Intelligent prediction processing method and device for air conditioner operation faults

Abstract

The invention relates to the technical field of data processing, and discloses an intelligent prediction processing method and device for an air conditioner operation fault, and the method comprises the steps: collecting environment data of a working area of an air conditioner and operation data of the air conditioner, determining real-time environment parameters corresponding to the working area of the air conditioner according to the environment data, and determining real-time environment parameters corresponding to the working area of the air conditioner according to the operation data of the air conditioner; real-time operation parameters of the air conditioner are determined, ideal environment parameters corresponding to the real-time operation parameters are estimated according to the real-time operation parameters of the air conditioner, the matching degree between the real-time environment parameters and the ideal environment parameters is calculated, and when the matching degree is smaller than a preset matching degree threshold value, the real-time operation parameters of the air conditioner are determined according to the real-time environment parameters, the ideal environment parameters and the real-time operation parameters. And determining current fault information of the air conditioner. Therefore, the determining accuracy and determining efficiency of the fault information of the air conditioner can be improved, then the operation safety and stability of the air conditioner can be improved, and the air conditioner use experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent prediction and processing method and device for air-conditioning operation failure. Background Art

[0002] With the advancement of technology and the improvement of people's living standards, air conditioners have gradually entered various scenes of people's production and life, providing people with a comfortable production and living environment. However, air conditioner failures often bring inconvenience to people's production and life, and even cause serious economic losses. It is very important to ensure the normal and stable operation of air conditioners.

[0003] In real life, the cause of an air conditioner failure often needs to be determined by professional maintenance personnel using professional equipment, and corresponding maintenance suggestions are given based on the cause of the air conditioner failure. However, this method of determining the cause of the air conditioner failure is inefficient, resulting in a longer maintenance time for the air conditioner, which may increase the risk of economic losses to users due to air conditioner failure. Therefore, it is particularly important to propose a technical solution that can improve the efficiency of determining the cause of an air conditioner failure. Summary of the invention

[0004] The present invention provides an intelligent prediction and processing method and device for air-conditioning operation failure, which can help improve the efficiency of determining the cause of the air-conditioning failure.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses an intelligent prediction and processing method for air conditioner operation failure, the method comprising:

[0006] Collecting environmental data of the working area of ​​the air conditioner and operating data of the air conditioner;

[0007] Determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner;

[0008] According to the real-time operating parameters of the air conditioner, estimating the ideal environmental parameters corresponding to the real-time operating parameters;

[0009] The matching degree between the real-time environmental parameters and the ideal environmental parameters is calculated, and when the matching degree is less than a preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

[0010] As an optional implementation, in the first aspect of the present invention, when the matching degree is less than a preset matching degree threshold, the method further includes:

[0011] Acquire a set of influencing factors affecting the real-time environmental parameters in the working area of ​​the air conditioner and data of at least one influencing factor in the set of influencing factors;

[0012] Determining, according to the data of each of the influencing factors in the influencing factor set, an influence coefficient of the influencing factor set on the real-time environmental parameter;

[0013] When the influence coefficient is less than a preset influence coefficient threshold, the operation of determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters is triggered.

[0014] As an optional implementation manner, in the first aspect of the present invention, determining the influence coefficient of the influencing factor set on the real-time environmental parameter according to the data of each influencing factor in the influencing factor set includes:

[0015] Determine, according to the data of each of the influencing factors in the influencing factor set, a parameter of the degree of influence of each of the influencing factors on the real-time environmental parameter;

[0016] Acquire historical impact data corresponding to each of the impact factors, and determine a weight coefficient of each of the impact factors according to the historical impact data;

[0017] Determining the influence coefficient of the influencing factor set on the real-time environmental parameter according to the influence degree parameter of each influencing factor on the real-time environmental parameter and the weight coefficient of each influencing factor;

[0018] And, when the influence coefficient is greater than the influence coefficient threshold, the method further includes:

[0019] The matching degree between the real-time environmental parameter and the ideal environmental parameter is updated according to the influence coefficient.

[0020] As an optional implementation manner, in the first aspect of the present invention, determining the current fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter and the real-time operating parameter includes:

[0021] Acquire user data of a target user associated with the air conditioner in a working area of ​​the air conditioner, and determine operation information of the target user on the air conditioner according to the user data;

[0022] Determine the software fault impact degree corresponding to the operation information, and determine the software fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter, the real-time operating parameter and the software fault impact degree, wherein the current fault information at least includes the software fault information; and / or,

[0023] Determining an operating parameter of at least one component of the air conditioner according to the real-time operating parameter of the air conditioner;

[0024] According to the operating parameters of each component of the air conditioner and the operating information, the degree of impact of the hardware fault corresponding to the operating information is determined, and according to the real-time environmental parameters, the ideal environmental parameters, the real-time operating parameters and the degree of impact of the hardware fault, the hardware fault information of the air conditioner is determined, and the current fault information at least includes the hardware fault information.

[0025] As an optional implementation manner, in the first aspect of the present invention, after determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters, the method further includes:

[0026] Determining, according to current fault information of the air conditioner, a probability of occurrence of an associated fault corresponding to the current fault information, wherein the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from a current operation mode to a target operation mode, wherein the target operation mode includes at least one other operation mode different from the current operation mode;

[0027] When the probability of occurrence of the associated fault is greater than a preset associated fault probability threshold, the air conditioner is adjusted from the current operating mode to each of the other operating modes, and associated fault information of the associated fault corresponding to the current fault information of the air conditioner in each of the other operating modes is determined.

[0028] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0029] Analyze the current fault information of the air conditioner and / or the associated fault information to obtain an analysis result, and determine a fault processing condition corresponding to the analysis result, wherein the analysis result includes comprehensive fault information of the air conditioner;

[0030] When the fault handling condition meets the preset self-help troubleshooting condition, generating self-help troubleshooting parameters according to the comprehensive fault information of the air conditioner;

[0031] The air conditioner is controlled to perform a self-service troubleshooting operation according to the self-service troubleshooting parameters.

[0032] As an optional implementation manner, in the first aspect of the present invention, when the fault handling condition does not meet the preset self-service troubleshooting condition, the method further includes:

[0033] Acquire historical fault data of the air conditioner, and determine a fault level reference parameter corresponding to comprehensive fault information of the air conditioner according to the historical fault data of the air conditioner;

[0034] Determining a fault level and a fault handling strategy corresponding to the comprehensive fault information of the air conditioner according to the fault level reference parameter and the comprehensive fault information;

[0035] A fault prompt is provided according to the comprehensive fault information, the fault level and the fault handling strategy.

[0036] The second aspect of the present invention discloses an intelligent prediction and processing device for air conditioner operation failure, the device comprising:

[0037] A collection module, used to collect environmental data of the working area of ​​the air conditioner and operating data of the air conditioner;

[0038] A first determination module, configured to determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and to determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner;

[0039] An estimation module, used for estimating ideal environmental parameters corresponding to the real-time operating parameters of the air conditioner according to the real-time operating parameters of the air conditioner;

[0040] A calculation module is used to calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters. When the matching degree is less than a preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

[0041] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0042] A first acquisition module, configured to acquire, when the matching degree is less than a preset matching degree threshold, a set of influencing factors affecting the real-time environmental parameters in the working area of ​​the air conditioner and data of at least one influencing factor in the set of influencing factors;

[0043] The first determination module is also used to determine the influence coefficient of the influence factor set on the real-time environmental parameters based on the data of each of the influence factors in the influence factor set. When the influence coefficient is less than a preset influence coefficient threshold, the calculation module is triggered to execute the operation of determining the current fault information of the air conditioner based on the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

[0044] As an optional implementation, in the second aspect of the present invention, the first determination module determines the influence coefficient of the influencing factor set on the real-time environmental parameter according to the data of each influencing factor in the influencing factor set, specifically including:

[0045] Determine, according to the data of each of the influencing factors in the influencing factor set, a parameter of the degree of influence of each of the influencing factors on the real-time environmental parameter;

[0046] Acquire historical impact data corresponding to each of the impact factors, and determine a weight coefficient of each of the impact factors according to the historical impact data;

[0047] Determining the influence coefficient of the influencing factor set on the real-time environmental parameter according to the influence degree parameter of each influencing factor on the real-time environmental parameter and the weight coefficient of each influencing factor;

[0048] And, the device further comprises:

[0049] An updating module is used to update the matching degree between the real-time environment parameter and the ideal environment parameter according to the influence coefficient when the influence coefficient is greater than the influence coefficient threshold.

[0050] As an optional implementation, in the second aspect of the present invention, the calculation module determines the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters in a manner that specifically includes:

[0051] Acquire user data of a target user associated with the air conditioner in a working area of ​​the air conditioner, and determine operation information of the target user on the air conditioner according to the user data;

[0052] Determine the software fault impact degree corresponding to the operation information, and determine the software fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter, the real-time operating parameter and the software fault impact degree, wherein the current fault information at least includes the software fault information; and / or,

[0053] Determining an operating parameter of at least one component of the air conditioner according to the real-time operating parameter of the air conditioner;

[0054] According to the operating parameters of each component of the air conditioner and the operating information, the degree of impact of the hardware fault corresponding to the operating information is determined, and according to the real-time environmental parameters, the ideal environmental parameters, the real-time operating parameters and the degree of impact of the hardware fault, the hardware fault information of the air conditioner is determined, and the current fault information at least includes the hardware fault information.

[0055] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0056] a second determination module, configured to determine, after the calculation module determines the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters, a probability of occurrence of an associated fault corresponding to the current fault information according to the current fault information of the air conditioner, wherein the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from the current operating mode to the target operating mode, and the target operating mode includes at least one other operating mode different from the current operating mode;

[0057] The second determination module is also used to adjust the air conditioner from the current operating mode to each of the other operating modes when the probability of occurrence of the associated fault is greater than a preset associated fault probability threshold, and determine the associated fault information of the associated fault corresponding to the current fault information in each of the other operating modes of the air conditioner.

[0058] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0059] an analysis module, configured to analyze the current fault information of the air conditioner and / or the associated fault information, obtain an analysis result, and determine a fault processing condition corresponding to the analysis result, wherein the analysis result includes comprehensive fault information of the air conditioner;

[0060] A generating module, configured to generate a self-service troubleshooting parameter according to the comprehensive fault information of the air conditioner when the fault handling condition satisfies a preset self-service troubleshooting condition;

[0061] A control module is used to control the air conditioner to perform a self-service troubleshooting operation according to the self-service troubleshooting parameters.

[0062] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0063] a second acquisition module, configured to acquire historical fault data of the air conditioner when the fault handling condition does not meet a preset self-help troubleshooting condition, and determine a fault level reference parameter corresponding to the comprehensive fault information of the air conditioner according to the historical fault data of the air conditioner;

[0064] The second determination module is further used to determine the fault level and fault handling strategy corresponding to the comprehensive fault information of the air conditioner according to the fault level reference parameter and the comprehensive fault information;

[0065] A fault prompt module is used to provide a fault prompt according to the comprehensive fault information, the fault level and the fault handling strategy.

[0066] The third aspect of the present invention discloses another intelligent prediction and processing device for air conditioner operation failure, the device comprising:

[0067] A memory storing executable program code;

[0068] a processor coupled to the memory;

[0069] The processor calls the executable program code stored in the memory to execute the intelligent prediction and processing method for air-conditioning operation failure disclosed in the first aspect of the present invention.

[0070] The fourth aspect of the present invention discloses a computer storage medium, wherein the computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the intelligent prediction and processing method for air-conditioning operation failure disclosed in the first aspect of the present invention.

[0071] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0072] In the embodiment of the present invention, the environmental data of the working area of ​​the air conditioner and the operating data of the air conditioner are collected, and the real-time environmental parameters corresponding to the working area of ​​the air conditioner are determined according to the environmental data, and the real-time operating parameters of the air conditioner are determined according to the operating data of the air conditioner, and the ideal environmental parameters corresponding to the real-time operating parameters are estimated according to the real-time operating parameters of the air conditioner, and the matching degree between the real-time environmental parameters and the ideal environmental parameters is calculated, and when the matching degree is less than the preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters. It can be seen that the implementation of the present invention can determine the real-time operating parameters through the operating data of the air conditioner, and then estimate the ideal environmental parameters of the air conditioner, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, and can determine the current fault information of the air conditioner when the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, thereby improving the accuracy and efficiency of determining the fault information of the air conditioner, thereby improving the operating safety and stability of the air conditioner, and enhancing the user's air conditioner usage experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0074] Figure 1It is a schematic diagram of a scenario of an application scenario of an intelligent prediction and processing method for air-conditioning operation failure disclosed in an embodiment of the present invention;

[0075] Figure 2 It is a flow chart of an intelligent prediction and processing method for air-conditioning operation failure disclosed in an embodiment of the present invention;

[0076] Figure 3 It is a flow chart of another intelligent prediction and processing method for air-conditioning operation failure disclosed in an embodiment of the present invention;

[0077] Figure 4 It is a structural schematic diagram of an intelligent prediction and processing device for air-conditioning operation failure disclosed in an embodiment of the present invention;

[0078] Figure 5 It is a structural schematic diagram of another intelligent prediction and processing device for air-conditioning operation failure disclosed in an embodiment of the present invention;

[0079] Figure 6 It is a structural schematic diagram of another intelligent prediction and processing device for air-conditioning operation failure disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0080] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0082] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0083] The present invention discloses an intelligent prediction and processing method and device for air conditioner operation failure, which can determine the real-time operation parameters through the operation data of the air conditioner, and then estimate the ideal environmental parameters of the air conditioner, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, and can determine the current fault information of the air conditioner when the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, thereby improving the accuracy and efficiency of determining the fault information of the air conditioner, thereby improving the operation safety and stability of the air conditioner, and enhancing the user's air conditioner use experience. The following are detailed descriptions.

[0084] In order to better understand the intelligent prediction and processing method for air-conditioning operation failure described in the present invention, i.e., the device, firstly, the scenario to which the intelligent prediction and processing method for air-conditioning operation failure is applicable is described. Specifically, the scenario can be as follows: Figure 1 As shown, Figure 1 The following is a schematic diagram of an application scenario of an intelligent prediction and processing method for air-conditioning operation failure disclosed in an embodiment of the present invention. Figure 1 As shown, the scene diagram includes an air conditioner and a user (such as Xiao Ming), a smart device (such as a cleaning robot) and a home (such as a chair) in the working area corresponding to the air conditioner. The environmental data in the working area of ​​the air conditioner and the operating data of the air conditioner can be collected, and the current fault information of the air conditioner can be determined based on the environmental data in the working area of ​​the air conditioner and the operating data of the air conditioner. The relevant data can be collected by a collection device preset in the working area corresponding to the air conditioner or a collection device preset in the air conditioner, and the fault information of the air conditioner can be displayed on the display screen of the air conditioner in the form of a fault code, or the fault information of the air conditioner can be transmitted to the user in the form of a text message or an application message.

[0085] It should be noted that Figure 1 The scenario diagram shown is only for illustrating the scenarios to which the intelligent prediction and processing method for air conditioner operation failure is applicable. The air conditioner involved and the user (such as Xiao Ming) in the working area corresponding to the air conditioner, the smart device (such as a cleaning robot) and the home (such as a chair) are also only schematically shown. Figure 1 The scenario diagram shown does not limit this. The above describes the scenarios to which the intelligent prediction and processing method for air conditioner operation failure is applicable, and the following describes the intelligent prediction and processing method and device for air conditioner operation failure in detail.

[0086] Embodiment 1

[0087] See also Figure 2 , Figure 2 This is a flow chart of an intelligent prediction and processing method for air conditioner operation failure disclosed in an embodiment of the present invention. Figure 2The intelligent prediction and processing method for air-conditioning operation failure described can be applied to an intelligent prediction and processing device for air-conditioning operation failure, wherein the intelligent prediction and processing device for air-conditioning operation failure may include an intelligent device for predicting and processing air-conditioning failure, the intelligent device may include an intelligent collection device and an intelligent prediction and processing device, the intelligent collection device may include an intelligent sensor, the intelligent prediction and processing device may include an intelligent server or an intelligent platform, the intelligent server includes a local server or a cloud server, and the embodiments of the present invention do not limit this. Figure 2 As shown, the intelligent prediction and processing method for air conditioner operation failure may include the following operations:

[0088] 101. Collect environmental data of the working area of ​​the air conditioner and the operating data of the air conditioner.

[0089] In an embodiment of the present invention, optionally, the environmental data of the working area of ​​the air conditioner may include internal environmental data of the working area and external environmental data of the working area. The internal environmental data of the working area may include at least one of the area of ​​the area, the ventilation conditions of the area, the internal temperature data, the internal humidity data, the internal heat source data, the internal heat absorption conditions data, the internal user data and the functional division data of the working area. The external environmental data of the working area may include at least one of the external temperature data, the external humidity data, the meteorological data and the like. The operating data of the air conditioner may include the current operating mode of the air conditioner and at least one of the air outlet direction, air outlet temperature, air outlet flow rate, air outlet noise, air outlet humidity and operating data of components of the air conditioner corresponding to the current operating mode. The present invention is not limited thereto.

[0090] 102. Determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner.

[0091] In an embodiment of the present invention, optionally, the real-time environmental parameters corresponding to the working area of ​​the air conditioner may include internal environmental parameters of the working area and external environmental parameters of the working area, wherein the internal environmental parameters of the working area can be used to reflect the working effect of the air conditioner in the current operating mode, and the external environmental parameters of the working area can be used to determine the impact of the external environment of the air conditioner on the operation of the outdoor unit of the air conditioner. The real-time operating parameters of the air conditioner may include the air outlet parameters of the air conditioner in the current operating mode and the operating parameters of each component of the air conditioner, which are not limited by the present invention.

[0092] 103. According to the real-time operating parameters of the air conditioner, estimate the ideal environmental parameters corresponding to the real-time operating parameters.

[0093] In an embodiment of the present invention, optionally, the ideal environmental parameters corresponding to the real-time operating parameters may indicate the parameter conditions of the working area corresponding to the air conditioner when the air conditioner works in a preset standard environmental scenario according to the implementation operating parameters. The ideal environmental parameters may include at least one of ideal environmental temperature parameters, ideal environmental humidity parameters, and ideal environmental user parameters, and the present invention does not limit this.

[0094] 104. Calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters. When the matching degree is less than a preset matching degree threshold, determine the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

[0095] In an embodiment of the present invention, optionally, the degree of match between the real-time environmental parameters and the ideal environmental parameters can be reflected by the parameter difference between the real-time environmental parameters and the ideal environmental parameters, that is, the parameter difference of each corresponding parameter between the real-time environmental parameters and the ideal environmental parameters can be calculated respectively, and then the parameter difference of each corresponding parameter is integrated and calculated, such as weighted average calculation, to obtain the degree of match between the real-time environmental parameters and the ideal environmental parameters. When the degree of match is greater than a preset degree of match threshold, it means that the difference between the real-time environmental parameters and the ideal environmental parameters when the air conditioner is running in the current operating mode is small, that is, the air conditioner is running normally. When the degree of match is less than the preset degree of match threshold, it means that the difference between the real-time environmental parameters and the ideal environmental parameters when the air conditioner is running in the current operating mode is large, that is, the air conditioner is running abnormally. The present invention does not make any limitation.

[0096] In an embodiment of the present invention, optionally, the current fault information of the air conditioner may include the current actual fault information and / or the current predicted fault information of the air conditioner. The current actual fault information of the air conditioner indicates that the air conditioner has currently failed, and the current predicted fault information indicates that the air conditioner is about to fail. The current fault information of the air conditioner may include at least one of the fault type, fault cause, fault level, etc., which is not limited by the present invention.

[0097] It can be seen that the implementation Figure 2The described intelligent prediction and processing method for air-conditioning operation failure can collect environmental data of the working area of ​​the air-conditioning and the operation data of the air-conditioning, determine the real-time environmental parameters corresponding to the working area of ​​the air-conditioning according to the environmental data, and determine the real-time operation parameters of the air-conditioning according to the operation data of the air-conditioning, estimate the ideal environmental parameters corresponding to the real-time operation parameters according to the real-time operation parameters of the air-conditioning, determine the real-time operation parameters through the operation data of the air-conditioning, and then estimate the ideal environmental parameters of the air-conditioning, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, calculating the matching degree between the real-time environmental parameters and the ideal environmental parameters, and when the matching degree is less than a preset matching degree threshold, determining the current fault information of the air-conditioning according to the real-time environmental parameters, the ideal environmental parameters and the real-time operation parameters, and being able to determine the current fault information of the air-conditioning when the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, thereby improving the accuracy and efficiency of determining the fault information of the air-conditioning, thereby improving the operating safety and stability of the air-conditioning, and enhancing the user's air-conditioning usage experience.

[0098] In an optional embodiment, determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters, and the real-time operating parameters may include the following operations:

[0099] Acquire user data of a target user associated with the air conditioner in a working area of ​​the air conditioner, and determine operation information of the target user on the air conditioner according to the user data;

[0100] Determine the impact degree of the software fault corresponding to the operation information, and determine the software fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters, the real-time operating parameters and the impact degree of the software fault, wherein the current fault information at least includes the software fault information; and / or,

[0101] determining an operating parameter of at least one component of the air conditioner based on the real-time operating parameter of the air conditioner;

[0102] Based on the operating parameters and operation information of each component of the air conditioner, the impact degree of the hardware failure corresponding to the operation information is determined, and based on the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the impact degree of the hardware failure, the hardware failure information of the air conditioner is determined. The current fault information at least includes the hardware failure information.

[0103] In this optional embodiment, optionally, the user data of the target user associated with the air conditioner within the working area of ​​the air conditioner may include at least one of the number of users, the age of the user, the health status of the user, the sleep status of the user, the user's perceived temperature requirements, the user's perceived humidity requirements, the user's temperature sensitivity coefficient, and the user's operation data on the air conditioner, and the target user's operation information on the air conditioner may include current operation information and historical operation information, the current operation information may include manual control operation information and / or voice control operation information, and the historical operation information may include the target user's operating habit information on the air conditioner, which is not limited in this embodiment.

[0104] In this optional embodiment, optionally, the impact degree of the software failure corresponding to the operation information may include the rationality of the operation instructions of the target user to operate the air conditioner, the time interval between different operation instructions, and whether there will be conflicts between different operation instructions, etc., and the impact degree of information on the software operation of the air conditioner. When the impact degree is greater than the relevant threshold, it will cause a software failure of the air conditioner. The software failure information may include the type of software failure, the fault code of each type of software failure, and the solution. Among them, the type of software failure may include at least one of the following: the air conditioner software freezes, the air conditioner cannot recognize the instructions issued by the target user, the air conditioner incorrectly recognizes the instructions issued by the target user, and the air conditioner stops working, etc. This embodiment does not limit this.

[0105] In this optional embodiment, optionally, the operating parameters of the components of the air conditioner may include at least one of the current operating posture, standard operating posture, operating time, operating freeze, etc. of the components of the air conditioner. The degree of impact of the hardware failure corresponding to the operating information may include the rationality of the operating instructions of the target user to operate the air conditioner, the time interval between different operating instructions, and whether there will be conflicts between different operating instructions, etc., and the degree of impact on the hardware operation of the air conditioner. When the degree of impact is greater than the relevant threshold, a hardware failure of the air conditioner will be caused. The hardware failure information may include the type of hardware failure, the fault code of each type of hardware failure, and the solution. Among them, the type of hardware failure may include at least one of hardware operation freeze, the operation of the relevant hardware does not match the instruction after the user issues an instruction, the relevant hardware does not respond after the user issues an instruction, and the air conditioner stops working, etc., which is not limited in this embodiment.

[0106] It can be seen that implementing this optional embodiment can obtain user data of a target user associated with the air conditioner in the working area of ​​the air conditioner, and determine the target user's operation data on the air conditioner, determine the degree of influence of the target user's operation data on the software failure of the air conditioner, and determine the software failure information of the air conditioner based on the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the degree of influence of the software failure, and / or determine the operating parameters of at least one component of the air conditioner, and determine the degree of influence of the hardware failure corresponding to the operation information based on the target user's operation data and the component operating parameters, and determine the hardware failure information of the air conditioner based on the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the degree of influence of the hardware failure. It can be combined with the target user's operation data on the air conditioner to determine the degree of influence of the target user's operation data on the software failure and the degree of influence of the hardware failure of the air conditioner, and determine the software and hardware failure information of the air conditioner, thereby improving the accuracy and reliability of the determined air conditioning failure information, thereby improving the operating safety and stability of the air conditioner, and enhancing the user's air conditioning usage experience.

[0107] In another optional embodiment, after determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters, the intelligent prediction and processing method for the air conditioner operating fault may further include the following operations:

[0108] Determine, according to current fault information of the air conditioner, the occurrence probability of an associated fault corresponding to the current fault information, wherein the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from the current operation mode to the target operation mode, and the target operation mode includes at least one other operation mode different from the current operation mode;

[0109] When the probability of occurrence of the associated fault is greater than a preset associated fault probability threshold, the air conditioner is adjusted from the current operating mode to each other operating mode, and the associated fault information of the associated fault corresponding to the current fault information in each other operating mode of the air conditioner is determined.

[0110] In this optional embodiment, optionally, the current fault information of the air conditioner includes fault information of the air conditioner operating in the current operating mode, and the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from the current operating mode to the target operating mode, wherein the target operating mode includes at least one other operating mode different from the current operating mode, which is not limited in this embodiment.

[0111] In this optional embodiment, optionally, when the probability of occurrence of an associated fault is less than a preset associated fault probability threshold, it means that after the air conditioner is adjusted from the current operating mode to the target operating mode, the probability of the air conditioner having a fault associated with the current fault information is small, and there is no need to adjust the air conditioner from the current operating mode to each other operating mode to check for associated faults; when the probability of occurrence of an associated fault is greater than the preset associated fault probability threshold, it means that after the air conditioner is adjusted from the current operating mode to the target operating mode, the probability of the air conditioner having a fault associated with the current fault information is large, and it is necessary to adjust the air conditioner from the current operating mode to each other operating mode, and determine the associated fault information of the associated fault corresponding to the current fault information in each other operating mode of the air conditioner. The associated fault information may include at least one of the associated fault type, the degree of correlation between the associated fault and the current fault, and whether the associated fault can be solved by repairing the current fault, etc., which is not limited in this embodiment.

[0112] It can be seen that the implementation of this optional embodiment can determine the probability of occurrence of the associated fault corresponding to the current fault information based on the current fault information of the air conditioner. When the probability of occurrence of the associated fault is greater than the preset associated fault probability threshold, the air conditioner is adjusted from the current operating mode to each other operating mode, and the associated fault information of the associated fault corresponding to the current fault information in each other operating mode of the air conditioner is determined. The associated fault information of the air conditioner in other operating modes can be checked through the current fault information to reduce the risk of safety problems caused by hidden faults of the air conditioner, improve the completeness and efficiency of determining the fault information of the air conditioner, and at the same time improve the operating safety and reliability of the air conditioner.

[0113] In yet another optional embodiment, the intelligent prediction and processing method for air conditioner operation failure may further include the following operations:

[0114] Analyze the current fault information and / or related fault information of the air conditioner to obtain analysis results, and determine the fault processing conditions corresponding to the analysis results, wherein the analysis results include comprehensive fault information of the air conditioner;

[0115] When the fault handling conditions meet the preset self-service troubleshooting conditions, self-service troubleshooting parameters are generated according to the comprehensive fault information of the air conditioner;

[0116] Control the air conditioner to perform self-service troubleshooting operations according to the self-service troubleshooting parameters.

[0117] In this optional embodiment, optionally, the analysis results may include comprehensive fault information of the air conditioner, i.e., current fault information and / or associated fault information of the air conditioner, the fault handling conditions include the fault handling difficulty corresponding to the fault of the air conditioner, the preset self-service troubleshooting conditions include the self-service troubleshooting capability of the air conditioner, the fault handling conditions satisfying the preset self-service troubleshooting conditions may include that the fault handling difficulty corresponding to the fault of the air conditioner matches the self-service troubleshooting capability of the air conditioner, the self-service troubleshooting parameters include troubleshooting step parameters for the air conditioner fault and specific troubleshooting operation parameters, etc., which are not limited in this embodiment.

[0118] In this optional embodiment, optionally, analyzing the current fault information and / or associated fault information of the air conditioner to obtain the analysis result may include the following operations:

[0119] Determine, according to the current fault information and / or associated fault information of the air conditioner, a fault code corresponding to the current fault information and / or associated fault information of the air conditioner;

[0120] A set of fault codes for processable faults preset in the air conditioner is obtained, and it is analyzed whether there is a fault code for processable faults in the fault code set that matches the fault code corresponding to the current fault information and / or associated fault information of the air conditioner, to obtain an analysis result.

[0121] It can be seen that implementing this optional embodiment can analyze the current fault information and / or related fault information of the air conditioner, obtain analysis results, and determine the fault handling conditions corresponding to the analysis results. When the fault handling conditions meet the preset self-service troubleshooting conditions, self-service troubleshooting parameters are generated according to the comprehensive fault information of the air conditioner, and the air conditioner is controlled to perform self-service troubleshooting operations according to the self-service troubleshooting parameters. The air conditioner itself can handle faults that meet the conditions, thereby improving the efficiency of handling air conditioning faults, and thereby improving the safety and stability of the air conditioner operation.

[0122] In yet another optional embodiment, when the fault handling condition does not meet the preset self-help troubleshooting condition, the intelligent prediction and processing method for air conditioner operation fault may further include the following operations:

[0123] Acquire historical fault data of the air conditioner, and determine a fault level reference parameter corresponding to comprehensive fault information of the air conditioner according to the historical fault data of the air conditioner;

[0124] Determine the fault level and fault handling strategy corresponding to the comprehensive fault information of the air conditioner according to the fault level reference parameter and the comprehensive fault information;

[0125] Provide fault prompts based on comprehensive fault information, fault level and fault handling strategy.

[0126] In this optional embodiment, optionally, the historical fault data of the air conditioner may include historical fault types, historical fault causes, historical fault levels, processing methods corresponding to historical faults, and fault level reference parameters corresponding to each fault, wherein the fault level reference parameters can be used to determine the fault level corresponding to the fault, the fault handling strategy may include a recommended solution corresponding to the fault for reference by fault maintenance personnel, and the form of the fault prompt information may include at least one of a fault code prompt, a text message prompt, a related APP prompt information prompt, etc., which is not limited in this embodiment.

[0127] It can be seen that implementing this optional embodiment can obtain the historical fault data of the air conditioner, and determine the fault level reference parameters corresponding to the comprehensive fault information of the air conditioner based on the historical fault data of the air conditioner, and determine the fault level and fault handling strategy corresponding to the comprehensive fault information of the air conditioner based on the fault level reference parameters and the comprehensive fault information, and provide fault prompts based on the comprehensive fault information, fault level and fault handling strategy. The fault level and fault handling strategy corresponding to the fault information can be clearly defined for reference by fault maintenance personnel, which can improve the efficiency of handling air conditioner faults, improve the safety and stability of air conditioner operation, and thereby enhance user experience.

[0128] In another optional embodiment, after determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters, the intelligent prediction and processing method for the air conditioner operating fault may further include the following operations:

[0129] Determine device information of a smart device associated with the air conditioner in a working area of ​​the air conditioner, where the device information includes device operation information;

[0130] Determine, according to current fault information of the air conditioner and environmental data of a working area of ​​the air conditioner, a device impact parameter of the current fault of the air conditioner on the smart device;

[0131] Generate intelligent device control parameters based on device influencing parameters and environmental data, and control the intelligent device based on the intelligent device control parameters.

[0132] In this optional embodiment, optionally, the device information of the smart device may include device operation information, and may also include at least one of the following: dependence information of the smart device on the air conditioner, optimal operating temperature information of the smart device, optimal operating humidity information of the smart device, operating time of the smart device, etc. The device impact parameter of the current fault of the air conditioner on the smart device indicates the degree of influence of the current fault of the air conditioner on the operating state of the smart device. For example, when the air conditioner fails, a smart fan control parameter may be generated to increase the working mode or gear of the smart fan. For example, when the air conditioner fails, an exhaust fan control parameter, a heater control parameter, a dehumidifier or a humidifier control parameter may be generated to respectively control the working mode or gear of the exhaust fan, heater, dehumidifier or humidifier. This embodiment does not limit this.

[0133] It can be seen that implementing this optional embodiment can determine the device information of the smart device in the working area of ​​the air conditioner, the device information includes the device operation information, and determine the device impact parameters of the current fault of the air conditioner on the smart device based on the current fault information of the air conditioner and the environmental data of the working area of ​​the air conditioner. According to the device impact parameters and the environmental data, the smart device control parameters are generated, and the smart device is controlled according to the smart device control parameters. When the air conditioner fails, the comfort level in the working area of ​​the air conditioner can be ensured by regulating the devices corresponding to the functions of the air conditioner, thereby reducing the bad experience brought to users by the air conditioner failure.

[0134] Embodiment 2

[0135] See also Figure 3 , Figure 3 This is a flow chart of an intelligent prediction and processing method for air conditioner operation failure disclosed in an embodiment of the present invention. Figure 3 The intelligent prediction and processing method for air-conditioning operation failure described can be applied to an intelligent prediction and processing device for air-conditioning operation failure, wherein the intelligent prediction and processing device for air-conditioning operation failure may include an intelligent device for predicting and processing air-conditioning failure, the intelligent device may include an intelligent collection device and an intelligent prediction and processing device, the intelligent collection device may include an intelligent sensor, the intelligent prediction and processing device may include an intelligent server or an intelligent platform, the intelligent server includes a local server or a cloud server, and the embodiments of the present invention do not limit this. Figure 3 As shown, the intelligent prediction and processing method for air conditioner operation failure may include the following operations:

[0136] 201. Collect environmental data of the working area of ​​the air conditioner and operating data of the air conditioner.

[0137] 202. Determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner.

[0138] 203. According to the real-time operating parameters of the air conditioner, estimate the ideal environmental parameters corresponding to the real-time operating parameters.

[0139] 204. Calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters. When the matching degree is less than a preset matching degree threshold, obtain a set of influencing factors affecting the real-time environmental parameters in the working area of ​​the air conditioner and data of at least one influencing factor in the set of influencing factors.

[0140] In an embodiment of the present invention, optionally, the set of influencing factors affecting real-time environmental parameters within the working area of ​​the air conditioner may include biological influencing factors and / or non-biological influencing factors, and the data of the influencing factors may include biological influencing factor data and / or non-biological influencing factor data, wherein the biological influencing factor data may include user data of target users within the working area of ​​the air conditioner, specifically including at least one of the number of users, user temperature, user concentration, etc., and the non-biological influencing factor data may include non-biological data within the working area of ​​the air conditioner, specifically including device data and / or home data, and the device data may include at least one of device operation data, device heat generation data, device distribution data, etc., and the home data may include home distribution data and / or home heat absorption data, which is not limited by the present invention.

[0141] 205. Determine the influence coefficient of the influence factor set on the real-time environmental parameter according to the data of each influence factor in the influence factor set.

[0142] In an embodiment of the present invention, optionally, the influence coefficient of the influencing factor set on the real-time environmental parameters may include the influence coefficient of the influencing factor set on the internal environmental parameters of the working area, specifically including the influence coefficient on the real-time environmental temperature parameters and the influence coefficient on the real-time environmental humidity parameters, etc. The influence coefficient of the influencing factor set on the real-time environmental parameters can reflect the gap between the real-time environmental parameters of the air conditioner and the ideal environmental parameters, and can be used to update the matching degree between the real-time environmental parameters of the air conditioner and the ideal environmental parameters.

[0143] 206. When the influence coefficient is less than a preset influence coefficient threshold, current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters, and the real-time operating parameters.

[0144] In the embodiment of the present invention, for other descriptions of step 201 to step 203 and step 206, please refer to the detailed description of step 101 to step 104 in the first embodiment, which will not be repeated in this embodiment.

[0145] It can be seen that the implementation Figure 3The described intelligent prediction and processing method for air-conditioning operation failure can collect environmental data of the working area of ​​the air-conditioning and the operating data of the air-conditioning, determine the real-time environmental parameters corresponding to the working area of ​​the air-conditioning according to the environmental data, determine the real-time operating parameters of the air-conditioning according to the operating data of the air-conditioning, estimate the ideal environmental parameters corresponding to the real-time operating parameters according to the real-time operating parameters of the air-conditioning, determine the real-time operating parameters through the operating data of the air-conditioning, and then estimate the ideal environmental parameters of the air-conditioning, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters, and when the matching degree is less than a preset matching degree threshold, obtain the influencing factor set affecting the real-time environmental parameters in the working area of ​​the air-conditioning and the data of at least one influencing factor in the influencing factor set. According to the data of each influencing factor in the influencing factor set, the influence coefficient of the influencing factor set on the real-time environmental parameters is determined, and the influence of the influencing factor set on the real-time environmental parameters of the air conditioner can be determined according to the influencing factor set of the working area of ​​the air conditioner, which can reduce the occurrence of misjudgment of air-conditioning failures caused by the influencing factor set. When the influence coefficient is less than the preset influence coefficient threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters. When the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, the current fault information of the air conditioner can be determined, which improves the accuracy and efficiency of determining the fault information of the air conditioner, thereby improving the operating safety and stability of the air conditioner and enhancing the user's air-conditioning experience.

[0146] In an optional embodiment, determining the influence coefficient of the influence factor set on the real-time environment parameter according to the data of each influence factor in the influence factor set may include the following operations:

[0147] Determine the influence degree parameter of each influencing factor on the real-time environmental parameter according to the data of each influencing factor in the influencing factor set;

[0148] Obtaining historical impact data corresponding to each impact factor, and determining a weight coefficient of each impact factor based on the historical impact data;

[0149] Determine the influence coefficient of the influencing factor set on the real-time environmental parameter according to the influence degree parameter of each influencing factor on the real-time environmental parameter and the weight coefficient of each influencing factor;

[0150] Furthermore, when the influence coefficient is greater than the influence coefficient threshold, the intelligent prediction and processing method for air-conditioning operation failure may further include the following operations:

[0151] The matching degree between the real-time environmental parameters and the ideal environmental parameters is updated according to the influence coefficient.

[0152] In this optional embodiment, optionally, the data of the influencing factors may include biological influencing factor data and / or non-biological influencing factor data, wherein the biological influencing factor data may include user data of target users within the working area of ​​the air conditioner, specifically including at least one of the number of users, user temperature, user concentration, etc., and the non-biological influencing factor data may include non-biological data within the working area of ​​the air conditioner, specifically including device data and / or home data, the device data may include at least one of device operation data, device heat generation data, device distribution data, etc., the home data may include home distribution data and / or home heat absorption data, the real-time environmental parameters may include internal environmental parameters of the working area and external environmental parameters of the working area, wherein the internal environmental parameters of the working area can be used to reflect the working effect of the air conditioner under the current operating mode, and optionally, the influence degree parameter of each influencing factor on the real-time environmental parameters may include the influence degree parameter of each influencing factor on the internal environmental parameters of the working area, which is not limited in this embodiment.

[0153] In this optional embodiment, optionally, the historical impact data corresponding to each influencing factor may include the impact size and impact duration of each influencing factor on the real-time environmental parameters of the air conditioner in the working area of ​​the air conditioner when the air conditioner is running. The weight coefficient of each influencing factor can indicate the impact output of each influencing factor on the real-time environmental parameters, that is, the larger the weight coefficient of the influencing factor, the greater the impact of the influencing factor on the real-time environmental parameters. This embodiment does not limit this.

[0154] It can be seen that the implementation of this optional embodiment can determine the influence degree parameter of each influencing factor on the real-time environmental parameters according to the data of each influencing factor in the influencing factor set, obtain the historical influence data corresponding to each influencing factor, and determine the weight coefficient of each influencing factor according to the historical influence data. According to the influence degree parameter of each influencing factor on the real-time environmental parameters and the weight coefficient of each influencing factor, the influence coefficient of the influencing factor set on the real-time environmental parameters is determined, and the influence coefficient of the influencing factor set on the real-time environmental parameters can be calculated by determining the weights of different acoustic factors, thereby improving the accuracy and rationality of the determined influence coefficient, and then the influence of the influencing factor set on the real-time environmental parameters of the air conditioner can be determined according to the influencing factor set of the working area of ​​the air conditioner, and the occurrence of misjudgment of air conditioning failure due to the influencing factor set can be reduced, thereby improving the operating safety and stability of the air conditioner and enhancing the user's air conditioning usage experience.

[0155] Embodiment 3

[0156] See also Figure 4 , Figure 4 The structure diagram of an intelligent prediction and processing device for air conditioner operation failure disclosed in an embodiment of the present invention is shown in FIG. Figure 4The intelligent prediction and processing device for air-conditioning operation failure described may include an intelligent device for predicting and processing air-conditioning failures, the intelligent device may include an intelligent collection device and an intelligent prediction and processing device, the intelligent collection device may include an intelligent sensor, the intelligent prediction and processing device may include an intelligent server or an intelligent platform, the intelligent server includes a local server or a cloud server, and the embodiment of the present invention does not limit this. Figure 4 As shown, the intelligent prediction and processing device for air-conditioning operation failure may include:

[0157] The collection module 301 is used to collect the environmental data of the working area of ​​the air conditioner and the operation data of the air conditioner;

[0158] A first determination module 302 is used to determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner;

[0159] An estimation module 303 is used to estimate the ideal environmental parameters corresponding to the real-time operating parameters according to the real-time operating parameters of the air conditioner;

[0160] The calculation module 304 is used to calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters. When the matching degree is less than a preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

[0161] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure as described in 4 can collect the environmental data of the working area of ​​the air-conditioning and the operation data of the air-conditioning, determine the real-time environmental parameters corresponding to the working area of ​​the air-conditioning according to the environmental data, and determine the real-time operation parameters of the air-conditioning according to the operation data of the air-conditioning, and estimate the ideal environmental parameters corresponding to the real-time operation parameters according to the real-time operation parameters of the air-conditioning, determine the real-time operation parameters through the operation data of the air-conditioning, and then estimate the ideal environmental parameters of the air-conditioning, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, calculating the matching degree between the real-time environmental parameters and the ideal environmental parameters, and when the matching degree is less than the preset matching degree threshold, determining the current fault information of the air-conditioning according to the real-time environmental parameters, the ideal environmental parameters and the real-time operation parameters, and being able to determine the current fault information of the air-conditioning when the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, thereby improving the accuracy and efficiency of determining the fault information of the air-conditioning, thereby improving the operating safety and stability of the air-conditioning, and enhancing the user's air-conditioning usage experience.

[0162] In an optional embodiment, if Figure 5 As shown, the intelligent prediction and processing device for air-conditioning operation failure may also include:

[0163] The first acquisition module 305 is used to acquire a set of influencing factors affecting the real-time environmental parameters in the working area of ​​the air conditioner and data of at least one influencing factor in the set of influencing factors when the matching degree is less than a preset matching degree threshold;

[0164] The first determination module 302 is also used to determine the influence coefficient of the influence factor set on the real-time environmental parameters based on the data of each influence factor in the influence factor set. When the influence coefficient is less than the preset influence coefficient threshold, the calculation module 304 is triggered to execute the operation of determining the current fault information of the air conditioner based on the real-time environmental parameters, ideal environmental parameters and real-time operating parameters.

[0165] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure described in 5 can collect the environmental data of the working area of ​​the air-conditioner and the operation data of the air-conditioner, determine the real-time environmental parameters corresponding to the working area of ​​the air-conditioner according to the environmental data, and determine the real-time operation parameters of the air-conditioner according to the operation data of the air-conditioner, and estimate the ideal environmental parameters corresponding to the real-time operation parameters according to the real-time operation parameters of the air-conditioner, determine the real-time operation parameters through the operation data of the air-conditioner, and then estimate the ideal environmental parameters of the air-conditioner, thereby improving the accuracy and reliability of the obtained ideal environmental parameters, calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters, and when the matching degree is less than the preset matching degree threshold, obtain the influencing factor set affecting the real-time environmental parameters in the working area of ​​the air-conditioner and at least one influencing factor in the influencing factor set. The data of the sub-factor is used to determine the influence coefficient of the influence factor set on the real-time environmental parameters according to the data of each influence factor in the influence factor set. The influence of the influence factor set on the real-time environmental parameters of the air conditioner can be determined according to the influence factor set of the working area of ​​the air conditioner, and the occurrence of misjudgment of air conditioner failure caused by the influence factor set can be reduced. When the influence coefficient is less than the preset influence coefficient threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters. When the matching degree between the real-time environmental parameters and the ideal environmental parameters is less than the preset matching degree threshold, the current fault information of the air conditioner can be determined, which improves the accuracy and efficiency of determining the fault information of the air conditioner, thereby improving the operating safety and stability of the air conditioner, and enhancing the user's air conditioning usage experience.

[0166] In another optional embodiment, Figure 5 As shown, the specific manner in which the first determining module 302 determines the influence coefficient of the influence factor set on the real-time environmental parameter according to the data of each influence factor in the influence factor set includes:

[0167] Determine the influence degree parameter of each influencing factor on the real-time environmental parameter according to the data of each influencing factor in the influencing factor set;

[0168] Obtaining historical impact data corresponding to each impact factor, and determining a weight coefficient of each impact factor based on the historical impact data;

[0169] Determine the influence coefficient of the influencing factor set on the real-time environmental parameter according to the influence degree parameter of each influencing factor on the real-time environmental parameter and the weight coefficient of each influencing factor;

[0170] Furthermore, the intelligent prediction and processing device for air-conditioning operation failure may also include:

[0171] The updating module 306 is used to update the matching degree between the real-time environment parameters and the ideal environment parameters according to the influence coefficient when the influence coefficient is greater than the influence coefficient threshold.

[0172] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure described in 5 can determine the influence degree parameter of each influencing factor on the real-time environmental parameters according to the data of each influencing factor in the influencing factor set, obtain the historical influence data corresponding to each influencing factor, and determine the weight coefficient of each influencing factor according to the historical influence data. According to the influence degree parameter of each influencing factor on the real-time environmental parameters and the weight coefficient of each influencing factor, the influence coefficient of the influencing factor set on the real-time environmental parameters is determined, and the influence coefficient of the influencing factor set on the real-time environmental parameters can be calculated by determining the weights of different sound factors, thereby improving the accuracy and rationality of the determined influence coefficient, and then the influence of the influencing factor set on the real-time environmental parameters of the air conditioner can be determined according to the influencing factor set of the working area of ​​the air conditioner, which can reduce the occurrence of misjudgment of air-conditioning failure caused by the influencing factor set, thereby improving the operating safety and stability of the air conditioner and enhancing the user's air-conditioning experience.

[0173] In yet another optional embodiment, Figure 5 As shown, the specific manner in which the calculation module 304 determines the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters includes:

[0174] Acquire user data of a target user associated with the air conditioner in a working area of ​​the air conditioner, and determine operation information of the target user on the air conditioner according to the user data;

[0175] Determine the impact degree of the software fault corresponding to the operation information, and determine the software fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters, the real-time operating parameters and the impact degree of the software fault, wherein the current fault information at least includes the software fault information; and / or,

[0176] determining an operating parameter of at least one component of the air conditioner based on the real-time operating parameter of the air conditioner;

[0177] Based on the operating parameters and operation information of each component of the air conditioner, the impact degree of the hardware failure corresponding to the operation information is determined, and based on the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the impact degree of the hardware failure, the hardware failure information of the air conditioner is determined. The current fault information at least includes the hardware failure information.

[0178] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure as described in 5 can obtain the user data of the target user associated with the air-conditioning in the working area of ​​the air-conditioning, and determine the target user's operation data on the air-conditioning, determine the degree of influence of the target user's operation data on the software failure of the air-conditioning, and determine the software failure information of the air-conditioning according to the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the degree of influence of the software failure, and / or determine the operating parameters of at least one component of the air-conditioning, and determine the degree of influence of the hardware failure corresponding to the operation information according to the target user's operation data and the component operating parameters, according to the real-time environmental parameters, ideal environmental parameters, real-time operating parameters and the degree of influence of the hardware failure of the air-conditioning hardware failure information, can determine the degree of influence of the target user's operation data on the software failure and the degree of influence of the hardware failure of the air-conditioning in combination with the target user's operation data on the air-conditioning, and determine the software and hardware failure information of the air-conditioning, thereby improving the accuracy and reliability of the determined air-conditioning failure information, thereby improving the operating safety and stability of the air-conditioning, and enhancing the user's air-conditioning usage experience.

[0179] In yet another optional embodiment, Figure 5 As shown, the intelligent prediction and processing device for air-conditioning operation failure may also include:

[0180] a second determination module 307, configured to determine, after the calculation module 304 determines the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters, the occurrence probability of an associated fault corresponding to the current fault information according to the current fault information of the air conditioner, wherein the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from the current operating mode to the target operating mode, and the target operating mode includes at least one other operating mode different from the current operating mode;

[0181] The second determination module 307 is also used to adjust the air conditioner from the current operation mode to each other operation mode when the probability of occurrence of the associated fault is greater than a preset associated fault probability threshold, and determine the associated fault information of the associated fault corresponding to the current fault information in each other operation mode of the air conditioner.

[0182] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure as described in 5 can determine the probability of occurrence of associated failures corresponding to the current fault information based on the current fault information of the air-conditioning. When the probability of occurrence of associated failures is greater than the preset associated failure probability threshold, the air-conditioning is adjusted from the current operation mode to each other operation mode, and the associated fault information of the associated failure corresponding to the current fault information in each other operation mode of the air-conditioning is determined. The associated fault information of the air-conditioning in other operation modes can be checked through the current fault information to reduce the risk of safety problems caused by hidden faults of the air-conditioning, improve the completeness and efficiency of determining the fault information of the air-conditioning, and improve the operating safety and reliability of the air-conditioning.

[0183] In yet another optional embodiment, Figure 5 As shown, the intelligent prediction and processing device for air-conditioning operation failure may also include:

[0184] The analysis module 308 is used to analyze the current fault information and / or related fault information of the air conditioner, obtain the analysis result, and determine the fault processing condition corresponding to the analysis result, and the analysis result includes the comprehensive fault information of the air conditioner;

[0185] A generating module 309, configured to generate self-help troubleshooting parameters according to the comprehensive fault information of the air conditioner when the fault handling condition meets the preset self-help troubleshooting condition;

[0186] The control module 310 is used to control the air conditioner to perform a self-service troubleshooting operation according to the self-service troubleshooting parameters.

[0187] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure as described in 5 can analyze the current fault information and / or related fault information of the air-conditioner, obtain analysis results, and determine the fault handling conditions corresponding to the analysis results. When the fault handling conditions meet the preset self-service troubleshooting conditions, self-service troubleshooting parameters are generated according to the comprehensive fault information of the air-conditioner, and the air-conditioner is controlled to perform self-service troubleshooting operations according to the self-service troubleshooting parameters. The air-conditioner itself can handle the faults that meet the conditions, thereby improving the efficiency of handling air-conditioning faults, and thereby improving the safety and stability of the air-conditioning operation.

[0188] In yet another optional embodiment, Figure 5 As shown, the intelligent prediction and processing device for air-conditioning operation failure may also include:

[0189] The second acquisition module 311 is used to acquire historical fault data of the air conditioner when the fault handling condition does not meet the preset self-help troubleshooting condition, and determine the fault level reference parameter corresponding to the comprehensive fault information of the air conditioner according to the historical fault data of the air conditioner;

[0190] The second determination module 307 is further used to determine the fault level and fault handling strategy corresponding to the comprehensive fault information of the air conditioner according to the fault level reference parameter and the comprehensive fault information;

[0191] The fault prompt module 312 is used to provide fault prompts based on comprehensive fault information, fault levels and fault handling strategies.

[0192] It can be seen that the intelligent prediction and processing device for air-conditioning operation failure as described in 5 can obtain the historical failure data of the air-conditioning, and determine the fault level reference parameters corresponding to the comprehensive fault information of the air-conditioning based on the historical failure data of the air-conditioning, and determine the fault level and fault handling strategy corresponding to the comprehensive fault information of the air-conditioning based on the fault level reference parameters and the comprehensive failure information, and provide fault prompts based on the comprehensive failure information, failure level and failure handling strategy. It can clarify the fault level and fault handling strategy corresponding to the fault information for reference by failure maintenance personnel, which can improve the efficiency of handling air-conditioning failures, improve the safety and stability of air-conditioning operation, and thus enhance user experience.

[0193] Embodiment 4

[0194] See also Figure 6 , Figure 6 FIG. 1 is a schematic diagram of the structure of another intelligent prediction and processing device for air conditioner operation failure disclosed in an embodiment of the present invention. Figure 6 As shown, the intelligent prediction and processing device for air-conditioning operation failure may include:

[0195] A memory 401 storing executable program codes;

[0196] a processor 402 coupled to the memory 401;

[0197] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the intelligent prediction and processing method for air-conditioning operation failure described in the first embodiment of the present invention or the second embodiment of the present invention.

[0198] Embodiment 5

[0199] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps in the intelligent prediction and processing method for air conditioning operation failure described in Embodiment 1 or Embodiment 2 of the present invention.

[0200] Embodiment 6

[0201] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the intelligent prediction and processing method for air conditioning operation failures described in Example 1 or Example 2.

[0202] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0203] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0204] Finally, it should be noted that the intelligent prediction and processing method and device for air-conditioning operation failure disclosed in the embodiment of the present invention discloses only the preferred embodiments of the present invention, which are only used to illustrate the technical scheme of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that it is still possible to modify the technical schemes recorded in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical schemes from the spirit and scope of the technical schemes of the various embodiments of the present invention.

Claims

1. An intelligent prediction and processing method for air conditioning operation failure, characterized in that: The method comprises: Collecting environmental data of the working area of ​​the air conditioner and operating data of the air conditioner; Determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner; According to the real-time operating parameters of the air conditioner, estimating the ideal environmental parameters corresponding to the real-time operating parameters; The matching degree between the real-time environmental parameters and the ideal environmental parameters is calculated, and when the matching degree is less than a preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

2. The intelligent prediction and processing method for air conditioning operation failure according to claim 1 is characterized in that: When the matching degree is less than a preset matching degree threshold, the method further includes: Acquire a set of influencing factors affecting the real-time environmental parameters in the working area of ​​the air conditioner and data of at least one influencing factor in the set of influencing factors; Determining, according to the data of each of the influencing factors in the influencing factor set, an influence coefficient of the influencing factor set on the real-time environmental parameter; When the influence coefficient is less than a preset influence coefficient threshold, the operation of determining the current fault information of the air conditioner according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters is triggered.

3. The intelligent prediction and processing method for air conditioning operation failure according to claim 2 is characterized in that: The step of determining the influence coefficient of the influencing factor set on the real-time environmental parameter according to the data of each influencing factor in the influencing factor set includes: Determine, according to the data of each of the influencing factors in the influencing factor set, a parameter of the degree of influence of each of the influencing factors on the real-time environmental parameter; Acquire historical impact data corresponding to each of the impact factors, and determine a weight coefficient of each of the impact factors according to the historical impact data; Determining the influence coefficient of the influencing factor set on the real-time environmental parameter according to the influence degree parameter of each influencing factor on the real-time environmental parameter and the weight coefficient of each influencing factor; And, when the influence coefficient is greater than the influence coefficient threshold, the method further includes: The matching degree between the real-time environmental parameter and the ideal environmental parameter is updated according to the influence coefficient.

4. The intelligent prediction and processing method for air-conditioning operation failure according to any one of claims 1 to 3, characterized in that: The determining the current fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter and the real-time operating parameter includes: Acquire user data of a target user associated with the air conditioner in a working area of ​​the air conditioner, and determine operation information of the target user on the air conditioner according to the user data; Determine the software fault impact degree corresponding to the operation information, and determine the software fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter, the real-time operating parameter and the software fault impact degree, wherein the current fault information at least includes the software fault information; and / or, Determining an operating parameter of at least one component of the air conditioner according to the real-time operating parameter of the air conditioner; According to the operating parameters of each component of the air conditioner and the operating information, the degree of impact of the hardware fault corresponding to the operating information is determined, and according to the real-time environmental parameters, the ideal environmental parameters, the real-time operating parameters and the degree of impact of the hardware fault, the hardware fault information of the air conditioner is determined, and the current fault information at least includes the hardware fault information.

5. The intelligent prediction and processing method for air-conditioning operation failure according to claim 4 is characterized in that: After determining the current fault information of the air conditioner according to the real-time environmental parameter, the ideal environmental parameter and the real-time operating parameter, the method further includes: Determining, according to current fault information of the air conditioner, a probability of occurrence of an associated fault corresponding to the current fault information, wherein the associated fault includes a fault associated with the current fault information that occurs in the air conditioner after the air conditioner is adjusted from a current operation mode to a target operation mode, wherein the target operation mode includes at least one other operation mode different from the current operation mode; When the probability of occurrence of the associated fault is greater than a preset associated fault probability threshold, the air conditioner is adjusted from the current operating mode to each of the other operating modes, and associated fault information of the associated fault corresponding to the current fault information of the air conditioner in each of the other operating modes is determined.

6. The intelligent prediction and processing method for air-conditioning operation failure according to claim 5 is characterized in that: The method further comprises: Analyze the current fault information of the air conditioner and / or the associated fault information to obtain an analysis result, and determine a fault processing condition corresponding to the analysis result, wherein the analysis result includes comprehensive fault information of the air conditioner; When the fault handling condition meets the preset self-help troubleshooting condition, generating self-help troubleshooting parameters according to the comprehensive fault information of the air conditioner; The air conditioner is controlled to perform a self-service troubleshooting operation according to the self-service troubleshooting parameters.

7. The intelligent prediction and processing method for air-conditioning operation failure according to claim 6, characterized in that: When the fault handling condition does not meet the preset self-service troubleshooting condition, the method further includes: Acquire historical fault data of the air conditioner, and determine a fault level reference parameter corresponding to comprehensive fault information of the air conditioner according to the historical fault data of the air conditioner; Determining a fault level and a fault handling strategy corresponding to the comprehensive fault information of the air conditioner according to the fault level reference parameter and the comprehensive fault information; A fault prompt is provided according to the comprehensive fault information, the fault level and the fault handling strategy.

8. An intelligent prediction and processing device for air-conditioning operation failure, characterized in that: The device comprises: A collection module, used to collect environmental data of the working area of ​​the air conditioner and operating data of the air conditioner; A first determination module, configured to determine the real-time environmental parameters corresponding to the working area of ​​the air conditioner according to the environmental data, and to determine the real-time operating parameters of the air conditioner according to the operating data of the air conditioner; An estimation module, used for estimating ideal environmental parameters corresponding to the real-time operating parameters of the air conditioner according to the real-time operating parameters of the air conditioner; A calculation module is used to calculate the matching degree between the real-time environmental parameters and the ideal environmental parameters. When the matching degree is less than a preset matching degree threshold, the current fault information of the air conditioner is determined according to the real-time environmental parameters, the ideal environmental parameters and the real-time operating parameters.

9. An intelligent prediction and processing device for air conditioner operation failure, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent prediction and processing method for air conditioning operation failure as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the intelligent prediction and processing method for air-conditioning operation failure according to any one of claims 1-7.

Images