Cloud server and control method thereof

Abstract

The embodiment of the invention provides a cloud server and a control method thereof, relates to the technical field of cloud services, and is used for improving the accuracy of air conditioner fault detection. The cloud server comprises a communicator used for establishing communication connection with the air conditioner; the air conditioner comprises at least one indoor unit and at least one outdoor unit. The processor is configured to obtain operation data of the air conditioner; the operation data of the at least one indoor unit and the operation data of the at least one outdoor unit are combined, and first combined data of the indoor unit dimension and second combined data of the air conditioner dimension are obtained; inputting the first combined data into a first fault detection model to obtain first fault information of the air conditioner in the indoor unit dimension, and inputting the second combined data into a second fault detection model to obtain second fault information of the air conditioner in the air conditioner dimension; and determining a fault detection result of the air conditioner according to the first fault information and the second fault information.

Description

Technical Field

[0001] This application relates to the technical field of air conditioners, and particularly to a cloud server and its control method. Background Art

[0002] At present, air conditioners have become essential household appliances in family life. As the utilization rate of air conditioners gets higher and higher, the probability of air conditioner failures also increases.

[0003] When detecting faults in the indoor unit of an air conditioner, a fault detection model equivalent to the indoor unit is usually used for diagnosis. Similarly, a fault detection model equivalent to the outdoor unit is used to diagnose faults in the outdoor unit of the air conditioner. However, since modern air conditioning systems usually have multiple indoor units and multiple outdoor units, the complexity of the system and the mutual influence between components make traditional fault diagnosis methods difficult, and it is impossible to accurately determine the specific location and type of air conditioner failures, thus affecting the accuracy of air conditioner fault detection.

[0004] Therefore, how to improve the accuracy of air conditioner fault detection has become an urgent technical problem to be solved. Summary of the Invention

[0005] This application provides a cloud server and its control method for improving the accuracy of air conditioner fault detection.

[0006] To achieve the above object, this application adopts the following technical solutions.

[0007] In a first aspect, an embodiment of this application provides a cloud server, which includes: a communicator for establishing a communication connection with an air conditioner; the air conditioner includes at least one indoor unit and at least one outdoor unit; a processor configured to: obtain the operation data of the air conditioner; wherein, the operation data of the air conditioner includes the operation data of at least one indoor unit and the operation data of at least one outdoor unit; combine the operation data of at least one indoor unit with the operation data of at least one outdoor unit to obtain first combined data in terms of indoor unit dimension and second combined data in terms of air conditioner dimension; input the first combined data into a first fault detection model to obtain first fault information of the air conditioner in terms of indoor unit dimension, and input the second combined data into a second fault detection model to obtain second fault information of the air conditioner in terms of air conditioner dimension; determine the fault detection result of the air conditioner according to the first fault information and the second fault information.

[0008] The technical solutions provided by the embodiments of the present application at least bring the following beneficial effects: The embodiments of the present application provide a cloud server, which can divide the operation data of the air conditioner into combined data of different dimensions, such as the first combined data in the indoor unit dimension and the second combined data in the air conditioner dimension, so as to detect the faults of the air conditioner more comprehensively and accurately from different dimensions. For example, the first combined data can be input into the first fault detection model for detecting the faults of the air conditioner in the indoor unit dimension to achieve accurate detection of the indoor unit faults. The second combined data can also be input to detect the faults of the air conditioner in the overall dimension of the air conditioner to improve the accurate detection of the overall faults of the air conditioner.

[0009] Furthermore, the cloud server can obtain the target detection result of the air conditioner based on the first fault information and the second fault information. In this way, this method considers the fault problems of the air conditioner from both the indoor unit dimension and the overall dimension of the air conditioner, can more accurately locate and identify the fault source, and thus can improve the accuracy of fault detection.

[0010] In some embodiments, the processor is configured to combine the operation data of at least one indoor unit with the operation data of at least one outdoor unit to obtain the first combined data in the indoor unit dimension and the second combined data in the air conditioner dimension, and is specifically configured to: combine the operation data of each indoor unit in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit respectively to obtain the first combined data; the first combined data includes the combined data corresponding to each of at least one indoor unit; combine the operation data of all indoor units in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit to obtain the second combined data.

[0011] In some embodiments, before the processor is configured to combine the operation data of at least one indoor unit with the operation data of at least one outdoor unit, it is further configured to: process the operation data of the air conditioner, extract the non-steady-state operation data in the operation data of the air conditioner; remove the non-steady-state operation data.

[0012] In some embodiments, the processor is configured to process the operation data of the air conditioner and extract the non-steady-state operation data in the operation data of the air conditioner, and is specifically configured to: periodically detect the operation data of the air conditioner at a preset time length; wherein, one detection period includes the operation data within the preset time length; for each detection period, when the standard deviation of the operation data within the detection period is within the preset range, determine the operation data within the detection period as non-steady-state operation data.

[0013] In some embodiments, before the processor is configured to combine the operation data of at least one indoor unit with the operation data of at least one outdoor unit, the processor is further configured to process the operation data of the air conditioner in a target data type; the target data type is a detectable data type of a first fault detection model and / or a second fault detection model.

[0014] In some embodiments, the processor, which is configured to process the operation data of the air conditioner in a target data type, is specifically configured to: when the operation data of the air conditioner is first data, perform weighted averaging on the operation data of the air conditioner according to the weight value corresponding to the operation data of the air conditioner, so that the target data type matches the detectable data type; wherein, the weight value is used to represent the on / off state of the air conditioner, and the first data includes temperature data and pressure data; when the operation data of the air conditioner is second data, add up the operation data of the air conditioner, so that the target data type matches the detectable data type; wherein, the second data includes other data except temperature data and pressure data.

[0015] In a second aspect, an embodiment of the present application provides a control method for a cloud server. The method includes: obtaining the operation data of the air conditioner; wherein, the operation data of the air conditioner includes the operation data of at least one indoor unit and the operation data of at least one outdoor unit; combining the operation data of at least one indoor unit with the operation data of at least one outdoor unit to obtain first combined data in the indoor unit dimension and second combined data in the air conditioner dimension; inputting the first combined data into a first fault detection model to obtain first fault information of the air conditioner in the indoor unit dimension, and inputting the second combined data into a second fault detection model to obtain second fault information of the air conditioner in the air conditioner dimension; determining a fault detection result of the air conditioner according to the first fault information and the second fault information.

[0016] In some embodiments, before combining the operation data of at least one indoor unit with the operation data of at least one outdoor unit to obtain first combined data in the indoor unit dimension and second combined data in the air conditioner dimension, the method further includes: respectively combining the operation data of each indoor unit in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit to obtain first combined data; the first combined data includes combined data corresponding to each of at least one indoor unit; combining the operation data of all indoor units in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit to obtain second combined data.

[0017] In some embodiments, before combining the operation data of at least one indoor unit with the operation data of at least one outdoor unit, the method further includes: processing the operation data of the air conditioner, extracting non-steady-state operation data from the operation data of the air conditioner; removing the non-steady-state operation data.

[0018] In some embodiments, before combining the operation data of at least one indoor unit with the operation data of at least one outdoor unit, the method further includes: processing the operation data of the air conditioner in a target data type; the target data type is a detectable data type of the first fault detection model and / or the second fault detection model.

[0019] In some embodiments, processing the operation data of the air conditioner in a target data type includes: when the operation data of the air conditioner is first data, performing weighted averaging on the operation data of the air conditioner according to the weight value corresponding to the operation data of the air conditioner, so that the target data type matches the detectable data type; wherein, the weight value is used to represent the on state of the air conditioner, and the first data includes temperature data and pressure data; when the operation data of the air conditioner is second data, adding the operation data of the air conditioner, so that the target data type matches the detectable data type; wherein, the second data includes other data except temperature data and pressure data.

[0020] In a third aspect, an embodiment of the present application provides a controller, including: one or more processors; one or more memories; wherein, the one or more memories are used to store computer program code, and the computer program code includes computer instructions. When the one or more processors execute the computer instructions, the controller executes any one of the control methods of the cloud server provided in the second aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium includes computer instructions, and when the computer instructions run on a computer, the computer is enabled to execute any one of the control methods of the cloud server provided in the second aspect.

[0022] In a fifth aspect, an embodiment of the present invention provides a computer program product, which can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program product can implement any one of the control methods of the cloud server provided in the second aspect.

[0023] It should be noted that the above computer instructions can be stored in whole or in part on a computer-readable storage medium. Among them, the computer-readable storage medium can be packaged together with the processor of the controller or separately packaged from the processor of the controller. The present application does not make any limitation in this regard.

[0024] For the beneficial effects described in the second to fifth aspects of the present application, reference can be made to the analysis of the beneficial effects in the first aspect, and details are not described herein again. Description of the Drawings

[0025] The accompanying drawings are used to provide a further understanding of the technical solution of the present invention, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present invention, and do not constitute a limitation to the technical solution of the present invention.

[0026] Figure 1 It is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0027] Figure 2 It is another schematic diagram of an application scenario provided by an embodiment of the present application;

[0028] Figure 3 It is a schematic diagram of the composition of an air conditioner provided by an embodiment of the present application;

[0029] Figure 4 It is a hardware configuration block diagram of a cloud server provided by an embodiment of the present application;

[0030] Figure 5 It is a flowchart of a control method for a cloud server provided by an embodiment of the present application;

[0031] Figure 6 It is a combined schematic diagram of a first combined data provided by an embodiment of the present application;

[0032] Figure 7 It is a combined schematic diagram of a second combined data provided by an embodiment of the present application;

[0033] Figure 8 It is a flowchart of another control method for a cloud server provided by an embodiment of the present application;

[0034] Figure 9 It is a flowchart of another control method for a cloud server provided by an embodiment of the present application;

[0035] Figure 10 It is a flowchart of another control method for a cloud server provided by an embodiment of the present application;

[0036] Figure 11 It is a flowchart of another control method for a cloud server provided by an embodiment of the present application;

[0037] Figure 12 It is a flowchart of another control method for a cloud server provided by an embodiment of the present application. Detailed implementation manners

[0038] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0039] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0040] The terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0041] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances. In addition, when describing pipelines, the terms "connected" and "connected" used in the present application have the meaning of conducting. The specific meaning needs to be understood in combination with the context.

[0042] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0043] To improve the accuracy of air conditioner fault detection, an embodiment of the present application provides a control method for a cloud server. By dividing the operation data of the air conditioner into combined data of different dimensions, such as the first combined data in the indoor unit dimension and the second combined data in the air conditioner dimension, the faults of the air conditioner can be detected more comprehensively and accurately from different dimensions. For example, the first combined data can be input into the first fault detection model for detecting the faults of the air conditioner in the indoor unit dimension to achieve accurate detection of indoor unit faults. The second combined data can also be input to detect the faults of the air conditioner in the overall air conditioner dimension to improve the accurate detection of the overall faults of the air conditioner.

[0044] Furthermore, the cloud server can obtain the target detection result of the air conditioner based on the first fault information and the second fault information. In this way, this method considers the fault problems of the air conditioner from both the indoor unit dimension and the overall air conditioner dimension, can more accurately locate and identify the fault source, and thus can improve the accuracy of fault detection.

[0045] Figure 1 This is a schematic diagram of an application scenario provided by the present application according to an exemplary embodiment. As Figure 1 shown, this application scenario may include an air conditioner 101 and a cloud server 102.

[0046] Among them, the air conditioner 101 and the cloud server 102 can be communicatively connected.

[0047] In some embodiments, the number of air conditioners 101 can be one or multiple, and the present application does not impose special restrictions on the number of air conditioners 101 in this application scenario.

[0048] In some embodiments, the air conditioner 101 is a device for adjusting and controlling parameters such as the temperature, humidity, and flow rate of the indoor air in a building or structure. The air conditioner 101 can be an air conditioner with one indoor unit and one outdoor unit, or an air conditioner with multiple indoor units and multiple outdoor units. The present application does not impose special restrictions on the specific form of the air conditioner 101.

[0049] In some embodiments, the cloud server 102 can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data servers. The present application does not impose special restrictions on the specific form of the cloud server 102.

[0050] In some embodiments, as Figure 2 shown, the cloud server 102 can obtain the operation data of the air conditioner 101, such as temperature data, pressure data, valve opening data, current data, frequency data, air volume level data, etc.

[0051] In some embodiments, the cloud server 102 may store the operation data of the air conditioner 101 collected in real time in a database.

[0052] In some embodiments, the cloud server 102 may obtain multiple sets of operation data of the air conditioner 101 from the database and perform data processing operations on the operation data of the air conditioner 101.

[0053] In some embodiments, as Figure 2 shown, this application scenario may further include a client 201. Among them, the cloud server 102 and the client 201 may be communicatively connected.

[0054] In some embodiments, the client (which may also be referred to as the user side) 203 refers to a program that provides local services for clients corresponding to the server. The client is usually installed on a terminal device, such as a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, and a cellular phone, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device, etc.

[0055] In some embodiments, after determining that the air conditioner 101 has a fault, the cloud server 102 may send the fault result to the client 201 so that the client 201 visualizes the fault result to remind the user that the air conditioner 101 has a fault.

[0056] Figure 3 This is a schematic diagram of the composition of an air conditioner provided by an embodiment of the present application. As Figure 3 shown, the air conditioner 101 includes an indoor unit 301 and an outdoor unit 302.

[0057] In some embodiments, the number of indoor units 301 may be one or multiple, and the number of outdoor units 301 may be one or multiple. The present application does not impose special restrictions on the number of indoor units 301 and outdoor units 302.

[0058] Among them, taking the indoor unit 301 as an example of an indoor hanging unit, the indoor hanging unit is usually installed on an indoor wall surface, etc. Again, for example, an indoor cabinet unit is also a form of the indoor unit.

[0059] The outdoor unit 302 is usually set outdoors and is used for heat exchange in the indoor environment. In addition, in Figure 2In the illustration, since the outdoor unit 302 is located outdoors on the opposite side of the wall surface from the indoor unit 301, the outdoor unit 302 is represented by a dashed line.

[0060] Figure 4 This is a schematic diagram of the hardware structure of a cloud server provided by an embodiment of the present application. As Figure 4 shown, the cloud server 102 includes a processor 401, a memory 402, and a communicator 403.

[0061] The processor 401 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present disclosure. For example: one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0062] In some embodiments, the memory 402 can be used to store software programs and data, such as the operating data of the air conditioner 101. The processor 401 executes various functions and data processing of the cloud server 102 by running the software programs or data stored in the memory 402. The memory 402 can include high-speed random access memory, and can also include non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. The memory 402 stores an operating system that enables the cloud server 102 to run. In the present application, the memory 402 can store the operating system and various application programs, and can also store the code for executing the control method of the cloud server provided by the embodiments of the present application.

[0063] In some embodiments, the communicator 403 is used to establish a communication connection with other network entities, such as establishing a communication connection with the air conditioner 101 and the client 201. The communicator 403 can include a radio frequency (RF) module, a cellular module, a wireless fidelity (WIFI) module, and a GPS module, etc. Taking the RF module as an example, the RF module can be used for signal reception and transmission. In particular, the received information is sent to the processor 401 for processing; in addition, the signal generated by the processor 401 is sent out. Usually, the RF circuit can include, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA), a duplexer, etc.

[0064] Those skilled in the art can understand that Figure 4 the structure shown in Figure 4 does not constitute a limitation on the cloud server. The cloud server may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0065] The following specifically introduces the embodiments provided in the present application in conjunction with the accompanying drawings of the specification.

[0066] As Figure 5 shown, the embodiments of the present application provide a control method for a cloud server, and the method includes the following steps:

[0067] S101. The cloud server acquires the operation data of the air conditioner.

[0068] Among them, the operation data of the air conditioner includes the operation data of at least one indoor unit and the operation data of at least one outdoor unit.

[0069] In some embodiments, the cloud server can collect the operation data of the air conditioner in real time, and after collecting the operation data of the air conditioner, store the collected operation data of the air conditioner in a database, so that when the cloud server performs fault detection based on the operation data of the air conditioner, it can conveniently obtain the operation data of the air conditioner from the database.

[0070] It can be understood that storing the operation data in the database can achieve centralized management and storage, facilitating access, query, and analysis of the operation data. In addition, the database provides the characteristic of persistent storage, that is, the operation data will not be lost due to the restart or power failure of the cloud server after being stored, which helps with work such as fault detection of the air conditioner.

[0071] In some embodiments, the operation data of the air conditioner (that is, the operation data of each indoor unit in at least one indoor unit, or the operation data of each outdoor unit in at least one outdoor unit) may include temperature data, pressure data, valve opening data, frequency data, air volume level data, current data, etc.

[0072] Among them, the temperature data refers to the temperature data measured during the operation of the air conditioner, such as indoor temperature, supply air temperature, etc. Abnormal temperature data may be caused by air conditioner faults or other problems.

[0073] The pressure data is a series of static and dynamic pressures formed during the operation of the air conditioner. For example, condensation pressure, evaporation pressure, exhaust pressure, suction pressure, etc. Abnormal pressure data may indicate that there are problems of too high or too low pressure in the air conditioner, which may be caused by refrigerant leakage, valve failure, or other system problems.

[0074] The valve opening data refers to the opening of the valve that regulates the refrigerant flow in the air conditioner, such as the opening of the electronic expansion valve in the indoor unit and the opening of the electronic expansion valve in the outdoor unit. By monitoring the valve opening data, the refrigerant flow situation of the air conditioner under different working conditions can be understood, which helps to judge whether the valve is working properly. Abnormal valve opening values may indicate problems such as blockage, damage or control signal issues of the valve, thus affecting the cooling or heating effect of the air conditioner.

[0075] The frequency data is the operating frequency of components such as the compressor and the fan in the air conditioner. For example, the operating frequency of the compressor, the operating frequency of the fan, etc. By monitoring the frequency data, the change of the working state of components such as the compressor can be understood. Abnormal frequency data may indicate that there are faults in components such as the compressor, such as abnormal voltage, too high current or problems with the mechanical components of the compressor.

[0076] The air volume level data is the basic data reflecting the air supply and return air conditions of the air supply system of the air conditioner. For example, the indoor unit air supply volume level, the indoor unit return air volume level, etc. The air volume level data can be used to judge whether the air supply system of the air conditioner is working properly and whether the indoor air circulation state is good. Abnormal air volume level data may be caused by fan faults, air supply duct blockages or regulating valve problems, which will affect the cooling or heating effect of the air conditioner.

[0077] The current data refers to the current values consumed by each component during the operation of the air conditioner, such as the compressor current, the fan current, etc. By monitoring the current data, the working state of each component in the air conditioner can be evaluated, including the power consumption of components such as the compressor and the fan. Abnormal current values may indicate electrical faults or mechanical load problems in each component of the air conditioner.

[0078] S102. The cloud server combines the operation data of at least one indoor unit with the operation data of the at least one outdoor unit to obtain the first combined data in the dimension of the indoor unit and the second combined data in the dimension of the air conditioner.

[0079] Among them, the first combined data in the dimension of the indoor unit can reflect the operation situation of the indoor unit and does not include the operation data of the outdoor unit and other system components. The second combined data in the dimension of the air conditioner can reflect the overall operation situation of the air conditioner, including the indoor unit, the outdoor unit, and the related pipelines, circuits and control components, etc.

[0080] By combining and differentiating the operation data according to the air conditioner dimension and the indoor unit dimension, the specific source of the air conditioner fault can be accurately determined. The first combined data in the indoor unit dimension can help to separately identify and detect faults related to the indoor unit, such as the indoor unit clogging fault or the indoor unit expansion valve fault. The second combined data in the air conditioner dimension can provide more comprehensive fault information to help identify and detect faults of the entire air conditioner, such as refrigerant leakage fault or compressor fault, etc.

[0081] In some embodiments, the cloud server may combine the operation data of each indoor unit in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit to obtain the first combined data.

[0082] Among them, the first combined data includes the combined data corresponding to each of the at least one indoor unit.

[0083] Exemplarily, as Figure 6 shown, the air conditioner includes four indoor units, namely indoor unit A, indoor unit B, indoor unit C, and indoor unit D, and two outdoor units, namely outdoor unit a and outdoor unit b. In this case, the cloud server can obtain four first combined data, namely: the first combined data 1 formed by combining the operation data of indoor unit A with the operation data of outdoor unit a and outdoor unit b, the first combined data 2 formed by combining the operation data of indoor unit B with the operation data of outdoor unit a and outdoor unit b, the first combined data 3 formed by combining the operation data of indoor unit C with the operation data of outdoor unit a and outdoor unit b, and the first combined data 4 formed by combining the operation data of indoor unit D with the operation data of outdoor unit a and outdoor unit b.

[0084] In some embodiments, the cloud server may combine the operation data of all indoor units in at least one indoor unit with the operation data of all outdoor units in at least one outdoor unit to obtain the second combined data.

[0085] Exemplarily, as Figure 7 shown, the air conditioner includes four indoor units, namely indoor unit A, indoor unit B, indoor unit C, and indoor unit D, and two outdoor units, namely outdoor unit a and outdoor unit b. In this case, the cloud server can also obtain a second combined data, which is the second combined data formed by combining the operation data of indoor unit A, indoor unit B, indoor unit C, indoor unit D with the operation data of outdoor unit a and outdoor unit b.

[0086] S103. The cloud server inputs the first combined data into the first fault detection model to obtain the first fault information of the air conditioner in the indoor unit dimension, and inputs the second combined data into the second fault detection model to obtain the second fault information of the air conditioner in the air conditioner dimension.

[0087] Among them, the first fault information and the second fault information are respectively used to indicate the fault conditions of the air conditioner. The first fault information and the second fault information may respectively include fault information or normal information.

[0088] It can be understood that the fault of the air conditioner in the air conditioner dimension refers to the fault that occurs in the entire air conditioner, including the indoor unit, the outdoor unit, and the related pipelines, circuits, and control components, etc. This dimension considers the overall operation and fault of the air conditioner. The fault of the air conditioner in the indoor unit dimension refers to the fault that occurs only in the indoor unit and does not include the outdoor unit and other system components. This dimension focuses on the operation status and faults of the indoor unit. By distinguishing the air conditioner dimension and the indoor unit dimension for fault detection, the specific source of the air conditioner fault can be accurately determined, thereby improving the accuracy of air conditioner fault detection.

[0089] S104. The cloud server determines the fault detection result of the air conditioner according to the first fault information and the second fault information.

[0090] In some embodiments, the cloud server may determine the fault detection result of the air conditioner based on a preset correspondence relationship between the first fault information, the second fault information, and the fault detection result of the air conditioner.

[0091] Exemplarily, for the fault of the air conditioner in the air conditioner dimension, the preset correspondence relationship between the first fault information, the second fault information, and the fault detection result of the air conditioner may be as shown in Table 1 below.

[0092] Table 1

[0093] First fault information Second fault information Fault detection result of air conditioner Fault information Fault information Fault result Fault information Normal information Normal result Normal information Fault information Fault result Normal information Normal information Normal result

[0094] Exemplarily, based on the correspondence relationship described in Table 1 above, for the fault of the air conditioner in the air conditioner dimension, such as refrigerant fault, outdoor unit dirty blockage fault, outdoor unit expansion valve fault, compressor fault, etc., when the second fault information is fault information, the fault result is determined as the fault detection result of the air conditioner, that is, it is determined that the air conditioner has a fault in the outdoor unit dimension, such as the above-mentioned refrigerant fault, outdoor unit dirty blockage fault, outdoor unit expansion valve fault, compressor fault, etc.

[0095] Exemplarily, for the fault of the air conditioner in the indoor unit dimension, the preset correspondence relationship between the first fault information, the second fault information, and the fault detection result of the air conditioner may be as shown in Table 2 below.

[0096] Table 2

[0097] First fault information Second fault information Fault detection result of air conditioner Fault information Fault information Fault result Fault information Normal information Normal result Normal information Fault information Fault result Normal information Normal information Normal result

[0098] Exemplarily, based on the corresponding relationship described in Table 2 above, for faults of the air conditioner in the indoor unit dimension, such as indoor unit clogging fault, indoor unit expansion valve fault, etc., when the first fault information is fault information or the second fault information is fault information, the fault result is determined as the fault detection result of the air conditioner, that is, it is determined that the air conditioner has a fault in the indoor unit dimension, such as the above-mentioned indoor unit clogging fault, indoor unit expansion valve fault and other faults.

[0099] Based on Figure 5 In the embodiment shown, the embodiment of the present application provides a control method for a cloud server. By dividing the operation data of the air conditioner into combined data of different dimensions, such as the first combined data in the indoor unit dimension and the second combined data in the air conditioner dimension, the faults of the air conditioner can be detected more comprehensively and accurately from different dimensions. For example, the first combined data can be input into the first fault detection model for detecting faults of the air conditioner in the indoor unit dimension to achieve accurate detection of indoor unit faults. The second combined data can also be input to detect faults of the air conditioner in the overall dimension of the air conditioner to improve the accurate detection of overall faults of the air conditioner.

[0100] Furthermore, the cloud server can obtain the target detection result of the air conditioner based on the first fault information and the second fault information. In this way, this method considers the fault problem of the air conditioner from both the indoor unit dimension and the overall dimension of the air conditioner, can more accurately locate and identify the fault source, and thus can improve the accuracy of fault detection.

[0101] In some embodiments, before step S102, as Figure 8 shown, the control method for a cloud server provided by the embodiment of the present application may further include the following steps.

[0102] S201. The cloud server processes the operation data of the air conditioner and extracts the non-steady-state operation data from the operation data of the air conditioner.

[0103] In some embodiments, the cloud server may extract non-steady-state operation data based on the sliding window method.

[0104] In some embodiments, as Figure 9 shown, step S201 may also be implemented as the following steps.

[0105] S2011. The cloud server periodically detects the operation data of the air conditioner at a preset time length.

[0106] Wherein, one detection period includes the operation data within the preset time length.

[0107] In some embodiments, the preset duration can be set in advance by the management personnel or determined based on the detection period, and the embodiments of the present application do not limit this.

[0108] In some embodiments, the preset duration can be obtained from the following formula (1).

[0109] D = [e - c(t - d)] Formula (1)

[0110] Where D is the preset duration; c and d are constant coefficients; t is the detection period.

[0111] S2012. For each detection period, when the standard deviation of the operation data within the detection period is within the preset range, the cloud server determines that the operation data within the detection period is non-steady-state operation data.

[0112] Optionally, the preset range can be a numerical range greater than the preset threshold, and the embodiments of the present application do not limit this.

[0113] In some embodiments, for each detection period, when the standard deviation of the operation data within the detection period is outside the preset range, the cloud server determines that the operation data within the detection period is steady-state operation data.

[0114] S202. The cloud server eliminates the non-steady-state operation data.

[0115] It can be understood that as the operating conditions of the air conditioner change, such as load changes, etc., it will cause large changes in the operation data of the air conditioner, making the operation data of the air conditioner unstable or abnormal, thus unable to accurately reflect the fault situation of the air conditioner and affecting the accuracy of air conditioner fault detection. Therefore, it is necessary to eliminate the unstable operation data (i.e., the above non-steady-state operation data) in the operation data of the air conditioner.

[0116] In some embodiments, the cloud server can eliminate the non-steady-state operation data stored in the database.

[0117] In some embodiments, the cloud server can also eliminate the operation data within the first preset time period after the air conditioner is turned on.

[0118] It can be understood that the operation data of the air conditioner within a period of time after startup may be affected by various factors, such as temperature adjustment, wind speed change, etc., which may cause fluctuations in the operation data of the air conditioner. By eliminating the operation data within this period of time, it is possible to ensure that more stable operation data is obtained, thereby more accurately detecting the faults of the air conditioner.

[0119] In some embodiments, the above preset time period can be obtained from the following formula (2).

[0120] N = [e - a(t - b)] Equation (2)

[0121] Wherein, N is a preset time period; a and b are constant coefficients; t is a detection period.

[0122] In some embodiments, as Figure 10 shown, before step S102, as Figure 8 shown, a control method for a cloud server provided by an embodiment of the present application may further include the following steps.

[0123] S301. The cloud server processes the operation data of the air conditioner with a target data type.

[0124] Wherein, the target data type is a detectable data type of the first fault detection model and / or the second fault detection model.

[0125] It can be understood that the processing method based on the target data type is intended to convert the operation data of the air conditioner into operation data that can be processed and recognized by the first fault detection model and / or the second fault detection model. This method aims to keep the operation data consistent with the requirements of the target data type, thereby reducing the deviation of the fault detection model caused by inconsistent operation data of different air conditioners.

[0126] In some embodiments, the target data type can be used to indicate the data volume, and the cloud server can process the operation data of the air conditioner according to the target data type so that the data volume of the processed operation data of the air conditioner matches the data volume indicated by the target data type.

[0127] It can be understood that this can ensure that the operation data of different air conditioners have a consistent data volume. This can reduce the inconsistency of the input features of the first fault detection model and / or the second fault detection model caused by inconsistent data volumes of the operation data of different air conditioners, and further reduce the deviation of the fault detection model. By maintaining the consistency of the input features, the fault detection model can more accurately detect and diagnose air conditioner faults for different air conditioners.

[0128] In some embodiments, as Figure 11 shown, step S301 can be implemented as the following steps.

[0129] S3011. When the operation data of the air conditioner is the first data, the cloud server performs weighted averaging on the operation data of the air conditioner according to the weight value corresponding to the operation data of the air conditioner so that the weighted average operation data of the air conditioner matches the target data type.

[0130] Wherein, the weight value is used to characterize the on - off state of the air conditioner, and the first data includes temperature data and pressure data.

[0131] Optionally, when the air conditioner is in the on state, the weight value of the operation data of the air conditioner is 1. When the air conditioner is in the off state, the weight value of the operation data of the air conditioner is 0.

[0132] In some embodiments, when at least one indoor unit of the air conditioner is regarded as a whole and at least one outdoor unit is regarded as a whole, the first data can be considered as data obtained by detecting the same object at different points. For example, for the outdoor temperature in the operation data of the air conditioner, each outdoor unit may have its own independent temperature sensor. Due to the differences in the positions, settings, and external conditions of different outdoor units, there may be slight differences in the outdoor temperatures detected by different outdoor units.

[0133] In some embodiments, the cloud server can match the weighted average operation data of the air conditioner with the target data type by weighted averaging the operation data of the air conditioner, so as to maintain the consistency of the input features.

[0134] Exemplarily, the air conditioner includes three indoor units, namely indoor unit A, indoor unit B, and indoor unit C. And, the operation data of indoor unit A is A1, the weight value of the operation data of indoor unit A is status1, the operation data of indoor unit B is B1, the weight value of the operation data of indoor unit B is status2, the operation data of indoor unit C is C1, and the weight value of the operation data of indoor unit C is status3. When the operation data of the air conditioner is weighted averaged, the obtained weighted average value D is

[0135] (status1 × A1 + status2 × B1 + status3 × C1) / (status1 + status2 + status3).

[0136] S3012. When the operation data of the air conditioner is the second data, the cloud server adds the operation data of the air conditioner so that the added operation data of the air conditioner matches the target data type.

[0137] Wherein, the second data includes other data except the temperature data and the pressure data.

[0138] In some embodiments, if the operation data of the air conditioner not only represents its own characteristics and performance, and when at least one indoor unit of the air conditioner is regarded as a whole and at least one outdoor unit is regarded as a whole, after adding the operation data of at least one indoor unit or at least one outdoor unit, the obtained total operation data still reflects the comprehensive characteristics and performance of the entire air conditioner, then the operation data of the air conditioner can be determined as the second data.

[0139] In some embodiments, when the operating data of the air conditioner is the second data, the cloud server may add up the operating data of the air conditioner. This method not only makes the added operating data of the air conditioner match the target data type, thus maintaining the consistency of the input features, but also retains the physical meaning of these operating data.

[0140] It should be noted that the above steps are all executed by the processor of the cloud server.

[0141] The following combines with the Figure 12 illustrated embodiments to exemplarily introduce the complete process of the control method of the cloud server.

[0142] As Figure 12 shown, the cloud server can obtain the operating data of the air conditioner from the device side and store the operating data in the database. When the cloud server performs fault detection on the air conditioner, it can obtain the operating data of the air conditioner from the database. The data preprocessing module in the cloud server can perform data preprocessing on the obtained operating data of the air conditioner, including non-steady state data elimination (i.e., the Figure 8 , Figure 9 illustrated embodiments), data unification (i.e., the Figure 10 , Figure 11 illustrated embodiments), and data combination (i.e., the Figure 6 , Figure 7 illustrated embodiments). After performing data preprocessing on the obtained operating data of the air conditioner, the cloud server can input the preprocessed operating data of the air conditioner into the first fault detection model and the second fault detection model to obtain the fault detection result of the air conditioner. When the cloud server determines that the air conditioner has a fault, the cloud server can issue a fault warning. The cloud server can also send the fault detection result of the air conditioner to the user side for visual display to the user.

[0143] Those skilled in the art should be able to realize that in one or more of the above examples, the functions described in the present invention can be implemented by hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. The computer-readable medium includes computer storage media and communication media, where the communication media includes any medium that facilitates the transmission of a computer program from one place to another. The storage media can be any available medium accessible by a general-purpose or special-purpose computer.

[0144] Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and conciseness of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0145] As described above, this is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A cloud server, characterized in that, Including: A communicator for establishing a communication connection with an air conditioner; the air conditioner includes at least one indoor unit and at least one outdoor unit; A processor configured to: Obtain the operation data of the air conditioner; wherein, the operation data of the air conditioner includes the operation data of at least one indoor unit and the operation data of at least one outdoor unit; Combine the operation data of the at least one indoor unit with the operation data of the at least one outdoor unit to obtain first combined data in terms of the indoor unit dimension and second combined data in terms of the air conditioner dimension; Input the first combined data into a first fault detection model to obtain first fault information of the air conditioner in terms of the indoor unit dimension, and input the second combined data into a second fault detection model to obtain second fault information of the air conditioner in terms of the air conditioner dimension; Determine the fault detection result of the air conditioner according to the first fault information and the second fault information.

2. The cloud server according to claim 1, wherein The processor, when configured to combine the operation data of the at least one indoor unit with the operation data of the at least one outdoor unit to obtain first combined data in terms of the indoor unit dimension and second combined data in terms of the air conditioner dimension, is specifically configured to: Respectively combine the operation data of each indoor unit in the at least one indoor unit with the operation data of all outdoor units in the at least one outdoor unit to obtain the first combined data; the first combined data includes the combined data corresponding to each of the at least one indoor unit; Combine the operation data of all indoor units in the at least one indoor unit with the operation data of all outdoor units in the at least one outdoor unit to obtain the second combined data.

3. The cloud server according to claim 1, wherein Before the processor is configured to combine the operation data of the at least one indoor unit with the operation data of the at least one outdoor unit, it is further configured to: Process the operation data of the air conditioner and extract the non-steady-state operation data from the operation data of the air conditioner; Eliminate the non-steady-state operation data.

4. The cloud server according to claim 3, wherein, The processor, when configured to process the operation data of the air conditioner and extract the non-steady-state operation data from the operation data of the air conditioner, is specifically configured to: Periodically detect the operation data of the air conditioner at a preset time interval; wherein, one detection period includes the operation data within the preset time interval; For each detection period, when the standard deviation of the operation data within the detection period is within a preset range, determine the operation data within the detection period as non-steady-state operation data.

5. The cloud server according to any one of claims 1-4, characterized in that, Before the processor is configured to combine the operation data of the at least one indoor unit with the operation data of the at least one outdoor unit, it is further configured to: Process the operation data of the air conditioner in a target data type; the target data type is the detectable data type of the first fault detection model and / or the second fault detection model.

6. The cloud server according to claim 5, wherein, The processor, when configured to process the operation data of the air conditioner in a target data type, is specifically configured to: When the operating data of the air conditioner is the first data, the operating data of the air conditioner is weighted and averaged according to the weight value corresponding to the operating data of the air conditioner, so that the operating data of the air conditioner matches the target data type; wherein, the weight value is used to represent the on-off state of the air conditioner, and the first data includes temperature data and pressure data; When the operating data of the air conditioner is the second data, the operating data of the air conditioner is added up, so that the operating data of the air conditioner matches the target data type; wherein, the second data includes other data except the temperature data and the pressure data.

7. A control method for a cloud server, characterized in that, It includes: Obtain the operating data of the air conditioner; wherein, the operating data of the air conditioner includes the operating data of at least one indoor unit and the operating data of at least one outdoor unit; Combine the operating data of the at least one indoor unit and the operating data of the at least one outdoor unit to obtain first combined data in terms of the indoor unit dimension and second combined data in terms of the air conditioner dimension; Input the first combined data into a first fault detection model to obtain first fault information of the air conditioner in terms of the indoor unit dimension, and input the second combined data into a second fault detection model to obtain second fault information of the air conditioner in terms of the air conditioner dimension; Determine the fault detection result of the air conditioner according to the first fault information and the second fault information.

8. The method according to claim 7, characterized in that Before combining the operating data of the at least one indoor unit and the operating data of the at least one outdoor unit to obtain first combined data in terms of the indoor unit dimension and second combined data in terms of the air conditioner dimension, the method further includes: Combine the operating data of each indoor unit in the at least one indoor unit with the operating data of all outdoor units in the at least one outdoor unit respectively to obtain the first combined data; the first combined data includes the combined data corresponding to each of the at least one indoor unit; Combine the operating data of all indoor units in the at least one indoor unit with the operating data of all outdoor units in the at least one outdoor unit to obtain the second combined data.

9. The method according to claim 7, wherein Before combining the operating data of the at least one indoor unit and the operating data of the at least one outdoor unit, the method further includes: Process the operating data of the air conditioner and extract the non-steady-state operating data from the operating data of the air conditioner; Eliminate the non-steady-state operating data.

10. The method according to any one of claims 7-9, characterized in that, Before combining the operating data of the at least one indoor unit and the operating data of the at least one outdoor unit, the method further includes: Process the operating data of the air conditioner with a target data type; the target data type is the detectable data type of the first fault detection model and / or the second fault detection model.

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