of compressor suction superheat, etc.). • Time information regarding the operating status of the equipment (compressor operating time, defrost operating time, etc.). • Environmental conditions of the location where the equipment is operating (outside temperature, room temperature, indoor relative humidity, etc.). • Input energy to the equipment, such as compressor current and fan current. • The refrigeration or air conditioning capacity, which is the output of the equipment. • Flag values ​​indicating the operating mode of the equipment (e.g., cooling operation, heating operation, defrost operation)

[0055] <Configuration of remote monitoring device 10> Figure 3 is a hardware configuration diagram of a remote monitoring device 10 according to one embodiment of the present disclosure. The remote monitoring device 10 includes an input device 51, a display device 52, an external I / F 53, RAM 54, ROM 55, CPU 56, a communication I / F 57, and an HDD 58, each connected by a bus 59. The input device 51 and the display device 52 may be connected in a configuration as needed.

[0056] The input device 51 includes a touch panel, operation keys and buttons, a keyboard and mouse, etc., used by the user to input various signals. The display device 52 consists of a display such as an LCD or organic EL that displays the screen, and a speaker that outputs sound data such as voice and music. The communication I / F 57 is an interface for the remote monitoring device 10 to communicate data via the network N.

[0057] Furthermore, HDD58 is an example of a non-volatile storage device that stores programs and data. The programs and data stored include the OS, which is the basic software that controls the entire remote monitoring device 10, and applications that provide various functions on the OS. Note that the remote monitoring device 10 may use a drive device that uses flash memory as the storage medium instead of HDD58. For example, an SSD could be used as the drive device.

[0058] External I / F 53 is an interface to an external device. An external device could be a recording medium 53a. This allows the remote monitoring device 10 to read from and write to the recording medium 53a via the external I / F 53. The recording medium 53a could be a flexible disk, CD, DVD, SD memory card, USB memory, etc.

[0059] RAM54 is an example of volatile semiconductor memory that temporarily holds programs and data. ROM55 is an example of non-volatile semiconductor memory that can retain programs and data even when the power is turned off. ROM55 stores programs and data such as the BIOS, OS settings, and network settings that are executed when the remote monitoring device 10 is started up.

[0060] The CPU 56 is a computing unit that controls and implements the functions of the entire remote monitoring device 10 by reading programs and data from storage devices such as ROM 55 and HDD 58 onto RAM 54 and executing processing.

[0061] Figure 4 is a diagram illustrating a method by which a remote monitoring device 10 according to one embodiment of the present disclosure determines refrigerant leakage based on a refrigerant quantity index value. In Figure 4, the graph shows time-series data of the refrigerant quantity index value, where (a) shows the case of the monitored refrigeration and air conditioning equipment 20 and (b) shows the case of the non-monitored refrigeration and air conditioning equipment 30. In Figures 4(a) and (b), the vertical axis is the refrigerant quantity index value and the horizontal axis is time.

[0062] In Figure 4(a), t1 and in Figure 4(b), t2 are the sampling intervals for the refrigerant quantity index values, respectively. In Figure 4(a), th1 and in Figure 4(b), th2 are the threshold values ​​for the refrigerant quantity index values ​​used to determine refrigerant leakage in the monitored refrigeration and air conditioning equipment 20 and the unmonitored refrigeration and air conditioning equipment 30, respectively. In Figure 4(a), W1 and in Figure 4(b), W2 are movable windows for calculating the average value of the refrigerant quantity index values ​​used to determine refrigerant leakage, respectively. For example, movable window W1 is large enough to contain 10 data points. While outputting the average value of the 10 data points in the window, the graph moves one data point to the right.

[0063] The refrigerant quantity index value may be calculated using the sampling interval when acquiring operating data, or it may be calculated using data obtained by applying appropriate filtering to the acquired operating data to change the sampling interval. For example, the refrigerant quantity index value may be calculated directly from operating data acquired from refrigeration and air conditioning equipment at a sampling interval of 1 minute. Alternatively, it may be calculated from data obtained by applying appropriate filtering to data acquired at a sampling interval of 1 minute to convert the sampling interval to 1 hour. The filtering process may involve, for example, calculating the average value every 60 minutes for operating data at 1-minute intervals, arranging the data in the order of the average values, and converting it to data at 1-hour intervals.

[0064] As shown in Figure 4(a), the sampling interval for the time-series data of the refrigerant quantity index value of the monitored refrigeration and air conditioning equipment 20 is t1. The remote monitoring device 10 compares the refrigerant quantity index value with a threshold th1, for example, and determines that there is a leak if the refrigerant quantity index value exceeds the threshold th1.

[0065] In the case of a slow leak where refrigerant leakage occurs and operation is impaired more than one month later, usually, t1 is set to about one hour to one day. Even in such a case, the time-series data of the refrigerant amount index value contains some fluctuation components. Therefore, if the refrigerant leakage is determined using the time-series data as it is, there is a risk of misjudgment due to the fluctuation components. Thus, in this example, the time-series data of the refrigerant amount index value is converted into moving average data using a moving window W1 with a data number N = 10, and the fluctuation components are smoothed. By comparing the smoothed time-series data with the threshold value th1 to determine refrigerant leakage, misjudgment is prevented.

[0066] On the other hand, the sampling interval of the time-series data of the refrigerant amount index value of the non-monitored refrigeration and air-conditioning equipment 30 is t2 (<t1). The remote monitoring device 10 temporarily connects to the non-monitored refrigeration and air-conditioning equipment 30. Therefore, in order to obtain the number of data required for accurate determination in a short time, t2 has to be shorter than the sampling interval t1 in the case of the monitored refrigeration and air-conditioning equipment 20. For example, t2 is set to about several seconds to several minutes. In this case, the fluctuation components of the time-series data of the refrigerant amount index value are larger than those of the time-series data of the monitored refrigeration and air-conditioning equipment 20.

[0067] Therefore, the number of data N of the refrigerant amount index value included in the moving window W2 used for determining the refrigerant leakage of the non-monitored refrigeration and air-conditioning equipment 30 shown in Fig. 4(b) may be made larger than the number of data N of the refrigerant amount index value included in the moving window W1 in the case of the monitored refrigeration and air-conditioning equipment 20. As a result, since the smoothing ability of the moving window W2 is enhanced, misjudgment can be prevented even when determining time-series data with large fluctuation components. For example, in the case of Fig. 4(b), the data number N of W2 is set to N = 20.

[0068] Also, as shown in Fig. 4(b) as a measure to prevent misjudgment when determining time-series data with large fluctuation components, the threshold value th2 in the case of the non-monitored refrigeration and air-conditioning equipment 30 may be made larger than the threshold value th1 in the case of the monitored refrigeration and air-conditioning equipment 20.

[0069] In the case of the monitored refrigeration and air conditioning equipment 20 shown in Figure 4(a), for example, if the sampling interval t1 is 1 hour and the number of data points N for the refrigerant amount index value included in the moving window W1 is 10, then the time length of the moving window W1 will be 10 hours. Similarly, in the case of the non-monitored refrigeration and air conditioning equipment 30 shown in Figure 4(b), for example, if the sampling interval t2 is 1 minute and the number of data points N included in the moving window W2 is 20, then the time length of the moving window will be 20 minutes. The sampling interval is not limited to these examples, and various times can be set. Similarly, the number of data points is not limited to these examples, and various numbers can be set.

[0070] The refrigerant quantity index value used by the remote monitoring device 10 to determine refrigerant leakage is not limited to data smoothed using the movable window W. For example, if the fluctuation component of the refrigerant quantity index value calculated from the operating data is sufficiently small, the refrigerant quantity index value may be used directly for determination without using the movable window W.

[0071] Furthermore, when determining refrigerant leakage from refrigeration and air conditioning equipment 30 that is not subject to monitoring, it is not always necessary to change the threshold th1 to th2. For example, if the fluctuation of the time-series data of the refrigerant amount index value can be sufficiently suppressed by increasing the number of data points N within the movable window W2, the threshold th1 may be used as is.

[0072] As explained in Figures 4(a) and 4(b), the refrigerant leakage detection method for the monitored refrigeration and air conditioning equipment 20 and the unmonitored refrigeration and air conditioning equipment 30 uses the same refrigerant quantity index value and detection logic, but adjusts common parameters such as the sampling interval, the number of data points within the moving window, and the detection threshold to appropriate values ​​according to the characteristics of each operating data. In this case, even when the unmonitored refrigeration and air conditioning equipment 30 is temporarily connected to the network N to detect refrigerant leakage, the detection method for the monitored refrigeration and air conditioning equipment 20 can be reused with only parameter adjustments, thus enabling low-cost operation.

[0073] However, the number and types of parameters to be adjusted do not necessarily have to be the same. Here, let's assume there are four types of parameters: A, B, C, and D. In this case, for example, parameters A and B may be selected for adjustment in the monitored refrigeration and air conditioning equipment 20, while parameters B, C, and D may be selected for the non-monitored refrigeration and air conditioning equipment 30.

[0074] Furthermore, the refrigerant quantity index value and the judgment logic do not necessarily have to be the same. For example, the monitored refrigeration and air conditioning equipment 20 may use the degree of subcooling as the refrigerant quantity index value, while the non-monitored refrigeration and air conditioning equipment 30 may use the compressor discharge temperature superheat as the refrigerant quantity index value. In the monitored refrigeration and air conditioning equipment 20, leakage may be determined by comparing the difference between the predicted value of the refrigerant quantity index obtained by a prediction model trained on past operating data and the measured value with a threshold, while in the non-monitored refrigeration and air conditioning equipment 30, leakage may be determined by comparing the measured value of the refrigerant quantity index with a threshold.

[0075] Thus, instead of using the same determination method for monitored refrigeration and air conditioning equipment 20, a different determination method may be used for non-monitored refrigeration and air conditioning equipment 30. In this case, although operating costs will increase, a determination method more suitable for the operating data characteristics of non-monitored refrigeration and air conditioning equipment 30 can be used.

[0076] Figure 5 is a diagram illustrating the operating conditions for detecting refrigerant leaks of unmonitored refrigeration and air conditioning equipment 30, which are set when acquiring operating data from unmonitored refrigeration and air conditioning equipment 30 in a remote monitoring device 10 according to one embodiment of the present disclosure.

[0077] In Figure 5, (a) and (b) are graphs showing the time-series changes in the refrigerant quantity index value calculated based on operating data obtained from the refrigeration and air conditioning equipment 30 that is not subject to monitoring. In Figures 5(a) and (b), the vertical axis represents the refrigerant quantity index value, and the horizontal axis represents time.

[0078] In this case, the non-monitored refrigeration and air conditioning equipment 30 is equipped with four indoor units 31. The user can independently set the operating mode (on, off, cooling, heating, and fan), the room temperature setting during operation, and the fan airflow for each of the four indoor units 31 using a remote control.

[0079] In Figures 5(a) and (b), A, B, and C, indicated on the horizontal axis, represent the operating conditions of the non-monitored refrigeration and air conditioning equipment 30 during that time period. Details of each condition are shown below. • Operating conditions A: Cooling, 1 indoor unit in operation, room temperature set to 28°C, fan airflow low. • Operating conditions B: Cooling, 4 indoor units in operation, room temperature set to 24°C, fan airflow at high. • Operating conditions C: Cooling, 2 indoor units in operation, room temperature set to 25°C, fan speed medium.

[0080] Under operating condition A, only one indoor unit is in operation and the room temperature is set high. As a result, the load ratio relative to the rated capacity of the refrigeration and air conditioning equipment is, for example, 30% or less, close to the lower limit of the capacity control range. Consequently, the compressor 202 occasionally stops and restarts, resulting in an on / off state. Consequently, the refrigerant amount index value is in an unstable state where the transient response does not converge. Such a situation is prone to misjudgment and is unsuitable for refrigerant leak detection. In the case of refrigerant leak detection for the monitored refrigeration and air conditioning equipment 20, even if the monitored refrigeration and air conditioning equipment 20 continues to operate under these conditions, the operating conditions are not changed because it is the operating state intended by the user, and the refrigerant leak must be judged based on data that is unsuitable for judgment.

[0081] However, in determining refrigerant leakage in the monitored refrigeration and air conditioning equipment 20, accumulated historical data can be used, so by extracting only data under the best possible conditions and utilizing data smoothing and long-term trend analysis, it is possible to determine refrigerant leakage with a certain degree of accuracy. However, in the case of refrigeration and air conditioning equipment 30 that is not monitored, only short-term data can be obtained, so it is difficult to determine refrigerant leakage based solely on operating data under such conditions.

[0082] Therefore, when temporarily connecting the non-monitoring refrigeration and air conditioning equipment 30 to the network N to acquire operating data, even if it is normally operated under conditions unfavorable for leak detection, it may be operated under conditions favorable for detection when connecting to the network N to acquire operating data.

[0083] In the example shown in Figure 5(a), the refrigeration and air conditioning equipment 30, which is not subject to monitoring, is normally operated under condition A. When the remote monitoring device 10 temporarily connects to the network N to acquire operating data, the operating condition is changed to B. Under operating condition B, the room temperature is set to 24°C, which is below the comfortable temperature for cooling, and all four indoor units 31 are operated. In this case, during the daytime in summer, the load factor will be 90% or more, resulting in a stable operating state without starting or stopping. The fluctuation of the refrigerant amount index value is also relatively stable. Therefore, the remote monitoring device 10 can accurately determine refrigerant leakage based on the calculated refrigerant amount index value.

[0084] In the example shown in Figure 5(b), there are two types of operating conditions for the remote monitoring device 10 to acquire operating data from the non-monitored refrigeration and air conditioning equipment 30: operating condition B and operating condition C. Under operating condition C, the indoor set temperature is set higher than under operating condition B, and half of the four indoor units 31, or two units, are operated. In this case, the load factor will be around 50%, but a stable operating state can be expected without starting or stopping.

[0085] Under operating condition B, the operating state may become unstable due to the activation of high-pressure protection control under high ambient temperature conditions, and due to starting and stopping caused by a drop in room temperature under low ambient temperature conditions. Operating condition C is a load factor that does not cause starting and stopping, so it can be operated under a wider range of ambient temperature conditions. Depending on the type of fault diagnosed by the remote monitoring device 10, operating condition C may be easier to diagnose. In addition, by diagnosing with operating data from two types of stable conditions, the reliability of the diagnostic results can be expected to improve. Thus, the remote monitoring device 10 can also set multiple operating conditions when acquiring operating data.

[0086] Furthermore, the combination of operating conditions used by the remote monitoring device 10 to acquire operating data from the non-monitored refrigeration and air conditioning equipment 30 is not limited to the cases shown in Figures 5(a) and (b), but can be any combination of operating conditions. Also, the operating conditions are not limited to A to C, but can be set in any combination of conditions.

[0087] <Pre-trained model> In this embodiment, the remote monitoring device 10 may generate a trained model using the learning device 500 and determine whether refrigerant is leaking. More specifically, the learning device 500 extracts operating data, calculated refrigerant quantity index values, and operating conditions acquired from the monitored refrigeration and air conditioning equipment 20 as training data, and performs machine learning in association with the model of the monitored refrigeration and air conditioning equipment 20. Then, as a result of machine learning using the training data, a trained model is generated.

[0088] Figure 6 is a diagram illustrating the relationship between a monitored refrigeration and air conditioning unit 20, an unmonitored refrigeration and air conditioning unit 30, a remote monitoring device 10, and a learning device 500 according to one embodiment of the present disclosure. As shown in <Example 1> in the figure, the remote monitoring device 10 is connected to the monitored refrigeration and air conditioning unit 20 and the unmonitored refrigeration and air conditioning unit 30 via a network N. The learning device 500 may also be implemented on a cloud server located away from the monitored refrigeration and air conditioning unit 20, the unmonitored refrigeration and air conditioning unit 30, and the remote monitoring device 10.

[0089] As shown in <Example 2> in the figure, the remote monitoring device 10 and the learning device 500 may be implemented on a cloud server located away from the monitored refrigeration and air conditioning equipment 20 and the non-monitored refrigeration and air conditioning equipment 30.

[0090] Figure 7 is a functional block diagram of a learning device 500 according to one embodiment of the present disclosure. The learning device 500 may include a teacher data acquisition unit 501, a teacher data storage unit 502, and a learning unit 503. Furthermore, the learning device 500 can function as the teacher data acquisition unit 501 and the learning unit 503 by executing a program.

[0091] The training data acquisition unit 501 acquires training data. The training data acquisition unit 501 stores the acquired training data in the training data storage unit 502. The training data consists of operating data, refrigerant amount index values, and operating conditions of the refrigeration and air conditioning equipment 30 that is not subject to monitoring. The training data storage unit 502 stores the training data.

[0092] The learning unit 503 uses the operating data acquired from the monitored refrigeration and air conditioning equipment 20, the calculated refrigerant quantity index value, and the operating conditions as training data, and performs machine learning by associating them with the model of the monitored refrigeration and air conditioning equipment 20. As a result of machine learning using the training data, a trained model is generated.

[0093] Figure 8 is a functional block diagram illustrating the refrigerant leakage determination process in a remote monitoring device 10 according to one embodiment of the present disclosure.

[0094] The trained model receives operational data acquired from the monitored refrigeration and air conditioning equipment 20, which is constantly being monitored, and outputs a predicted value of the refrigerant quantity index to the remote monitoring device 10. The control unit 11 of the remote monitoring device 10, as a first judgment logic, compares the difference between the measured value of the refrigerant quantity index calculated from the operational data and the predicted value output by the trained model after inputting the operational data with a threshold to determine whether there is a refrigerant leak in the monitored refrigeration and air conditioning equipment 20.

[0095] Furthermore, the control unit 11 of the remote monitoring device 10 acquires operating data from the unmonitored refrigeration and air conditioning equipment 30 that is temporarily connected to the network N. As a second judgment logic, it compares the difference between the measured value of the refrigerant amount index calculated from the acquired operating data and the predicted value of the refrigerant amount index output by inputting the operating data into the trained model with a threshold to determine whether there is a refrigerant leak in the unmonitored refrigeration and air conditioning equipment 30.

[0096] The temporarily acquired operating data of the unmonitored refrigeration and air conditioning equipment 30, the measured and predicted values ​​of the refrigerant quantity index, and the refrigerant leak detection results may be recorded in the remote monitoring device 10 and referred to as auxiliary data when detecting refrigerant leaks in the future. For example, machine learning algorithms such as random forests and support vector machines can be used to create the trained model.

[0097] <Remote monitoring method> Figure 9 is a flowchart of a remote monitoring method according to one embodiment of the present disclosure. The remote monitoring device 10 recognizes whether the device used to determine refrigerant leakage is the refrigeration and air conditioning equipment 20 to be monitored or the refrigeration and air conditioning equipment 30 not to be monitored (S101).

[0098] The remote monitoring device 10 acquires operating data from the monitored refrigeration and air conditioning equipment 20, which is continuously connected via the network N, and calculates a refrigerant quantity index value based on the operating data (S102). Based on the refrigerant quantity index value and a first determination logic for determining refrigerant leakage from the monitored refrigeration and air conditioning equipment 20, the remote monitoring device 10 determines whether there is refrigerant leakage from the monitored refrigeration and air conditioning equipment 20 (S103).

[0099] The remote monitoring device 10 connects to the unmonitored refrigeration and air conditioning equipment 30 via the network N (S104). The remote monitoring device 10 acquires operating data from the unmonitored refrigeration and air conditioning equipment 30 and calculates a refrigerant quantity index value based on the operating data (S105). The remote monitoring device 10 determines whether there is a refrigerant leak in the unmonitored refrigeration and air conditioning equipment 30 based on the refrigerant quantity index value and a second determination logic for determining refrigerant leakage in the unmonitored refrigeration and air conditioning equipment 30 (S106). The second determination logic may be entirely the same as or partially the same as the first determination logic, or it may be a completely different logic.

[0100] The remote monitoring device 10 stores the operating data and refrigerant quantity index values ​​obtained from the refrigeration and air conditioning equipment 30 that is not being monitored (S107). If the acquired operating data and refrigerant quantity index values ​​are not to be used for the next refrigerant leakage determination, this step may be omitted.

[0101] These steps enable the implementation of a remote monitoring method according to one aspect of the present invention. However, the remote monitoring method according to one aspect of the present invention may include other steps as appropriate, depending on the measurement conditions and measurement environment. For example, when determining refrigerant leakage in an unmonitored refrigeration and air conditioning equipment 30, by adding the steps of obtaining operating data and refrigerant quantity index values ​​for the same model as the model to be determined from past data of the monitored refrigeration and air conditioning equipment 20 stored in the remote monitoring device 10, and using the acquired past data as reference data when determining refrigerant leakage in S106, refrigerant leakage can be accurately determined even if the quality of the short-term data of the unmonitored refrigeration and air conditioning equipment 30, which is temporarily acquired due to measurement conditions and measurement environment, is poor.

[0102] <Main effects of the embodiment> The remote monitoring device 10 according to this embodiment includes two independent logics: a first judgment logic for determining refrigerant leakage from the monitored refrigeration and air conditioning equipment 20, and a second judgment logic for determining refrigerant leakage from the non-monitored refrigeration and air conditioning equipment 30. Each logic can be specified according to the characteristics of the operating data it determines.

[0103] More specifically, because the second judgment logic differs from the first judgment logic in terms of the sampling interval of operating data and the number of data points available for judgment, the data smoothing method and judgment thresholds are also changed to settings unique to the second judgment logic, enabling accurate detection of refrigerant leakage even from unstable and highly variable data acquired in a short period of time.

[0104] Therefore, according to this embodiment, by temporarily connecting the non-monitored refrigeration and air conditioning equipment 30 to the remote monitoring device 10, it is possible to determine refrigerant leakage with an accuracy comparable to that of determining refrigerant leakage in the constantly connected monitored refrigeration and air conditioning equipment 20, and more accurately than the conventional method in which an inspector inspects and makes a judgment on-site.

[0105] <Other application examples> Although embodiments have been described above, it should be understood that various modifications to the form and details are possible without departing from the spirit and scope of the claims.

[0106] The apparatus described in the examples represents only one of several computing environments for carrying out the embodiments disclosed herein. In one embodiment, the remote monitoring device 10 includes several computing devices, such as a server cluster. The several computing devices are configured to communicate with each other via any type of communication link, including a network or shared memory, and to perform the processing disclosed herein.

[0107] Each of the functions of this disclosure described above can be implemented not only by software processing through program execution, but also by one or more processing circuits. Here, "processing circuit" as used herein includes processors programmed to execute each function by software, such as processors implemented by electronic circuits, as well as devices such as ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), FPGAs (Field Programmable Gate Arrays), and conventional circuit modules designed to execute each of the functions described above.

[0108] <Reasons why the effect occurs> A first aspect of this disclosure is that, "a fault diagnosis of the monitored refrigeration and air conditioning equipment is performed based on health indicator values ​​of the monitored refrigeration and air conditioning equipment that is continuously connected via a network and a trained model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment, and a fault diagnosis of the unmonitored refrigeration and air conditioning equipment is performed based on health indicator values ​​of the temporarily connected unmonitored refrigeration and air conditioning equipment and a trained model for performing fault diagnosis of the unmonitored refrigeration and air conditioning equipment," thereby enabling more accurate fault diagnosis of the temporarily connected unmonitored refrigeration and air conditioning equipment 30.

[0109] A second aspect of this disclosure is that "the refrigerant amount index value is calculated based on operating data obtained from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment," so even the non-monitored refrigeration and air conditioning equipment 30 can be diagnosed for malfunction by the remote monitoring device 10 based on its own operating data.

[0110] A third aspect of this disclosure is that "the sampling interval for acquiring the operation data from the monitored refrigeration and air conditioning equipment is different from the sampling interval for acquiring the operation data from the non-monitored refrigeration and air conditioning equipment," so that a sufficient amount of operation data necessary for a determination can be acquired in a short time from the temporarily connected non-monitored refrigeration and air conditioning equipment 30, and fault diagnosis can be performed.

[0111] A fourth aspect of this disclosure is that "the sampling interval for the health index value calculated based on the operating data acquired from the monitored refrigeration and air conditioning equipment is different from the sampling interval for the health index value calculated based on the operating data acquired from the non-monitored refrigeration and air conditioning equipment." Therefore, in order to accurately determine refrigerant leakage, the trained model can set the sampling interval for calculating the health index value based on the characteristics of the operating data acquired in large quantities in a short time from the temporarily connected non-monitored refrigeration and air conditioning equipment 30.

[0112] A fifth aspect of this disclosure is that "the control unit performs fault diagnosis of the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment based on data obtained by averaging the health indicator values, and the number of data points for the health indicator values ​​used in the averaging process of the monitored refrigeration and air conditioning equipment is different from the number of data points for the refrigerant amount indicator values ​​used in the averaging process of the health indicator values ​​of the non-monitored refrigeration and air conditioning equipment," so that even if there are large fluctuations in the health indicator values ​​of the non-monitored refrigeration and air conditioning equipment 30, misjudgments in fault diagnosis can be suppressed.

[0113] A sixth aspect of this disclosure is that "the control unit performs fault diagnosis based on the threshold values ​​of the health indicators, and the threshold values ​​of the health indicators for the monitored refrigeration and air conditioning equipment are different from the threshold values ​​of the health indicators for the non-monitored refrigeration and air conditioning equipment," so that even if there are large fluctuations in the health indicators of the non-monitored refrigeration and air conditioning equipment 30, misjudgments regarding fault diagnosis can be suppressed.

[0114] A seventh aspect of this disclosure states that "the operating conditions of the unmonitored refrigeration and air conditioning equipment when acquiring the operating data from the unmonitored refrigeration and air conditioning equipment are different from the operating conditions during normal operation," and "the operating conditions when acquiring the operating data include at least one of the number of outdoor units of the unmonitored refrigeration and air conditioning equipment, the number of indoor units, the room temperature setting set by the remote control, the fan airflow setting, and the heating and cooling operating mode." Therefore, when the remote monitoring device 10 temporarily connects to the unmonitored refrigeration and air conditioning equipment 30 to acquire operating data, the operating state of the unmonitored refrigeration and air conditioning equipment 30 can be adjusted by the remote control so that the operating data is suitable for detecting refrigerant leakage.

[0115] The eighth aspect of this disclosure is that "the control unit performs a fault diagnosis of the unmonitored refrigeration and air conditioning equipment based on the health index value of the unmonitored refrigeration and air conditioning equipment and the health index value of the same or similar model of the unmonitored refrigeration and air conditioning equipment extracted from past data of the monitored refrigeration and air conditioning equipment stored in advance." Therefore, even if the quality of the operating data of the unmonitored refrigeration and air conditioning equipment 30 acquired temporarily is poor due to environmental conditions, load conditions, etc., and the reliability of the calculated refrigerant amount index value is low, an accurate fault diagnosis can be performed by also referring to the data of the monitored refrigeration and air conditioning equipment of the same or similar model as the unmonitored refrigeration and air conditioning equipment 30.

[0116] A ninth aspect of this disclosure is that "the control unit stores the operating data and calculated health indicator values ​​obtained from the unmonitored refrigeration and air conditioning equipment, and the next time a fault diagnosis is performed on the unmonitored refrigeration and air conditioning equipment, it performs a fault diagnosis on the unmonitored refrigeration and air conditioning equipment based on the stored operating data and health indicator values ​​and the acquired operating data and calculated health indicator values," so that a fault diagnosis of the unmonitored refrigeration and air conditioning equipment 30 can be performed based on long-term changes in the health indicator values.

[0117] A tenth aspect of this disclosure is that "the health index value is a refrigerant amount index value which is an estimated value of the amount of refrigerant calculated based on operating data obtained from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment, or a value which has a strong correlation with the amount of refrigerant, and the fault diagnosis performed by the control unit is the determination of the amount of refrigerant held by the monitored refrigeration and air conditioning equipment and the monitored refrigeration and air conditioning equipment," so that refrigerant leakage can be determined more accurately for the temporarily connected non-monitored refrigeration and air conditioning equipment 30.

[0118] An eleventh aspect of this disclosure is that, "a fault diagnosis of the monitored refrigeration and air conditioning equipment is performed based on health indicator values ​​of the monitored refrigeration and air conditioning equipment that is continuously connected via a network and a learned model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment, and a fault diagnosis of the unmonitored refrigeration and air conditioning equipment is performed based on health indicator values ​​of the temporarily connected unmonitored refrigeration and air conditioning equipment and a learned model different from the learned model for performing fault diagnosis of the unmonitored refrigeration and air conditioning equipment," thereby enabling more accurate fault diagnosis of the temporarily connected unmonitored refrigeration and air conditioning equipment 30. [Explanation of symbols]

[0119] 1. Remote monitoring system for refrigeration and air conditioning. 10 Remote monitoring device 11 Control Unit 20. Refrigeration and air conditioning equipment under monitoring 30 Refrigeration and air conditioning equipment not subject to monitoring 40 Terminal devices N Network

Claims

1. A remote monitoring device for refrigeration and air conditioning equipment, which includes a control unit, The control unit, Based on health indicator values ​​of the monitored refrigeration and air conditioning equipment, which are continuously connected via a network, and a trained model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment, fault diagnosis of the monitored refrigeration and air conditioning equipment is performed. Based on the health indicator values ​​of the temporarily connected, unmonitored refrigeration and air conditioning equipment and the learned model used to diagnose the failure of the unmonitored refrigeration and air conditioning equipment, the system performs a failure diagnosis of the unmonitored refrigeration and air conditioning equipment. Remote monitoring device.

2. The aforementioned health indicator values ​​are calculated based on operating data obtained from the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment. The remote monitoring device according to claim 1.

3. The sampling interval when acquiring operating data from the aforementioned monitored refrigeration and air conditioning equipment is: The sampling interval for acquiring operating data from the aforementioned non-monitored refrigeration and air conditioning equipment is different from the sampling interval used for this purpose. The remote monitoring device according to claim 1.

4. The sampling interval for the health index values ​​calculated based on the operating data obtained from the monitored refrigeration and air conditioning equipment is: The sampling interval for the health index values ​​calculated based on the operating data obtained from the aforementioned non-monitored refrigeration and air conditioning equipment is different from the sampling interval for the aforementioned health index values. The remote monitoring device according to claim 1.

5. The control unit, Based on the averaged data of the aforementioned health indicator values, a fault diagnosis is performed on the monitored refrigeration and air conditioning equipment and the non-monitored refrigeration and air conditioning equipment. The number of health indicator data used in the averaging process for the health indicator values ​​of the monitored refrigeration and air conditioning equipment is different from the number of health indicator data used in the averaging process for the health indicator values ​​of the non-monitored refrigeration and air conditioning equipment. The remote monitoring device according to claim 1.

6. The control unit, A fault diagnosis is performed based on the threshold values ​​of the aforementioned health indicators. The threshold value of the health indicator for the monitored refrigeration and air conditioning equipment is different from the threshold value of the health indicator for the non-monitored refrigeration and air conditioning equipment. The remote monitoring device according to claim 1.

7. When acquiring operating data from the aforementioned unmonitored refrigeration and air conditioning equipment, the operating conditions of the unmonitored refrigeration and air conditioning equipment differ from the operating conditions during normal operation. The operating conditions for acquiring operating data include at least one of the following: the number of outdoor units operating, the number of indoor units operating, the room temperature set by the remote control, the fan airflow setting, and the heating / cooling operating mode of the refrigeration and air conditioning equipment not subject to monitoring. The remote monitoring device according to claim 1.

8. The control unit, The health indicator values ​​of the aforementioned refrigeration and air conditioning equipment not subject to monitoring, The health indicator values ​​of the same or similar models as the monitored refrigeration and air conditioning equipment, extracted from past data of the monitored refrigeration and air conditioning equipment that is stored in advance, Based on this, a fault diagnosis is performed on the refrigeration and air conditioning equipment that is not subject to monitoring. The remote monitoring device according to claim 1.

9. The control unit, The system stores the operating data obtained from the refrigeration and air conditioning equipment not subject to monitoring and the calculated health indicator values. Next time a fault diagnosis is performed on the refrigeration and air conditioning equipment not subject to monitoring, the fault diagnosis will be performed on the refrigeration and air conditioning equipment not subject to monitoring based on the stored operating data and the health indicator values, and the acquired operating data and the calculated health indicator values. The remote monitoring device according to claim 1.

10. The aforementioned health indicator value is a refrigerant amount indicator value which is an estimated value of the refrigerant amount calculated based on operating data obtained from the monitored refrigeration and air conditioning equipment and the refrigeration and air conditioning equipment not subject to monitoring, or a value that has a strong correlation with the refrigerant amount. The fault diagnosis performed by the control unit is to determine the amount of refrigerant in the monitored refrigeration and air conditioning equipment. A remote monitoring device according to any one of claims 1 to 9.

11. A remote monitoring device for refrigeration and air conditioning equipment, which includes a control unit, The control unit, Based on health indicator values ​​of the monitored refrigeration and air conditioning equipment, which are continuously connected via a network, and a trained model for performing fault diagnosis of the monitored refrigeration and air conditioning equipment, fault diagnosis of the monitored refrigeration and air conditioning equipment is performed. Based on the health indicator values ​​of the temporarily connected, unmonitored refrigeration and air conditioning equipment, and a different trained model from the trained model used to diagnose the failure of the unmonitored refrigeration and air conditioning equipment, the system performs a failure diagnosis of the unmonitored refrigeration and air conditioning equipment. Remote monitoring device.

12. A remote monitoring method performed by a remote monitoring device, A step of performing a fault diagnosis on a monitored refrigeration and air conditioning equipment based on health indicator values ​​of the monitored refrigeration and air conditioning equipment connected continuously via a network and a trained model for performing fault diagnosis on the monitored refrigeration and air conditioning equipment, A step of performing a fault diagnosis of the unmonitored refrigeration and air conditioning equipment based on the health indicator values ​​of the temporarily connected unmonitored refrigeration and air conditioning equipment and the learned model for performing fault diagnosis of the unmonitored refrigeration and air conditioning equipment, A remote monitoring method including

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