Abnormality site estimation system, abnormality site estimation method, and program

Abstract

An adverse condition site estimation system includes a control unit that controls a refrigeration air conditioning system, outputs adverse condition information indicating a site of an adverse condition, candidates for the site of the adverse condition, or a range of the adverse condition, using sensor information of a sensor that detects an adverse condition occurring in the refrigeration air conditioning system and setting position information indicating positions of one or more constituent elements included in the refrigeration air conditioning system.

Description

Technical Field

[0001] This disclosure relates to a system, method, and procedure for estimating the location of adverse conditions. Background Technology

[0002] In refrigeration and air conditioning systems, including refrigeration and air conditioning equipment used for purposes such as freezing, refrigeration, or air conditioning, there are known techniques for using sensors to determine the location of malfunctions.

[0003] For example, a refrigerant leak detection system is known, which includes a refrigerant leak detection device that detects refrigerant leaks based on the outputs of multiple refrigerant sensors and multiple alarms, and displays the area where the refrigerant leak occurs on a display device when a refrigerant leak occurs (for example, see Patent Document 1).

[0004] [Existing Technical Documents]

[0005] [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2017-525732 Summary of the Invention

[0007] The problem to be solved by the present invention

[0008] In a refrigeration and air conditioning system that includes multiple components, when it is determined that a malfunction has occurred at a certain location, in the technology disclosed in Patent Document 1, since a sensor is required at each location where a malfunction may occur, it is difficult to reduce the number of sensors.

[0009] This disclosure enables a refrigeration and air conditioning system comprising multiple components to provide malfunction information, such as the location of the malfunction, a candidate location of the malfunction, or the extent of the malfunction, with fewer sensors.

[0010] [Methods for solving problems]

[0011] According to the first aspect of the present disclosure, the defect location estimation system includes a control unit that controls a refrigeration and air conditioning system. The control unit uses sensor information from a sensor that detects a defect occurring in the refrigeration and air conditioning system and setting position information that indicates the location of one or more components included in the refrigeration and air conditioning system, and outputs defect information indicating the location where the defect occurs, a candidate for the location where the defect occurs, or the range where the defect occurs.

[0012] According to the first aspect of this disclosure, in a refrigeration and air conditioning system comprising multiple components, it is possible to provide malfunction information, such as the location of the malfunction, a candidate location of the malfunction, or the extent of the malfunction, with fewer sensors.

[0013] The second aspect of the present invention is the defect location estimation system described in the first aspect, wherein the defect information includes information on the constituent elements among the one or more constituent elements that may have experienced the defect.

[0014] The third aspect of the present invention is the defect location estimation system described in the first aspect, wherein the sensor information includes information related to the location where the sensor is set.

[0015] The fourth aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the control unit further uses sensor information obtained from one or more sensors that acquire environmental information to output the defect information.

[0016] The fifth aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the control unit uses sensor information from two or more sensors that detect the defect and the setting location information to output the defect information.

[0017] The sixth aspect of the present invention is the defect location estimation system described in the first aspect, wherein the control unit uses sensor information from the two or more sensors to define the location, candidate, or range where the defect occurs.

[0018] The seventh aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the control unit improves the accuracy of the defect information by combining sensor information from multiple sensors of the same or different types.

[0019] The eighth aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the setting location information includes information indicating the location of the connection of the piping connected to the equipment included in the refrigeration and air conditioning system, and the control unit uses sensor information from one or more refrigerant sensors or gas sensors and the setting location information to estimate candidate locations for refrigerant leaks.

[0020] The ninth aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the setting location information includes information indicating the location of equipment included in the refrigeration and air conditioning system and the connection of piping or pipes connected to the equipment, and the control unit estimates a candidate location where the defect occurs based on sensor information obtained from multiple sound sensors that acquire sound, the sound level or detection time of each sound sensor, and the setting location information.

[0021] The tenth aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the setting location information includes information indicating the location of equipment included in the refrigeration and air conditioning system, and the control unit estimates a candidate location where the defect occurs based on sensor information obtained from multiple vibration sensors that detect vibration, the magnitude of vibration or detection time of each vibration sensor, and the setting location information.

[0022] The eleventh aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the setting location information includes information indicating the connection portion of the piping connected to the equipment included in the refrigeration and air conditioning system, and the control unit estimates a candidate location where the defect occurs based on the sensor information obtained from a plurality of leak sensors that detect leaks and the leak detection time of each of the leak sensors.

[0023] The 12th aspect of this disclosure is the defect location estimation system described in the first aspect, wherein the setting location information includes drawing information indicating the configuration of the constituent element, the sensor includes one or more cameras for capturing images of the constituent element, and the control unit estimates a candidate location where the defect occurs based on the images captured by the one or more cameras and the drawing information.

[0024] According to the method for estimating the location of a defect according to the 13th aspect of this disclosure, a computer controlling a refrigeration and air conditioning system uses sensor information from a sensor that detects a defect occurring in the refrigeration and air conditioning system and setting position information indicating the location of one or more constituent elements included in the refrigeration and air conditioning system to output defect information indicating the location where the defect occurs, a candidate for the location where the defect occurs, or the range where the defect occurs.

[0025] According to the procedure of the 14th aspect of this disclosure, a computer controlling the refrigeration and air conditioning system is instructed to: use sensor information from sensors that detect malfunctions occurring in the refrigeration and air conditioning system and setting position information indicating the location of one or more components included in the refrigeration and air conditioning system, and output malfunction information indicating the location where the malfunction occurs, a candidate for the location where the malfunction occurs, or the range where the malfunction occurs. Attached Figure Description

[0026] Figure 1 This is a diagram illustrating an example of the system structure for inferring the system's structure based on the defective parts of one implementation.

[0027] Figure 2 This is a schematic diagram illustrating an example of setting location information in one implementation method.

[0028] Figure 3 This is a diagram illustrating an example of adverse condition information according to one implementation method.

[0029] Figure 4 This is a diagram illustrating another example of adverse condition information according to one implementation method.

[0030] Figure 5 This is a diagram illustrating an example of the hardware structure of a computer according to one implementation method.

[0031] Figure 6 This is a diagram illustrating an example of the functional structure of a system for estimating the location of a defect based on one implementation.

[0032] Figure 7A Figure (1) shows an example of sensor information according to one implementation.

[0033] Figure 7B Figure (2) shows an example of sensor information according to one implementation.

[0034] Figure 7C Figure (3) shows an example of sensor information according to one implementation.

[0035] Figure 7D Figure (4) shows an example of sensor information according to one implementation.

[0036] Figure 8A Figure (1) shows an example of setting location information according to one implementation method.

[0037] Figure 8B Figure (2) shows an example of setting location information according to one implementation method.

[0038] Figure 9AThis is a flowchart (1) illustrating an example of presumed treatment of defective parts according to the first embodiment.

[0039] Figure 9B This is a flowchart (2) illustrating an example of presumed treatment of defective parts according to the first embodiment.

[0040] Figure 10 This is a diagram illustrating an example of adverse condition information according to the first embodiment.

[0041] Figure 11A This is a flowchart (1) illustrating an example of presumed treatment of defective parts according to the second embodiment.

[0042] Figure 11B This is a flowchart (2) illustrating an example of presumed treatment of defective parts according to the second embodiment.

[0043] Figure 12A This is a flowchart (1) illustrating an example of the presumed treatment of defective parts in the third embodiment.

[0044] Figure 12B This is a flowchart (2) illustrating an example of presumed treatment of defective parts according to the third embodiment.

[0045] Figure 13 This is a diagram used to illustrate the specified distances in the second and third embodiments.

[0046] Figure 14 This is a flowchart illustrating an example of presumed treatment of defective parts according to the fourth embodiment.

[0047] Figure 15 This is a flowchart illustrating an example of presumed treatment of defective parts according to the fifth embodiment.

[0048] Figure 16 This is a diagram illustrating an example of camera setup according to the fifth embodiment.

[0049] Figure 17 This is a diagram illustrating another application example of a system for estimating the location of a defect based on one implementation. Detailed Implementation

[0050] Hereinafter, each embodiment will be described with reference to the accompanying drawings. Furthermore, in this specification and the accompanying drawings, structural elements having substantially the same functional structure are labeled with the same symbols, thereby omitting redundant descriptions.

[0051] <System Structure>

[0052] A fault location estimation system is a system that uses one or more sensors to detect the occurrence of faults in refrigeration and air conditioning systems, such as those containing refrigeration equipment, cold storage equipment, or air conditioning equipment, and to estimate potential fault locations where faults have occurred. Here, as an example for illustrative purposes, the system structure of a fault location estimation system for estimating fault locations in an air conditioning system will be described.

[0053] Figure 1 This diagram illustrates an example of the system structure of a defect location estimation system according to one embodiment. The defect location estimation system 100 includes an air conditioning system 110, which includes, for example, one or more air conditioning units 111a, 111b, ..., one or more sensors 112a, 112b, ... for detecting defects in the air conditioning system 110, a controller 113, etc. Furthermore, in the following description, "air conditioning unit 111" is used when referring to any one or more air conditioning units 111a, 111b, ... and "sensor 112" is used when referring to any one or more sensors 112a, 112b, ...

[0054] Preferably, the defect location estimation system 100 includes a management server 120 capable of communicating with the controller 113 and sensors 112 via communication networks N1, N2, etc. Here, communication network N1 is, for example, the Internet or a LAN (local area network). Communication network N2 is a network, such as a LAN, used for communication between devices within the air conditioning system 110. However, communication network N2 is not limited to a LAN, and can also be a network of various communication methods capable of communication between devices within the air conditioning system 110. In the following description, unless there is a specific need to distinguish between communication networks N1 and N2, they will simply be referred to as "communication network".

[0055] Air conditioning equipment 111 is, for example, equipment for adjusting (regulating) the air environment within a facility, such as temperature, humidity, cleanliness, or airflow. Air conditioning equipment 111 may include various components, such as indoor units, outdoor units, environmental sensors, coolers (cooling water circulation systems), air handling units, piping, connectors, or conduits. Additionally, air conditioning equipment 111 may also include, for example, ventilation devices and components such as ducts, air outlets, and air inlets for these devices.

[0056] Sensor 112 is a detection device for detecting malfunctions in the air conditioning system 110. Sensor 112 may include various detection devices, such as a refrigerant sensor (or gas sensor) for detecting refrigerant leaks, a leak sensor for detecting water leaks, a sound sensor (e.g., a microphone) for detecting sound, a vibration sensor for detecting vibrations, or a camera, etc.

[0057] The controller (control unit) 113 has a computer structure and controls one or more air conditioning units 111a, 111b, etc., by executing a prescribed program. For example, the controller 113 displays an operation screen on a touch panel display or the like, and controls the temperature, humidity, airflow, or cleanliness of the facility according to the operation of the manager or user. Furthermore, the controller 113 is an example of a control unit that controls an air conditioning system (refrigeration and air conditioning system) 110. The control unit in this embodiment is, for example, hardware such as a computer, processor, CPU (Central Processing Unit), ASIC (application-specific integrated circuit), or FPGA (Field Programmable Gate Array).

[0058] Furthermore, in this embodiment, the controller 113 stores the installation location information, indicating the location of one or more air conditioning units 111a, 111b, ... included in the air conditioning system 110, in its storage unit or management server 120 for management. Moreover, the controller 113 has the function of detecting malfunctions occurring in the air conditioning system 110 using sensor information containing inherent information from one or more sensors 112a, 112b, ... and the installation location information, and outputting malfunction information indicating potential locations of the malfunctions.

[0059] In addition, at least some of the functions of the controller 113, such as controlling the air conditioning equipment, acquiring sensor information, managing setting location information, and outputting adverse condition information, can also be possessed by the management server.

[0060] Management server 120 is an information processing device with computer configuration or a system including multiple computers. Management server 120 may also be, for example, a cloud system that manages multiple air conditioning systems 110.

[0061] (Regarding setting location information)

[0062] The malfunction location estimation system 100 (controller 113 or management server 120) manages and displays the location information of one or more components of the air conditioning equipment 111 included in the air conditioning system 110.

[0063] Figure 2 This is a schematic diagram illustrating an example of setting location information in one implementation method. As an example of the setting location information, such as... Figure 2 As shown, the drawing information 200 includes a room 220 where an air conditioning unit 111 is installed, and records the installation locations of one or more components of the air conditioning system 110 installed in the room 220. Figure 2 In this example, the drawing information 200 records information indicating the locations of indoor units 201a-201d, refrigerant piping 203 connected to the indoor units, and connection points 204a-204h of the piping 203, as seen in a view of room 220 from above. Additionally, the drawing information 200 records the locations of the ventilation system 210, the pipe 211 connected to the ventilation system 210, multiple air outlets 212, and multiple air inlets 213. Furthermore, the drawing information 200 may also record the locations of one or more sensors 112a and 112b for detecting malfunctions, and environmental sensors 202a-202d respectively equipped in indoor units 201a-201d.

[0064] The drawing information 200 is, for example, created by the provider of the air conditioning system 110 or the manager of the air conditioning system 110 based on the design drawings or construction drawings used during the construction of the air conditioning equipment 111, and stored in the controller 113 or management server 120, etc. Alternatively, the fault location estimation system 100 may also have the function of analyzing the design drawings or construction drawings used during the construction of the air conditioning equipment 111 to generate the drawing information 200.

[0065] Preferably, the location information includes device coordinate information, which stores identification information for identifying one or more components included in the air conditioning system 110 and coordinate information indicating the location of each component.

[0066] (Information regarding adverse conditions)

[0067] The defect location estimation system 100 acquires sensor information from sensors 112a and 112b that detect defects. When a defect is detected, it uses the acquired sensor information and setting location information to output defect information indicating candidate locations of defects.

[0068] Figure 3 This is a schematic diagram illustrating an example of adverse condition information according to one embodiment. This diagram, as an example, shows... Figure 2In the event that sensor 112a detects a refrigerant leak through piping 203 (hereinafter referred to as refrigerant leak), an example of a defect location estimation system 100 outputting defect information 300.

[0069] The fault location estimation system 100, for example, determines the location of a fault based on the inherent information contained in the sensor information of sensor 112a when sensor 112a detects a refrigerant leak. Figure 2 The drawing information 200 shows the position (coordinate information) of sensor 112a. Additionally, the defect location estimation system 100 uses the setting position information (e.g., Figure 2 (See drawing information 200, etc.) to extract potential components from sensor 112a that are located within a specified range and are considered potential locations for refrigerant leakage. Here, the potential components for potential locations for refrigerant leakage are defined as the connection parts 204a, 204b, 204c, and 204d of the extraction piping 203.

[0070] At this point, as an example, the defect location estimation system 100... Figure 3 As shown, the output includes defect information 300, such as a graph 301 indicating the candidate location of the defective part, a string 302 indicating the candidate defective part, and a string 303 indicating the range of the defect. For example, the defective part estimation system 100 can... Figure 3 The malfunction information 300 shown is displayed on the controller 113, etc., and can also be sent to a pre-logged information terminal, etc.

[0071] pass Figure 3 The malfunction information 300 shown allows the manager of the air conditioning system 110 or the user of the air conditioning system 110 to easily identify the possibility of refrigerant leakage at any of the connections 204a to 204d of the piping 203.

[0072] Figure 4 This is a diagram illustrating another example of adverse condition information according to one implementation method. This diagram, as an example, shows... Figure 2 This is an example of a defect information 400 output by the defect location estimation system 100 when sensors 112a and 112b simultaneously detect a refrigerant leak through piping 203.

[0073] The fault location estimation system 100, for example, determines the location of a fault based on the inherent information contained in the sensor information of sensor 112 when sensors 112a and 112b detect a refrigerant leak. Figure 2The drawing information 200 shows the positions of sensors 112a and 112b. Additionally, the fault location estimation system 100 uses the setting location information (e.g., Figure 2 Based on the drawing information 200, candidate components for refrigerant leakage are extracted from sensors 112a and 112b, which are located within a specified range. Here, the connection parts 204a to 204h of the piping 203 are selected as candidate components for refrigerant leakage.

[0074] In this case, as an example, the defect location estimation system 100... Figure 4 As shown, the output includes a defect information 300, which includes a figure 401 indicating the candidate location of the defective part, a string 302 indicating the candidate defective part, and a string 303 indicating the range of the defect.

[0075] In the existing technology, if a refrigerant leak is detected in the entire room 220, it can only be determined that a refrigerant leak has occurred in the room 220, and it is difficult to indicate the alternative location of the problem.

[0076] On the other hand, in the defect location estimation system 100 according to this embodiment, sensor information from the sensor 112 that detects refrigerant leakage and location information are used to extract candidates for defect locations, for example, providing... Figure 4 The defect information 400 is shown. Furthermore, the defect location estimation system 100 according to this embodiment has the function of further narrowing down the candidates for defect locations based on the time difference between the time when sensor 112a detects the defect and the time when sensor 112b detects the defect. Regarding the specific processing details, several embodiments will be described later.

[0077] Thus, according to this embodiment, in a refrigeration and air conditioning system that includes multiple components, it is possible to determine the location of the malfunction, the alternative locations of the malfunction, or the range of the malfunction with fewer sensors.

[0078] <Hardware Structure>

[0079] (Hardware architecture of the controller and management server)

[0080] Controller 113 and management server 120 have, for example Figure 5 The hardware structure of computer 500 is shown. As another example, management server 120 may include multiple computers 500.

[0081] Figure 5This is a diagram illustrating an example of the hardware structure of a computer according to one embodiment. The computer 500 includes, for example, a CPU (Central Processing Unit) 501, a memory 502, a storage device 503, a communication device 504, an output device 505, an input device 506, a bus 507, etc.

[0082] CPU 501 is a processor that implements various functions of the fault location estimation system 100 by executing predetermined programs stored, for example, in a recording medium such as storage device 503 or memory 502. Memory 502 includes, for example, volatile memory such as RAM (Random Access Memory) used as the working area of ​​CPU 501, and non-volatile memory such as ROM (Read Only Memory) used as the storage medium for storing boot programs of computer 500. For example, storage device 503 is a large-capacity storage device that stores programs such as OS (operating system), application programs, and various data, and is implemented by SSD (Solid State Drive) or HDD (Hard Disk Drive).

[0083] Communication device 504 is a communication interface, such as a LAN or WAN (Wide Area Network), that connects computer 500 to a communication network and enables communication with other devices. Output device 505 includes, for example, a display device that displays various screens such as error messages or operation screens; or a sound output device that outputs sound messages or error sounds. Input device 506 is, for example, an input device that receives input from devices such as touch panels, keyboards, or indicator devices. Alternatively, input device 506 may also be a display input device such as a touch panel display. Bus 507 is connected to the aforementioned components, for example, transmitting address signals, data signals, and various control signals.

[0084] (Hardware structure of air conditioning equipment and sensors)

[0085] The air conditioning unit 111 and the sensor 112 are envisioned to utilize known air conditioning units 111 and sensors 112, for example, those with computer structures and communication devices, so detailed descriptions are omitted here.

[0086] <Functional Structure>

[0087] Figure 6 This diagram illustrates an example of the functional configuration of a defect location estimation system according to an embodiment. The defect location estimation system 100 includes, for example, a communication unit 601, an acquisition unit 602, an output unit 603, an operation receiving unit 604, a sensor information storage unit 605, and a setting position information storage unit 606.

[0088] The communication unit 601, acquisition unit 602, output unit 603, and operation receiving unit 604 are implemented, for example, by a program executed by the computer 500 (controller 113 and / or management server 120) included in the fault location estimation system 100. Alternatively, at least some of the above functional structures can also be implemented in hardware. Furthermore, the sensor information storage unit 605 and the setting location information storage unit 606 are implemented, for example, by the storage device 503 or memory 502 of the computer 500 included in the fault location estimation system 100.

[0089] For example, the Communications Department 601 uses Figure 5 The communication device 504, etc., connects the fault location estimation system 100 to the communication network and performs communication processing to communicate with other devices.

[0090] The acquisition unit 602 performs acquisition processing, for example, to acquire sensor information via the communication unit 601. The sensor information includes inherent information from one or more sensors 112a, 112b, ... that detect adverse conditions occurring in the air conditioning system (an example of a refrigeration air conditioning system) 110.

[0091] Figure 7A This is an image representing an example of sensor information output by sensor 112. Figure 7A In the example, sensor information 701 includes a management ID (an example of inherent information) used to identify sensor 112 and one or more sensor data sets (sensor data 1, sensor data 2, ...). The management ID can be identification information assigned by the fault location estimation system 100, or other inherent information such as the address information (IP address or MAC address) of sensor 112. Sensor data are detection data acquired by sensor 112, such as Freon concentration data, temperature data, humidity data, sound data, vibration data, or image data.

[0092] In this case, the defect location estimation system 100 pre-stores, for example, information in the sensor information storage unit 605, etc. Figure 7B The sensor location information 702 is shown as described. The sensor location information 702 stores the management IDs of multiple sensors 112 and the location coordinates indicating the positions of each sensor 112. Therefore, the fault location estimation system 100 can use the management IDs and sensor location information 702 contained in the sensor information 701 output by the sensor 112 to determine the position of the sensor 112 that output the sensor information 701.

[0093] Figure 7C This is another example image representing the sensor information output by sensor 112. Figure 7C In the examples, except Figure 7AIn addition to the sensor information 701 shown, the sensor information 703 also includes position coordinates. Thus, the sensor information output by the sensor 112 can also include position coordinates (an example of information related to setting the position of the sensor 112).

[0094] Figure 7D This diagram illustrates an example of sensor information 704 stored in the sensor information storage unit 605. Sensor information 704 includes information such as management ID, location coordinates, data from one or more sensors, and detection time, contained in sensor information acquired from multiple sensors 112. The detection time information can be the time contained in the sensor information output by the sensor 112, or it can be assigned when the acquisition unit 602 stores the sensor information acquired from the sensor 112 into sensor information 704.

[0095] Alternatively, if the controller 113 has an acquisition unit 602, the acquisition unit 602 can also acquire sensor information from the management server 120. Figure 7D The sensor information 704 shown is stored in the sensor information storage unit 605 of the controller 113. In short, the acquisition unit 602 only needs to... Figure 7D The sensor information 704 shown is stored in the sensor information storage unit 605, so the obtained sensor information can be in any form.

[0096] The output unit 603 performs output processing based on the sensor information 704 acquired by the acquisition unit 602 and the setting position information stored in the setting position information storage unit 606, outputting information indicating the location where a malfunction has occurred, a candidate location where a malfunction has occurred, or the range of a malfunction. The output unit 603 includes, for example, an estimation unit 611, a display control unit 612, and a sound control unit 613.

[0097] The estimation unit 611 uses the sensor information obtained by the acquisition unit 602 and the installation location information indicating the location of one or more components included in the air conditioning system 110 to estimate (extract) the candidate part of the part where the malfunction occurred when a malfunction occurs.

[0098] Figure 8A This diagram illustrates an example of drawing information 801 included in the location information. In drawing information 801, [the information is related to...]. Figure 2 The drawing information 200 also records the location of one or more components of the air conditioning system 110 installed in room 220. Figure 8AIn the example, drawing information 801, in a view of room 220 from above, records information indicating the positions of indoor units 201a-201d, refrigerant piping 203 connected to the indoor units, and connection points 204a-204h of the piping 203. Additionally, drawing information 801 also records information indicating the positions of ventilation unit 210, pipes 211a-211d connected to the ventilation unit 210, air outlets 212a-212d, and air inlets 213a-213d. Furthermore, drawing information 801 may also record information indicating the positions of one or more sensors 112a, 112b for detecting malfunctions, and environmental sensors 202a-202d respectively equipped in indoor units 201a-201d.

[0099] Figure 8B This diagram illustrates an example of device coordinate information 802 included in the location setting information. Device coordinate information 802 records management IDs that identify one or more components included in the air conditioning system 110, display names for each component, and coordinate information indicating the location of each component. The management ID is identification information for each component. The display name is information indicating the name of each component, for example, when displayed in a fault condition information. The location coordinates are, for example, coordinates indicating the location of the component obtained from design drawings, construction drawings, or drawing information 801 during the construction of the air conditioning equipment 111. As an example, the location coordinates are represented by coordinates on drawing information 801. As another example, the location coordinates may also be three-dimensional location information located through a location information system within the facility. Furthermore, drawing information 801 and device coordinate information 802 are examples of location setting information.

[0100] For example, if a sensor 112 detects a defect, the estimation unit 611 will consider a specified component located within a specified distance from the sensor 112 that detected the defect as a candidate for a defect location.

[0101] Preferably, the defect location estimation system 100 predetermines the components that are likely to cause the defect based on the type of sensor 112 that detects the defect. For example, if it is predetermined that a refrigerant leak is occurring at the connection of the piping 203, the connection of the piping 203 becomes a predetermined component corresponding to the refrigerant sensor.

[0102] Furthermore, when multiple sensors 112 detect a defect, the estimation unit 611 identifies a predetermined component located within a predetermined distance from all sensors 112 that detected the defect as a candidate for a defect location. Since the processing of the estimation unit 611 can be modified or applied in various ways, several specific embodiments will be described later.

[0103] The display control unit 612 generates, for example, candidate defect information (display screen) representing the defective location extracted by the estimation unit 611, and displays the generated defect information on the display unit of the controller 113, management server 120, or an information terminal connected to the management server 120. Figure 3 , 4 The defect information 300 and 400 described herein are examples of defect information generated and displayed by the display control unit 612.

[0104] For example, if the malfunction information generated by the display control unit 612 includes sound (voice message, error tone, etc.), the sound control unit 613 outputs sound. Alternatively, as another example, the sound control unit 613 may also generate candidate malfunction information (voice message, error tone, etc.) representing the malfunction location extracted by the estimation unit 611, and output the generated malfunction information, for example, from the controller 113, the management server 120, or an information terminal connected to the management server 120.

[0105] in addition, Figure 6 The functional structure of the output unit 603 shown is an example. For example, the functions of the estimation unit 611, the display control unit 612, and the sound control unit 613 can be implemented by a single output unit 603.

[0106] Operation receiving unit 604, for example, using Figure 5 The input device 506, etc., accepts various operations from the administrator or user. The sensor information storage unit 605, for example, stores... Figure 7D Sensor information 704 as shown. The location information storage unit 606 stores, for example, sensor information 704. Figure 8A The drawing information shown is 801, and Figure 8B The device coordinate information 802 and other setting location information are shown.

[0107] in addition, Figure 6 The functional structures included in the defect location estimation system 100 shown can be included in... Figure 1 The controller 113 can also be included in the management server 120. Alternatively, the various functional structures included in the fault location estimation system 100 can be distributed across the controller 113 and the management server 120. Here, it is assumed that the controller 113 has… Figure 6 The functional structure of the defect location estimation system 100 shown is explained below.

[0108] <Processing Flow>

[0109] Next, the process of the method for estimating the location of the defect according to this embodiment will be explained.

[0110] [First Implementation]

[0111] Figure 9A This is a flowchart illustrating an example of a presumed defect location treatment according to the first embodiment. The treatment indicates, for example, in... Figure 8A This is an example of the processing performed by the controller (control unit) 113 of the defect location estimation system 100 when a sensor 112 for detecting defects is installed in the room 220 to cover the entire room 220.

[0112] In step S901, the acquisition unit 602 of the output unit 603 acquires sensor information from the sensor 112 installed in the room 220 that detects malfunctions.

[0113] In step S902, the acquisition unit 602 determines whether a defective condition has been detected based on the acquired sensor information. For example, when the value of the sensor data included in the sensor information exceeds a predetermined threshold, the acquisition unit 602 determines that a defective condition has been detected.

[0114] In step S903, if a defective condition is detected, the acquisition unit 602 transfers the process to step S904. On the other hand, if no defective condition is detected, the acquisition unit 602 returns the process to step S901.

[0115] After moving to step S904, the estimation unit 611 of the output unit 603 extracts (estimates) candidate defect locations as constituent elements that may have experienced defective conditions, based on the sensor information obtained by the acquisition unit 602 and the position information stored in the setting position information storage unit 606.

[0116] Preferably, the estimation part 611, for example, is from... Figure 8A The drawing information shown is 801 or Figure 8B Extract the specified constituent elements corresponding to the defects detected by sensor 112 from the device coordinate information 802 shown.

[0117] In step S905, the output unit 603 generates and outputs defect information representing candidate (constituent elements) of the defect location extracted by the estimation unit 611. Additionally, if the estimation unit 611 extracts only one specified constituent element, the output unit 603 may also generate defect information that sets the constituent element extracted by the estimation unit 611 as a "defect location". Furthermore, the defect information may include information such as the room 220 where the sensor 112 is installed, as part of the "range of the defect".

[0118] At this time, the output unit 603 may, for example, use the display control unit 612 to generate malfunction information (display screen) and display it on the display unit of the controller 113 or management server 120. Alternatively, the output unit 603 may also use the sound control unit 613 to generate malfunction information (voice message, error tone, etc.) and output it from the controller 113 or management server 120. Furthermore, the output unit 603 may also send the malfunction information (display screen, voice message, error tone, etc.) to a pre-registered information terminal for administrators.

[0119] Figure 9B This is a flowchart illustrating a specific example of the presumed treatment of a defective location according to the first embodiment. The treatment indicates, for example, in... Figure 8A The sensor 112 shown in room 220 is an example of the handling of a Freon sensor for detecting refrigerant leakage.

[0120] In step S911, the acquisition unit 602 of the output unit 603 acquires sensor information from the sensor 112, which is a Freon sensor installed in the room 220.

[0121] In step S912, the acquisition unit 602 determines whether a refrigerant leak exists based on the acquired sensor information. For example, if the Freon concentration value contained in the sensor information is greater than a predetermined threshold, the acquisition unit 602 determines that a refrigerant leak has been detected.

[0122] In step S913, if a refrigerant leak is detected, the acquisition unit 602 transfers the process to step S914. On the other hand, if no refrigerant leak is detected, the acquisition unit 602 returns the process to step S911.

[0123] When the process moves to step S914, the estimation unit 611 of the output unit 603 extracts the connection portions 204a to 204h of the piping 203 as candidate refrigerant leak locations based on the sensor information obtained by the acquisition unit 602 and the location information stored in the setting location information storage unit 606. Furthermore, the connection portion of the piping 203 is an example of a predetermined component corresponding to the sensor 112, which serves as a Freon sensor.

[0124] In step S915, the display control unit 612 of the output unit 603 generates defect information illustrating the connection parts 204a to 204h of the piping 203 extracted by the estimation unit 611, and displays it, for example, on the display unit of the controller 113 or the management server 120.

[0125] Figure 10 This diagram illustrates an example of displaying the fault information shown by the control unit 612 in step S915. Figure 10 In the example, the malfunction information 400 displays a diagram 1001 indicating the candidate location of the refrigerant leak, a string 1002 indicating the candidate location of the refrigerant leak, and a string 1003 indicating the extent of the refrigerant leak.

[0126] In the prior art, this situation only indicates that a refrigerant leak has occurred in room 220. However, in the defect location estimation system 100 according to this embodiment, candidate locations for refrigerant leaks are extracted using location information, for example, it is possible to provide... Figure 10 The error message 1000 is shown.

[0127] [Second Implementation]

[0128] Figure 11A This is a flowchart illustrating an example of a presumed treatment of a defective location according to the second embodiment. The treatment indicates, for example, in... Figure 8A This is an example of the processing performed by the controller (control unit) 113 of the fault location estimation system 100 when multiple sensors 112 for detecting fault conditions are installed in the room 220 shown. Furthermore, a detailed description of the processing identical to that in the first embodiment is omitted here.

[0129] In step S1101, the acquisition unit 602 of the output unit 603 acquires sensor information from multiple sensors 112 installed in the room 220. For example, the acquisition unit 602 obtains sensor information from... Figure 7D The sensor information 704 shown is obtained from updated sensor information or sensor information within the most recent specified period.

[0130] In step S1102, the acquisition unit 602 determines whether a defective condition has been detected based on the acquired sensor information. For example, when the value of the sensor data included in the sensor information exceeds a predetermined threshold, the acquisition unit 602 determines that a defective condition has been detected.

[0131] In step S1103, when sensor information indicating a defect is detected, the acquisition unit 602 causes the process to proceed to step S1104. On the other hand, if no sensor information indicating a defect is detected, the acquisition unit 602 causes the process to return to step S1101.

[0132] After proceeding to step S1104, the estimation unit 611 of the output unit 603 obtains the position coordinates of one or more sensors 112 that detected a defect based on the sensor information obtained by the acquisition unit 602. Furthermore, in step S1105, the estimation unit 611 extracts a specified constituent element located within a specified distance from the obtained position coordinates.

[0133] In step S1106, when multiple sensors 112 detect a malfunction, the estimation unit 611 causes the process to proceed to step S1107. On the other hand, if only one sensor 112 detects a malfunction, the estimation unit 611 causes the process to proceed to step S1108.

[0134] After moving to step S1107, the estimation unit 611 extracts the specified constituent elements located within a specified distance from all sensors 112 that have detected the malfunction.

[0135] After proceeding to step S1108, the output unit 603 generates and outputs candidate defect information that represents the constituent elements extracted by the estimation unit 611 as defect locations. Additionally, if the estimation unit 611 extracts only one specified constituent element, the output unit 603 can also generate defect information that sets the constituent element extracted by the estimation unit 611 as a "defect location". Furthermore, the defect information may also include information indicating the "range of the defect".

[0136] Figure 11B This is a flowchart illustrating a specific example of the deviance site estimation process according to the second embodiment. The process includes, for example, Figure 8A The sensors 112a and 112b shown installed in room 220 are examples of the handling in the case of Freon sensors detecting refrigerant leaks. Alternatively, the number of sensors 112 for detecting refrigerant leaks can be three or more.

[0137] In step S1111, the acquisition unit 602 of the output unit 603 acquires sensor information from the sensor 112, which serves as one of the multiple Freon sensors installed in the room 220. For example, the acquisition unit 602 acquires sensor information from... Figure 7D The sensor information 704 shown is obtained from updated sensor information or sensor information within the most recent specified period.

[0138] In step S1112, the acquisition unit 602 determines whether a refrigerant leak has been detected based on the acquired sensor information. For example, if the value of the Freon concentration contained in the sensor information exceeds a threshold, the acquisition unit 602 determines that a refrigerant leak has been detected.

[0139] In step S1113, if sensor information indicating a refrigerant leak is detected, the acquisition unit 602 transfers the processing to step S1114. On the other hand, if no sensor information indicating a refrigerant leak is detected, the acquisition unit 602 returns the processing to step S1111.

[0140] After proceeding to step S1114, the estimation unit 611 of the output unit 603 obtains the position coordinates of one or more sensors (Freon sensors) 112 that have detected refrigerant leakage, based on the sensor information obtained by the acquisition unit 602. Furthermore, in step S1115, the estimation unit 611 extracts the connection portion of the piping (refrigerant piping) 203 within a predetermined distance of the obtained position coordinates. The connection portion of the piping 203 is an example of a predetermined component corresponding to the sensor (Freon sensor) 112.

[0141] In step S1116, if multiple sensors (Freon sensors) 112 detect refrigerant leakage, the estimation unit 611 transfers the process to step S1117. On the other hand, if only one sensor 112 detects refrigerant leakage, the estimation unit 611 transfers the process to step S1118.

[0142] After moving to step S1117, the estimation unit 611 extracts the connection of the piping 203 located within a specified distance from all sensors (Freon sensors) 112 that detect refrigerant leakage.

[0143] After proceeding to step S1118, the output unit 603 generates and outputs candidate defect information that represents the connection portion of the piping 203 extracted by the estimation unit 611 as a refrigerant leak location. For example, in the case of... Figure 8A When sensor 112a in room 220 detects a refrigerant leak, output unit 603 outputs... Figure 3 The error message 300 is shown.

[0144] Thus, the defect location estimation system 100 can use multiple sensors 112 to screen candidates for the location of the defect and improve the accuracy of the defect information.

[0145] In the above example, the sensor 112 for detecting refrigerant leakage is set as a Freon sensor, but it is not limited to this. Various gas sensors that can detect refrigerant leakage can also be used as sensor 112.

[0146] [Third Implementation]

[0147] In the first and second embodiments, examples of the sensor 112 that detects malfunctions being a Freon sensor or a gas sensor were described. In the third embodiment, examples of the sensor 112 that detects malfunctions being a sound sensor such as a microphone that acquires sound data, or a vibration sensor that detects vibrations, were described. Detailed descriptions of the same processing as in the first and second embodiments are omitted here.

[0148] Figure 12A This is a flowchart illustrating an example of the defect location estimation process according to the third embodiment. This process represents an example of the process executed by the controller (control unit) 113 of the defect location estimation system 100 when the sensor 112 that detects the defect is a sound sensor such as a microphone that acquires sound data.

[0149] In step S1201, the acquisition unit 602 of the output unit 603 acquires sensor information from multiple sound sensors installed in the room 220, and acquires sound data included in the sensor information. For example, the acquisition unit 602 acquires from... Figure 7D The sensor information 704 shown is obtained from updated sensor information or sensor information within the most recent specified period.

[0150] In step S1202, the acquisition unit 602 performs a defect determination on each acquired sound data. For example, if the sound data includes sounds with a volume greater than threshold 1, and the frequency of sounds greater than threshold 1 is higher than threshold 2 and lower than threshold 3, the acquisition unit 602 determines that a defect has been detected. In addition, thresholds 1 to 3 are preset values ​​based on the volume and frequency of sounds that occur or are predicted to occur when a defect occurs.

[0151] If sound data indicating a problem is detected in step S1203, the acquisition unit 602 transfers the processing to step S1204. On the other hand, if no sound data indicating a problem is detected, the acquisition unit 602 returns the processing to step S1201.

[0152] After moving to step S1204, the estimation unit 611 of the output unit 603 obtains the position coordinates of one or more sound sensors from the sensor information obtained by the acquisition unit 602: the sound data of the detected defective condition is obtained.

[0153] In step S1205, the estimation unit 611 extracts a predetermined component corresponding to the sound sensor, which is located within a predetermined distance from the obtained position coordinates. Furthermore, the predetermined component corresponding to the sound sensor may include, for example, equipment such as an indoor unit, cooler, or outdoor unit, or piping, pipes, or connectors (connections to piping or pipes).

[0154] In step S1206, if multiple sound sensors detect a malfunction, the estimation unit 611 causes the process to proceed to step S1207. On the other hand, if only one sound sensor detects a malfunction, the estimation unit 611 causes the process to proceed to step S1208.

[0155] When proceeding to step S1207, the estimation unit 611 extracts the specified constituent elements located within a predetermined distance from all sound sensors that have detected the defective condition.

[0156] After moving to step S1208, the output unit 603 generates and outputs candidate defect information that represents the specified constituent elements extracted by the estimation unit 611 as defect locations.

[0157] Through the above processing, the defect location estimation system 100 can output alternative defect information, such as equipment failure (e.g., motor failure in the machine) or loose equipment and piping, indicating defects other than refrigerant leakage.

[0158] Figure 12B This is a flowchart illustrating another example of the defect location estimation process in the third embodiment. This process illustrates an example of the process executed by the controller (control unit) 113 of the defect location estimation system 100 when the sensor 112 for detecting defects is a vibration sensor that detects vibration.

[0159] In step S1211, the acquisition unit 602 of the output unit 603 acquires sensor information from multiple vibration sensors installed in the room 220, and acquires vibration data contained in the sensor information. For example, the acquisition unit 602 obtains... Figure 7D The sensor information 704 shown is obtained from updated sensor information or sensor information within the most recent specified period.

[0160] In step S1212, the acquisition unit 602 determines the adverse condition of each acquired vibration data. For example, if the vibration data includes vibrations whose magnitude is greater than threshold A, and the frequency of the vibrations greater than threshold A is higher than threshold B and lower than threshold C, the acquisition unit 602 determines that an adverse condition has been detected. In addition, thresholds A to C are preset values ​​based on the magnitude and frequency of the vibrations that occur or are predicted to occur when an adverse condition occurs.

[0161] In step S1213, when vibration data indicating a defect is detected, the acquisition unit 602 transfers the processing to step S1214. On the other hand, if no vibration data indicating a defect is detected, the acquisition unit 602 returns the processing to step S1211.

[0162] After moving to step S1214, the estimation unit 611 of the output unit 603 obtains the position coordinates of one or more vibration sensors from the sensor information obtained by the acquisition unit 602, which obtains vibration data of the detected defective condition.

[0163] In step S1215, the estimation unit 611 extracts a predetermined component corresponding to the vibration sensor located within a predetermined distance from the obtained position coordinates. Furthermore, the predetermined component corresponding to the vibration sensor may include, for example, an indoor unit, a cooler, an outdoor unit, or other similar equipment.

[0164] In step S1216, if multiple vibration sensors detect a malfunction, the estimation unit 611 transfers the process to step S1217. On the other hand, if only one vibration sensor detects a malfunction, the estimation unit 611 transfers the process to step S1218.

[0165] After moving to step S1217, the estimation unit 611 extracts the specified constituent elements located within a specified distance from all vibration sensors that have detected the malfunction.

[0166] After moving to step S1218, the output unit 603 generates and outputs candidate defect information that represents the specified constituent elements extracted by the estimation unit 611 as defect locations.

[0167] Through the above processing, the defect location estimation system 100 can provide, for example, equipment defects, and other defect locations other than refrigerant leaks, alternative defect information.

[0168] (For the specified distance)

[0169] Figure 13 This is a diagram used to illustrate the specified distance according to the second and third embodiments.

[0170] For example, in Figure 11B In step S1117, the estimation unit 611 of the output unit 603 extracts a predetermined component within a predetermined distance from all Freon sensors that have detected refrigerant leakage. This predetermined distance serves as an initial value, and for example, it can be the detection range of the Freon sensor predicted based on past data, or the detection range of the Freon sensor predicted through simulation. Furthermore, this predetermined distance can be dynamically changed as needed.

[0171] For example, in Figure 13 , assume that two sensors 112x and 112y are Freon sensors, and there are two components 1301 and 1302 that are candidates for the refrigerant leakage position between the two sensors 112x and 112y. Also assume that refrigerant leakage occurs in component 1301 among the two components 1301 and 1302, the distance between component 1301 and sensor 112x is d1, and the distance between component 1301 and sensor 112y is d2 (d1 < d2). Further, the components 1301 and 1302 are included in the detection range 1303 within a specified distance (initial value) from sensor 112x and the detection range 1304 within a specified distance (initial value) from sensor 112y.

[0172] In this case, there is a time difference between the time (the first time) until the refrigerant leaked from component 1301 diffuses and is detected by sensor 112x and the time (the second time) until it is detected by sensor 112y. The estimation unit 611 can also use this time difference to change the specified distance for extracting candidates for the refrigerant leakage location and limit the detection range 1305 for extracting candidates for the refrigerant leakage location.

[0173] For example, the estimation unit 611 can also assume that the distance is proportional to the detection time, calculate the ratio of distance d1 to distance d2 based on the time difference between the first time and the second time, shorten the specified distance according to this ratio, and extract candidates for the refrigerant leakage location in a narrower detection range 1305. Thus, the estimation unit 611 can narrow down the candidates for the refrigerant leakage location to component 1301.

[0174] In addition, regarding the relationship between the distance and the detection time, for example, a function for calculating the distance can be generated based on the diffusion speed and time of the refrigerant, etc., or a learned prediction model, etc. can be used.

[0175] As another example, in Figure 12A at step S1207, the estimation unit 611 of the output unit 603 extracts specified components located within a specified distance from all the sound sensors that have detected an abnormal condition. This specified distance can also be dynamically changed as needed.

[0176] For example, in Figure 13In this design, two sensors 112x and 112y are sound sensors. Between the two sensors 112x and 112y are two constituent elements 1301 and 1302, which serve as candidate locations for malfunctions. Furthermore, assuming that an abnormal sound caused by a malfunction occurs in constituent element 1301, the distance between constituent element 1301 and sensor 112x is d1, and the distance between constituent element 1301 and sensor 112y is d2 (d1...). <d2)。

[0177] In this case, for abnormal sounds generated from constituent element 1301, there is a difference between the sound intensity detected by sensor 112x (first sound pressure) and the sound intensity detected by sensor 112y (second sound pressure). The estimation unit 611 can also use the difference between the first sound pressure and the second sound pressure to change the predetermined distance for extracting the candidate defective part, and limit the detection range 1305 for extracting the candidate defective part.

[0178] For example, the estimation unit 611 can also assume that the distance is proportional to the sound intensity (sound pressure), calculate the ratio of distance d1 to distance d2 based on the difference between the first and second sound pressure levels, and shorten the predetermined distance based on this ratio to extract potential defective locations within a narrower detection range 1305. Thus, the estimation unit 611 can narrow down the potential defective locations to component 1301. Furthermore, this method can also be applied when sensors 112x and 112y are vibration sensors.

[0179] Furthermore, regarding the relationship between distance and the magnitude of sound (or vibration), for example, a function that calculates distance based on the magnitude of sound (or vibration) can be generated, or a learned prediction model can be utilized.

[0180] [Fourth Implementation]

[0181] In the fourth embodiment, an example will be described in which the estimation unit 611 uses sensor information from environmental sensors, such as those that detect temperature and humidity, in addition to using sensor information from one or more sensors 112a, 112b, ... that detect defects, to improve the estimation accuracy of the candidate defect location.

[0182] Figure 14 This is a flowchart illustrating an example of presumed treatment of defective areas according to the fourth embodiment. Additionally, Figure 14 In the process shown, steps S1111-1114 and S1115-S1118 are similar to those in... Figure 11B The presumed treatment of the defective parts described in the second embodiment is the same as that described in the second embodiment. Therefore, the description here focuses on the differences from the second embodiment.

[0183] If a refrigerant leak is detected in step S1113, in step S1401, the estimation unit 611 of the output unit 603, for example, from... Figure 8A One or more environmental sensors 202a to 202d acquire sensor information, including temperature information, humidity information, etc. For example, the estimation unit 611 uses the acquisition unit 602 to acquire sensor information from one or more environmental sensors 202a to 202d. In addition, the processing in step S1401 can also be performed before step S1114.

[0184] In step S1402, the estimation unit 611 determines a predetermined distance from one or more sensors that have detected refrigerant leakage based on the acquired environmental information. For example, in... Figure 13 As explained, when two sensors 112x and 112y detect a refrigerant leak, the estimation unit 611 calculates the ratio of distance d1 to distance d2, and determines, for example, a specified distance for sensor 112x based on this ratio.

[0185] At this point, as described above, the estimation unit 611 can also use a function that calculates distance based on the refrigerant's diffusion rate and time, or a learned prediction model. Here, since the refrigerant's diffusion rate depends on temperature, the diffusion rate can be determined, for example, by using the temperature obtained from an environmental sensor, thereby improving the accuracy of the distance calculation. Furthermore, for a learned prediction model, by inputting temperature information as one of the learning data into the learned prediction model, the accuracy of the distance prediction can also be improved.

[0186] In step S1115, the estimation unit 611 uses the predetermined distance determined in step S1402 to extract the connection of the refrigerant piping located within the predetermined distance from the obtained location information.

[0187] Through the above processing, the defect location estimation system 100 can improve the estimation accuracy of defect locations by using environmental information obtained from environmental sensors.

[0188] [Fifth Implementation]

[0189] In the fifth embodiment, an example will be described where the sensor 112 for detecting malfunctions is a camera.

[0190] Figure 15 This is a flowchart illustrating an example of the defect location estimation processing according to the fifth embodiment. Here, it is assumed that the sensor 112 for detecting defects is a camera such as a thermal imaging camera (hereinafter referred to as a thermal imager) that captures a temperature image representing the temperature of an object. A thermal imager is a device that images the infrared radiation from the object being measured, converts it into temperature, and visualizes the temperature distribution through color or the like.

[0191] In step S1501, the acquisition unit 602 of the output unit 603 acquires a temperature image from sensor information from multiple cameras. For example, as shown... Figure 16 As shown, the acquisition unit 602 acquires temperature images captured by cameras 1 and 2 installed in room 1610.

[0192] In step S1502, the acquisition unit 602 determines whether a defective condition is detected in each of the acquired temperature images. For example, if there is a region in the temperature image that represents a temperature higher than a threshold, the acquisition unit 602 determines that a defective condition has been detected.

[0193] In step S1503, when a temperature image indicating a defect is detected, the acquisition unit 602 transfers the processing to step S1504. On the other hand, if no temperature image indicating a defect is detected, the acquisition unit 602 returns the processing to step S1501.

[0194] After moving to step S1504, the estimation unit 611 of the output unit 603 obtains the position coordinates of the camera that captured the temperature image of the detected defect based on the sensor information obtained by the acquisition unit 602.

[0195] In step S1505, the estimation unit 611 calculates the coordinates of the defective area based on the obtained position coordinates and the camera's orientation. For example, as... Figure 16 As shown, cameras 1 and 2 are arranged such that multiple constituent elements 1 to 5 are contained within the field of view. Additionally, camera 1 is used to capture... Figure 16 The temperature image 1620 taken by camera 1 and the temperature image 1630 taken by camera 2 are shown.

[0196] In this case, such as Figure 16 As shown, the estimation unit 611, for example, estimates the direction 1611 of the region 1621 relative to the camera 1 based on the location of the region 1621 whose temperature is higher than the threshold value captured in the temperature image 1620 of the camera 1. Similarly, as Figure 16 As shown, the estimation unit 611 estimates the direction 1612 of region 1631 relative to camera 2, for example, based on the location of region 1631 where the temperature is higher than the threshold captured in the temperature image 1630 of camera 2. The estimation unit 611 calculates the coordinates of the intersection point of the direction 1611 of region 1621 relative to camera 1 and the direction 1612 of region 1631 relative to camera 2.

[0197] In step S1506, the estimation unit 611 extracts the constituent elements located in the calculated coordinates. For example, in Figure 16In the example, since there is a constituent element 5 at the intersection of the direction 1611 of region 1621 relative to camera 1 and the direction 1612 of region 1631 relative to camera 2, the estimation unit 611 extracts the constituent element 5 located at the calculated coordinates.

[0198] In step S1507, the output unit 603 generates and outputs defect information indicating that the extracted constituent elements are defective parts or candidate defective parts.

[0199] (Modified Example)

[0200] In the above process, if either camera 1 or camera 2 fails to detect a defect, it is difficult to determine the constituent elements that could be the defective part.

[0201] Therefore, cameras 1 and 2 can also be used that not only capture temperature images but also capture depth images representing distances from the camera. Thus, even with just one camera, it is possible to determine the direction and distance of areas where the temperature is higher than a threshold, thereby identifying potential components that could become defective areas.

[0202] Furthermore, a technique for estimating depth from ordinary captured images (such as RGB images) using AI (artificial intelligence) technology has been developed. If such a technique is employed, cameras capable of capturing temperature images and ordinary photographic images can be used as both camera 1 and camera 2. For example, when a defect is detected only by camera 1, the estimation unit 611 can convert the ordinary captured image taken by camera 1 into a depth image using a learned prediction model or a cloud service that provides depth estimation based on ordinary captured images.

[0203] Therefore, the defect location estimation system 100 can estimate the defect location based on images captured by one or more cameras and, for example... Figure 16 The drawing information 1600 shown is used to estimate the location of the defect or a candidate location of the defect, and the defect information is output.

[0204] <Application Example>

[0205] The above embodiments are examples, and various modifications and applications are possible.

[0206] Figure 17 This diagram illustrates an application example of a defect location estimation system based on one implementation method. For example... Figure 17 As shown, the defect location estimation system 100 according to this disclosure can also be applied to a machine room 1700, etc., which is equipped with multiple coolers 1701a to 1701h. Figure 17In the example, multiple coolers 1701a to 1701d are connected to water piping 1703a via pump 1702. Similarly, multiple coolers 1701a to 1701d are connected to water piping 1703b via pump 1702.

[0207] Thus, in the machine room 1700 equipped with water pipes 1703a and 1703b, leakage sensors 1706a and 1706b can be used as sensors to detect malfunctions. For example, in Figure 17 In the event of a leak, the leaked water flows to a drainage channel located at a lower position.

[0208] In this situation, when a leak is detected only by the leak sensor 1706a, the estimation unit 611 can, for example, consider coolers 1701a-1701d and the connection between coolers 1701a-1701d and water pipe 1703a as potential leak locations. Similarly, when a leak is detected only by the leak sensor 1706b, the estimation unit 611 can, for example, consider coolers 1701e-1701h and the connection between coolers 1701e-1701h and water pipe 1703b as potential leak locations. Furthermore, the estimation unit 611 can also estimate potential locations of malfunctions based on sensor information obtained from multiple leak sensors and the leak detection time of each leak sensor.

[0209] Alternatively, the defect location estimation system 100 can also use sound sensors (or vibration sensors) 1705a-1705d located near the multiple coolers 1701a-1701h to estimate the candidate coolers that have experienced a defect, applying the third embodiment. Thus, the defect location estimation system 100 can use fewer sound sensors (or vibration sensors) 1705a-1705d than the multiple coolers 1701a-1701h to provide defect information indicating the candidate coolers that have experienced a defect.

[0210] For example, it is difficult to detect malfunctions such as cooler overheating using only sound sensors (or vibration sensors) 1705a to 1705d. Therefore, the malfunction location estimation system 100 may also use cameras 1704a and 1704b, for example, and apply the fourth embodiment to provide malfunction information such as that of a candidate cooler where malfunctions such as cooler overheating have occurred.

[0211] In this way, the defect location estimation system 100 can improve the estimation accuracy of defect locations or candidate defect locations by combining sensor information from multiple sensors of the same or different types.

[0212] <Other application examples>

[0213] (Application Example 1)

[0214] The defect location estimation system 100 can also obtain information such as temperature difference, time difference of temperature change, or time change of temperature difference from the sensor information of the two temperature sensors, and use the obtained information to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can limit the plane where the defect occurred or the range where the defect occurred based on the set location information.

[0215] (Application Example 2)

[0216] The defect location estimation system 100 can also obtain information such as temperature difference, time difference of temperature change, or time change of temperature difference from sensor information of three or more temperature sensors, and use the obtained information to estimate the direction of the location where the defect occurred. Therefore, the defect location estimation system 100 can further limit the location where the defect occurred based on the installation location information. For example, the defect location estimation system 100 can limit the range of defect occurrence not only in the horizontal direction, but also in three dimensions, including pipe connections installed in the vertical direction.

[0217] (Application Example 3)

[0218] The defect location estimation system 100 can also obtain information such as the gas concentration difference, the time difference of concentration change, or the time change of concentration difference from the sensor information of the two gas sensors, and use the obtained information to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can limit the plane where the defect occurred or the range where the defect occurred based on the set location information.

[0219] (Application Example 4)

[0220] The malfunction location estimation system 100 can also obtain information such as gas concentration difference, time difference of concentration change, or time change of concentration difference from sensor information of three or more gas sensors, and use the obtained information to estimate the direction of the location where the malfunction occurred. Therefore, the malfunction location estimation system 100 can further limit the location where the malfunction occurred based on the installation location information. For example, the malfunction location estimation system 100 can define the range of the malfunction in three dimensions.

[0221] (Application Example 5)

[0222] The defect location estimation system 100 can also obtain the sound intensity difference based on the sensor information from two sound sensors, and use the obtained sound intensity difference to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can define the plane where the defect occurred or the range of the defect based on the set location information.

[0223] (Application Example 6)

[0224] The defect location estimation system 100 can also obtain the sound intensity difference based on sensor information from three or more sound sensors, and use the obtained sound intensity difference to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can further limit the location where the defect has occurred based on the set location information. For example, the defect location estimation system 100 can limit the range of the defect in three dimensions.

[0225] (Application Example 7)

[0226] The defect location estimation system 100 can also obtain the vibration intensity based on the sensor information from the two vibration sensors, and use the obtained vibration intensity to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can define the plane where the defect occurred, or the range of the defect, based on the set location information.

[0227] (Application Example 8)

[0228] The defect location estimation system 100 can also obtain the vibration intensity based on sensor information from three or more vibration sensors, and use the obtained vibration intensity to estimate the direction of the defect location. Therefore, the defect location estimation system 100 can further limit the location of the defect based on the set location information. For example, the defect location estimation system 100 can define the range of the defect location in three dimensions.

[0229] (Application Example 9)

[0230] The defect location estimation system 100 can also use images captured by two cameras and setup location information to determine the location where the defect has occurred. For example, the defect location estimation system 100 can calculate the distance to the target device based on the size of the target device (scale shown in the image) or depth estimation technology, thereby determining the target device where the defect has occurred based on the setup location information.

[0231] (Application Example 10)

[0232] The defect location estimation system 100 can also use images captured by two thermal imagers and setup location information to determine the occurrence of a defect or the location of the defect. For example, the defect location estimation system 100 can determine that a defect has occurred by detecting changes in surface temperature, color, or vibration in images captured by the thermal imagers, and determine the location of the defect based on the setup location information.

[0233] (Application Example 11)

[0234] The fault location estimation system 100 can also obtain information on temperature changes over time and gas concentration changes based on sensor information from the temperature sensor and the gas sensor, and use the obtained information to estimate the severity of the leak location (leakage amount, etc.). For example, since the propagation of temperature (heat) takes time, the fault location estimation system 100 can also determine that there is a slow leak if gas is detected but there is no temperature change.

[0235] (Application Example 12)

[0236] The fault location estimation system 100 can also estimate the severity of the leak location (leakage amount, etc.) based on sensor information from the temperature sensor and the sound sensor, obtaining the time change of temperature and the intensity of sound. For example, the fault location estimation system 100 can also determine that there is a slow leak if an abnormal sound is detected but there is no temperature change.

[0237] (Application Example 13)

[0238] The malfunction location estimation system 100 can also estimate the location of the malfunction and the severity of the leak (leakage amount, etc.) based on sensor information from the gas sensor and the sound sensor. For example, the malfunction location estimation system 100 can estimate the location of the malfunction based on changes in gas concentration and installation location information. Furthermore, since sound travels faster than gas diffuses, the malfunction location estimation system 100 can also determine whether it is a slow leak based on the time delay between the time of detecting an abnormal sound and the time of detecting a gas leak.

[0239] (Application Example 14)

[0240] The malfunction location estimation system 100 can also estimate the location of the malfunction and the severity of the leak (leakage amount, etc.) based on sensor information from the gas sensor and vibration sensor. For example, the malfunction location estimation system 100 can estimate the location of the malfunction based on changes in gas concentration and installation location information. Furthermore, since vibration propagates faster than gas diffusion, the malfunction location estimation system 100 can also determine whether it is a slow leak based on the time delay between the time of vibration detection and the time of gas leak detection.

[0241] (Application Example 15)

[0242] The fault location estimation system 100 can also estimate the direction of the fault location based on the sensor information from the two temperature sensors, similar to Application Example 1, and determine refrigerant leakage based on the sensor information from the gas sensor. Therefore, for example, although false detections may occur only due to temperature changes caused by external factors (such as the presence of a heat source), false detections can be prevented by using a gas sensor.

[0243] (Application Example 16)

[0244] The fault location estimation system 100 can also estimate the direction of the fault location based on the sensor information from the two temperature sensors, similar to Application Example 1, and further limit the location of the fault location based on the sensor information from the sound sensor. For example, the fault location estimation system 100 can also determine whether the fault location is equipment or piping, etc., based on the frequency pattern of the sound obtained by the sound sensor.

[0245] (Application Example 17)

[0246] The defect location estimation system 100 can also estimate the direction of the defect location based on the sensor information from the two temperature sensors, similar to Application Example 1, and further limit the location of the defect based on the sensor information from the vibration sensor. For example, the defect location estimation system 100 can also obtain the vibration frequency from the sensor information from the vibration sensor, and determine whether the defect location is equipment or piping, etc., based on the vibration frequency pattern.

[0247] (Application Example 18)

[0248] The defect location estimation system 100 can also estimate the direction of the defect location based on sensor information from two temperature sensors, similar to Application Example 1, and determine the defect location by analyzing images captured by the camera. Therefore, for example, as in Application Example 9, defects can be detected more quickly compared to determining the defect location solely based on images captured by the camera. Furthermore, this application example can also be applied to determine defects in blind spots of the camera.

[0249] (Application Example 19)

[0250] The defect location estimation system 100 can also estimate the direction of the defect location based on the sensor information from the two gas sensors, similar to Application Example 3, and further define the defect location based on the sound intensity and installation location information obtained from the sound sensor. Therefore, the defect location estimation system 100 can further improve the estimation accuracy of the defect location.

[0251] (Application Example 20)

[0252] The defect location estimation system 100 can also estimate the direction of the defect location based on the sensor information from the two gas sensors, similar to Application Example 3, and further define the defect location based on the vibration intensity and installation position information obtained from the vibration sensor. Therefore, the defect location estimation system 100 can further improve the estimation accuracy of the defect location.

[0253] (Application Example 21)

[0254] The defect location estimation system 100 can also estimate the direction of the defect location based on sensor information from two gas sensors, similar to Application Example 3, and determine the defect location by analyzing images captured by the camera. Therefore, for example, as in Application Example 9, defects can be detected more quickly compared to determining the defect location solely based on images captured by the camera. Furthermore, this application example can also be applied to determine defects in blind spots of the camera.

[0255] (Application Example 22)

[0256] The defect location estimation system 100 can also estimate the direction of the defect location based on the sensor information from the two sound sensors, similar to Application Example 5, and further define the defect location based on the vibration intensity and installation position information obtained from the vibration sensor. Therefore, the defect location estimation system 100 can further improve the estimation accuracy of the defect location.

[0257] (Application Example 23)

[0258] The defect location estimation system 100 can also estimate the direction of the defect location based on sensor information from the two sound sensors, similar to Application Example 5, and determine the location of the defect by analyzing images captured by the camera. Therefore, compared to determining the defect location solely based on images captured by the camera, as in Application Example 9, the defect location estimation system 100 can quickly detect defects. Furthermore, this application example can also be applied to determine defects in blind spots of the camera.

[0259] (Application Example 24)

[0260] The defect location estimation system 100 can also estimate the direction of the defect location based on the sensor information from the two vibration sensors, similar to Application Example 7, and determine the location of the defect by analyzing images captured by the camera. Therefore, compared to determining the defect location solely based on images captured by the camera, as in Application Example 9, the defect location estimation system 100 can quickly detect defects. Furthermore, this application example can also be applied to determine defect locations in blind spots of the camera.

[0261] The above describes the implementation methods, but it is understood that various changes in form and detail may be made without departing from the spirit and scope of the claims.

[0262] This application claims priority to basic application No. 2021-001922 filed with the Japan Patent Office on January 8, 2021, the entire contents of which are incorporated herein by reference.

[0263] [Symbol Explanation]

[0264] 100 Defect Location Estimation System

[0265] 110 Air Conditioning System (An Example of a Refrigeration and Air Conditioning System)

[0266] 111 Air Conditioning Equipment

[0267] 112 Sensors

[0268] 113 Controller (Control Unit)

[0269] 120 Management Server

[0270] 203 Piping

[0271] Connection parts of piping 204a~204h

[0272] Pipelines 211a~211d

[0273] 300, 400, 1000 adverse status information

[0274] 500 computers

[0275] Sensor information for 701, 703, and 704

[0276] 801 Drawing Information (An Example of Setting Location Information)

[0277] 802 Device Coordinate Information (An Example of Setting Location Information)

[0278] 1704a and 1704b cameras

[0279] 1706a and 1706b water leakage sensors

Claims

1. A system for estimating the location of a defect, comprising: A first sensor is used to detect adverse conditions occurring in the refrigeration and air conditioning system. A second sensor is used to detect malfunctions occurring in the refrigeration and air conditioning system. as well as The control unit controls the refrigeration and air conditioning system. The control unit, The system includes location information indicating the locations of specified components in the refrigeration and air conditioning system that are present in greater numbers than the first sensor and where the adverse condition may have occurred. If the first sensor and the second sensor detect the defective condition, using the sensor information of the first sensor and the second sensor, as well as the setting location information, the specified constituent element located within a specified distance from the first sensor and the second sensor is designated as a candidate for the location where the defective condition has occurred. Based on the time difference between the first time the first sensor detects the adverse condition and the second time the second sensor detects the adverse condition, the predetermined distance is changed, and Output defect information indicating the location where the defect occurred, a candidate location for the defect, or the extent of the defect.

2. The defect location estimation system according to claim 1, wherein, The adverse condition information includes information about the constituent elements that may have experienced the adverse condition, from among the one or more constituent elements.

3. The defect location estimation system according to claim 1 or 2, wherein, The sensor information includes information related to the location where the sensor is set.

4. The defect location estimation system according to claim 1 or 2, wherein, The control unit also uses sensor information obtained from one or more sensors that acquire environmental information to output the adverse condition information.

5. The defect location estimation system according to claim 1 or 2, wherein, The control unit uses sensor information from two or more sensors that detect the defective condition and the setting location information to output the defective condition information.

6. The defect location estimation system according to claim 5, wherein, The control unit uses sensor information from the two or more sensors to define the location, alternatives, or range where the malfunction occurs.

7. The defect location estimation system according to claim 5, wherein, The control unit improves the accuracy of the adverse condition information by combining sensor information from multiple sensors of the same or different types.

8. The system for estimating the location of defects according to any one of claims 1, 2, 6, and 7, wherein, The location information includes information indicating the location of the connection points of the piping that connects to the equipment included in the refrigeration and air conditioning system. The control unit uses sensor information from one or more refrigerant sensors or gas sensors and the setting location information to estimate potential refrigerant leakage points.

9. The system for estimating the location of defects according to any one of claims 1, 2, 6, and 7, wherein, The location information includes information indicating the location of the equipment included in the refrigeration and air conditioning system and the connection points of the piping or pipes connected to the equipment. The control unit estimates a candidate location where the malfunction occurs based on sensor information obtained from multiple sound sensors, the volume or detection time of the sound from each sound sensor, and the location information.

10. The system for estimating the location of defects according to any one of claims 1, 2, 6, and 7, wherein, The location information includes information indicating the location of the equipment included in the refrigeration and air conditioning system. The control unit estimates a candidate location where the adverse condition occurs based on sensor information obtained from multiple vibration sensors that detect vibration, the magnitude of vibration or detection time of each vibration sensor, and the location information.

11. The system for estimating the location of defects according to any one of claims 1, 2, 6, and 7, wherein, The location information includes information indicating the connection points of the piping connected to the equipment included in the refrigeration and air conditioning system. The control unit estimates a candidate location where the malfunction is occurring based on sensor information obtained from multiple leak sensors and the leak detection time of each leak sensor.

12. The system for estimating the location of defects according to any one of claims 1, 2, and 6, wherein, The location information includes drawing information indicating the configuration of the constituent elements. The sensor includes one or more cameras that capture images of the constituent elements. The control unit estimates the candidate location where the defect occurs based on images captured by one or more cameras and the drawing information.

13. A method for estimating the location of an adverse condition, wherein, include: The refrigeration and air conditioning system is controlled by a computer. as well as Using sensor information from both a first sensor and a second sensor that detect malfunctions occurring in the refrigeration and air conditioning system, along with location information, the system outputs malfunction information indicating the location of the malfunction, a candidate location for the malfunction, or the extent of the malfunction. The location information indicates the locations of specified components in the refrigeration and air conditioning system that are more numerous than the first sensor and where the aforementioned adverse condition may have occurred. When the first sensor and the second sensor detect the defective condition, using the sensor information of the first sensor and the second sensor, as well as the setting position information, the specified constituent element located within a specified distance from the first sensor and the second sensor is designated as a candidate for the location where the defective condition has occurred. The specified distance is adjusted based on the time difference between the first time the first sensor detects the adverse condition and the second time the second sensor detects the adverse condition.

14. A program that enables a computer controlling a refrigeration and air conditioning system to: Using sensor information from both a first sensor and a second sensor that detect malfunctions occurring in the refrigeration and air conditioning system, along with location information, the system outputs malfunction information indicating the location of the malfunction, a candidate location for the malfunction, or the extent of the malfunction. The location information indicates the locations of specified components in the refrigeration and air conditioning system that are more numerous than the first sensor and where the aforementioned adverse condition may have occurred. When the first sensor and the second sensor detect the defective condition, using the sensor information of the first sensor and the second sensor, as well as the setting position information, the specified constituent element located within a specified distance from the first sensor and the second sensor is designated as a candidate for the location where the defective condition has occurred. The specified distance is adjusted based on the time difference between the first time the first sensor detects the adverse condition and the second time the second sensor detects the adverse condition.

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