Air conditioner operation fault prediction method and device based on user parameters and air conditioner parameters

Abstract

The invention discloses an air conditioner operation fault prediction method and device based on user parameters and air conditioner parameters. The method comprises the steps that the user parameters of users facing the air conditioner during operation and the operation parameters of the air conditioner are obtained; judging whether the current operation condition of the air conditioner meets a preset fault condition or not according to the user parameters of the user and the operation parameters of the air conditioner; and when it is judged that the current operation condition of the air conditioner meets the preset fault condition, the predicted fault condition of the air conditioner is predicted according to the user parameters of the user and the operation parameters of the air conditioner. Therefore, by implementing the method, the prediction accuracy of the fault condition during air conditioner operation can be improved, so that the accuracy and timeliness of fault prevention on the air conditioner can be improved through the accurately predicted fault condition during air conditioner operation subsequently; and the situation that a user cannot start the air conditioner to work due to the air conditioner fault is reduced, and the intelligence of the air conditioner is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning, and in particular to a method and device for predicting air conditioning operation failure based on user parameters and air conditioning parameters. Background Art

[0002] As air conditioners are used more frequently, they malfunction more and more frequently.

[0003] At present, when the air conditioner is running, the main way to detect whether the air conditioner has a fault is to first pause the air conditioner, then detect whether the components of the air conditioner have a fault, and when a fault is detected, prevent the air conditioner from failing. However, in real life, once the air conditioner is in the state of detecting whether a fault has occurred, it cannot be started to work, which may easily lead to the user's demand for the air conditioner not being met, and its intelligence needs to be improved. It can be seen that it is particularly important to propose a technical solution to improve the prediction accuracy of air conditioner operation faults. Summary of the invention

[0004] The present invention provides an air-conditioning operation fault prediction method and device based on user parameters and air-conditioning parameters, which can improve the prediction accuracy of fault conditions during air-conditioning operation, thereby facilitating the subsequent improvement of the accuracy of air-conditioning fault prevention through accurately predicted fault conditions during air-conditioning operation.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a method for predicting air conditioner operation failure based on user parameters and air conditioner parameters, the method comprising:

[0006] Acquire user parameters of the user facing the air conditioner during operation and operating parameters of the air conditioner;

[0007] Determining whether a current operating condition of the air conditioner meets a preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner;

[0008] When it is determined that the current operating condition of the air conditioner meets the preset fault condition, a predicted fault condition of the air conditioner is predicted according to the user parameters of the user and the operating parameters of the air conditioner.

[0009] As an optional implementation, in the first aspect of the present invention, the predicted fault condition of the air conditioner is used to represent the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0010] The operating parameters of the air conditioner include actual operating parameters of the air conditioner and theoretical operating parameters of the air conditioner, and the user parameters of the user include actual user parameters of the user obtained by operating the air conditioner according to the actual operating parameters of the air conditioner and theoretical user parameters of the user obtained by operating the air conditioner according to the theoretical operating parameters of the air conditioner;

[0011] And, predicting the predicted fault condition of the air conditioner according to the user parameter of the user and the operating parameter of the air conditioner includes:

[0012] Performing difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result, wherein the difference analysis result includes a difference corresponding to each of the multiple information types;

[0013] Filter out one of the information types with the largest corresponding difference value from all the information types as the target information type;

[0014] The predicted fault type of the air conditioner is determined according to the target information type, and the target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type.

[0015] As an optional implementation manner, in the first aspect of the present invention, determining the predicted fault type of the air conditioner according to the target information type includes:

[0016] According to the target information type, searching for one of the preset fault types corresponding to the target information type from the set of fault types as the predicted fault type of the air conditioner;

[0017] And, determining the target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type includes:

[0018] The target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type and the fault degree corresponding to each of the plurality of preset difference value intervals.

[0019] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0020] generating fault prevention processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0021] performing a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner;

[0022] The performing of a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner includes:

[0023] When the target fault degree contained in the fault prevention processing information of the air conditioner is less than or equal to a preset fault degree threshold, directly performing a fault prevention processing operation on the air conditioner;

[0024] When the target fault degree contained in the fault prevention processing information of the air conditioner is greater than the preset fault degree threshold, the target operating components matching the predicted fault type among all operating components of the air conditioner are suspended, and the fault prevention processing operation is performed on the air conditioner after suspending the target operating components.

[0025] As an optional implementation, in the first aspect of the present invention, the user parameters of the user include the current user parameters of the user, and the operating parameters of the air conditioner include the current operating parameters of the air conditioner;

[0026] And, judging whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameter of the user and the operating parameter of the air conditioner includes:

[0027] Analyzing the target probability of failure of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner;

[0028] Determining whether a target probability of the air conditioner failing is greater than or equal to a predetermined probability threshold;

[0029] If it is determined that the target probability of the air conditioner failing is greater than or equal to the probability threshold, it is determined that the current operating condition of the air conditioner meets a preset failure condition.

[0030] As an optional implementation, in the first aspect of the present invention, the user parameters of the user further include the historical user parameters of the user, and the operating parameters of the air conditioner further include the historical operating parameters of the air conditioner;

[0031] And, the method further comprises:

[0032] If it is determined that the target probability of the air conditioner malfunctioning is less than the probability threshold, analyzing historical malfunction situations of the air conditioner malfunctioning according to historical user parameters of the user and historical operating parameters of the air conditioner;

[0033] Determining whether the historical fault condition of the air conditioner fault is used to indicate that the number of historical faults of the air conditioner faults within a preset time period in the past is greater than or equal to a preset number threshold;

[0034] If it is determined that the historical fault conditions of the air conditioner are used to indicate that the number of historical faults of the air conditioner within the past preset time period is greater than or equal to the preset number threshold, it is determined that the current operating condition of the air conditioner meets the preset fault condition.

[0035] As an optional implementation, in the first aspect of the present invention, the target probability of the air conditioner malfunctioning includes a first probability of the air conditioner malfunctioning obtained by analyzing the user parameters of the user and a second probability of the air conditioner malfunctioning obtained by analyzing the operating parameters of the air conditioner;

[0036] And, the step of determining whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold comprises:

[0037] respectively determining whether the first possibility is greater than or equal to a first preset possibility threshold and whether the second possibility is greater than or equal to a second preset possibility threshold;

[0038] If it is determined that the first probability is less than the first preset probability threshold, and the second probability is less than the second preset probability threshold, then it is determined that the target probability of the air conditioner failure is less than the predetermined probability threshold;

[0039] If it is determined that the first possibility is greater than or equal to the first preset possibility threshold, and / or the second possibility is greater than or equal to the second preset possibility threshold, then it is determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold.

[0040] A second aspect of the present invention discloses an air conditioning operation fault prediction device based on user parameters and air conditioning parameters, the device comprising:

[0041] An acquisition module, used to acquire user parameters of the user facing the air conditioner during operation and operating parameters of the air conditioner;

[0042] A judgment module, used for judging whether the current operating condition of the air conditioner meets a preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner;

[0043] A prediction module is used to predict the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner when the judgment module determines that the current operating condition of the air conditioner meets the preset fault condition.

[0044] As an optional implementation, in the second aspect of the present invention, the predicted fault condition of the air conditioner is used to represent the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0045] The operating parameters of the air conditioner include actual operating parameters of the air conditioner and theoretical operating parameters of the air conditioner, and the user parameters of the user include actual user parameters of the user obtained by operating the air conditioner according to the actual operating parameters of the air conditioner and theoretical user parameters of the user obtained by operating the air conditioner according to the theoretical operating parameters of the air conditioner;

[0046] Furthermore, the prediction module predicts the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner, specifically including:

[0047] Performing difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result, wherein the difference analysis result includes a difference corresponding to each of the multiple information types;

[0048] Filter out one of the information types with the largest corresponding difference value from all the information types as the target information type;

[0049] The predicted fault type of the air conditioner is determined according to the target information type, and the target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type.

[0050] As an optional implementation, in the second aspect of the present invention, the prediction module determines the predicted fault type of the air conditioner according to the target information type in a manner that specifically includes:

[0051] According to the target information type, searching for one of the preset fault types corresponding to the target information type from the set of fault types as the predicted fault type of the air conditioner;

[0052] And, the prediction module determines the target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type, specifically including:

[0053] The target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type and the fault degree corresponding to each of the plurality of preset difference value intervals.

[0054] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0055] A generating module, configured to generate fault prevention processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0056] an execution module, configured to execute a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner;

[0057] The execution module executes the fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner in a manner specifically including:

[0058] When the target fault degree contained in the fault prevention processing information of the air conditioner is less than or equal to a preset fault degree threshold, directly performing a fault prevention processing operation on the air conditioner;

[0059] When the target fault degree contained in the fault prevention processing information of the air conditioner is greater than the preset fault degree threshold, the target operating components matching the predicted fault type among all operating components of the air conditioner are suspended, and the fault prevention processing operation is performed on the air conditioner after suspending the target operating components.

[0060] As an optional implementation, in the second aspect of the present invention, the user parameters of the user include the current user parameters of the user, and the operating parameters of the air conditioner include the current operating parameters of the air conditioner;

[0061] And, the judgment module judges whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner, specifically including:

[0062] Analyzing the target probability of failure of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner;

[0063] Determining whether a target probability of the air conditioner failing is greater than or equal to a predetermined probability threshold;

[0064] If it is determined that the target probability of the air conditioner failing is greater than or equal to the probability threshold, it is determined that the current operating condition of the air conditioner meets a preset failure condition.

[0065] As an optional implementation, in the second aspect of the present invention, the user parameters of the user further include the historical user parameters of the user, and the operating parameters of the air conditioner further include the historical operating parameters of the air conditioner;

[0066] And, the device further comprises:

[0067] an analysis module, configured to analyze historical failure conditions of the air conditioner according to historical user parameters of the user and historical operating parameters of the air conditioner if the determination module determines that the target probability of the air conditioner failure is less than the probability threshold;

[0068] The judgment module is further used to judge whether the historical fault situation of the air conditioner fault is used to indicate that the number of historical faults of the air conditioner faults in the past preset time period is greater than or equal to a preset number threshold;

[0069] A determination module is used to determine that the current operating condition of the air conditioner meets the preset fault condition if the judgment module determines that the historical fault condition of the air conditioner is used to indicate that the number of historical faults of the air conditioner within the preset time period in the past is greater than or equal to the preset number threshold.

[0070] As an optional implementation, in the second aspect of the present invention, the target probability of the air conditioner malfunctioning includes a first probability of the air conditioner malfunctioning obtained by analyzing the user parameters of the user and a second probability of the air conditioner malfunctioning obtained by analyzing the operating parameters of the air conditioner;

[0071] And, the method in which the judgment module judges whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold specifically includes:

[0072] respectively determining whether the first possibility is greater than or equal to a first preset possibility threshold and whether the second possibility is greater than or equal to a second preset possibility threshold;

[0073] If it is determined that the first probability is less than the first preset probability threshold, and the second probability is less than the second preset probability threshold, then it is determined that the target probability of the air conditioner failure is less than the predetermined probability threshold;

[0074] If it is determined that the first possibility is greater than or equal to the first preset possibility threshold, and / or the second possibility is greater than or equal to the second preset possibility threshold, then it is determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold.

[0075] The third aspect of the present invention discloses another air-conditioning operation fault prediction device based on user parameters and air-conditioning parameters, the device comprising:

[0076] A memory storing executable program code;

[0077] a processor coupled to the memory;

[0078] The processor calls the executable program code stored in the memory to execute the air conditioning operation fault prediction method based on user parameters and air conditioning parameters disclosed in the first aspect of the present invention.

[0079] The fourth aspect 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 air conditioning operation fault prediction method based on user parameters and air conditioning parameters disclosed in the first aspect of the present invention.

[0080] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0081] In the embodiment of the present invention, the user parameters of the user facing the air conditioner when the air conditioner is running and the operating parameters of the air conditioner are obtained; according to the user parameters of the user and the operating parameters of the air conditioner, it is judged whether the current operating condition of the air conditioner meets the preset fault condition; when it is judged that the current operating condition of the air conditioner meets the preset fault condition, the predicted fault condition of the air conditioner is predicted according to the user parameters of the user facing the air conditioner when the air conditioner is running. It can be seen that the implementation of the present invention can judge whether the air conditioner has an operating fault according to the user parameters of the user facing the air conditioner when the air conditioner is running and the operating parameters of the air conditioner, which can improve the accuracy of judging whether the air conditioner has an operating fault, and when it is accurately judged that the air conditioner has an operating fault, the predicted fault condition of the air conditioner is predicted according to the user parameters and the operating parameters, which can improve the prediction accuracy of the fault condition when the air conditioner is running, thereby facilitating the subsequent improvement of the accuracy and timeliness of fault prevention of the air conditioner through the accurately predicted fault condition when the air conditioner is running, and is conducive to reducing the situation where the user cannot start the air conditioner to work due to the air conditioner fault, thereby facilitating the improvement of the intelligence of the air conditioner. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] 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.

[0083] Figure 1 It is a schematic diagram of a scenario to which an air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention is applicable;

[0084] Figure 2 It is a flow chart of an air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention;

[0085] Figure 3 It is a flow chart of another method for predicting air-conditioning operation failure based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention;

[0086] Figure 4It is a structural diagram of an air-conditioning operation fault prediction device based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention;

[0087] Figure 5 It is a structural schematic diagram of another air-conditioning operation fault prediction device based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention;

[0088] Figure 6 It is a structural diagram of another air-conditioning operation fault prediction device based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0089] 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.

[0090] 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.

[0091] 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.

[0092] The present invention discloses a method and device for predicting air conditioner operation failure based on user parameters and air conditioner parameters, which can judge whether the air conditioner has an operation failure according to the user parameters of the user facing the air conditioner and the operation parameters of the air conditioner obtained when the air conditioner is in operation, and can improve the accuracy of judging whether the air conditioner has an operation failure, and when the air conditioner is accurately judged to have an operation failure, the predicted failure situation of the air conditioner is predicted according to the user parameters and the operation parameters, and can improve the prediction accuracy of the failure situation when the air conditioner is in operation, so as to improve the accuracy and timeliness of the failure prevention of the air conditioner through the subsequent accurate prediction of the failure situation when the air conditioner is in operation, and to reduce the situation where the user cannot start the air conditioner to work due to the failure of the air conditioner, and thus to improve the intelligence of the air conditioner. The following are detailed descriptions respectively.

[0093] In order to better understand the air conditioner operation fault prediction method and device based on user parameters and air conditioner parameters described in the present invention, the scenario to which the air conditioner operation fault prediction method based on user parameters and air conditioner parameters is applicable is first described. The scenario to which the method is applicable is specifically a scenario in which the user parameters of users in the area where the air conditioner is located need to be adjusted through the air conditioner, such as a home scenario. Specifically, taking the home scenario as an example, the scenario can be as follows: Figure 1 As shown, Figure 1 Schematic diagram of a scenario to which an air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters disclosed in an embodiment of the present invention is applicable. Figure 1 As shown, the scene schematic diagram takes the living room area in the home scene as an example for illustration, in which a smart air conditioner is placed and a user is present. Furthermore, furniture, such as a sofa, may also be placed in the living room area.

[0094] It should be noted that Figure 1 The scenario diagram shown is only for showing one scenario to which the air-conditioning operation fault prediction method and device based on user parameters and air-conditioning parameters are applicable, and it is not used to limit other scenarios to which the air-conditioning operation fault prediction method and device based on user parameters and air-conditioning parameters are applicable, and Figure 1 The smart air conditioner involved in Figure 1 The scenario schematic diagram shown does not limit the shape, size, installation location, etc. of the smart air conditioner; Figure 1 There is no limitation on the existence form of the users involved, whether the sofa exists and its existence form, etc.

[0095] The above describes an example of one of the scenarios to which the air-conditioning operation fault prediction method and device based on user parameters and air-conditioning parameters are applicable. The following describes the air-conditioning operation fault prediction method and device based on user parameters and air-conditioning parameters in detail.

[0096] Embodiment 1

[0097] See also Figure 2 , Figure 2 1 is a flow chart of an air conditioning operation fault prediction method based on user parameters and air conditioning parameters disclosed in an embodiment of the present invention. Figure 2 The air conditioning operation fault prediction method based on user parameters and air conditioning parameters described above can be applied to an air conditioning operation fault prediction device based on user parameters and air conditioning parameters, wherein the device may include a fault prediction device or a fault prediction server, wherein the fault prediction server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. Figure 2 As shown, the air conditioning operation fault prediction method based on user parameters and air conditioning parameters may include the following operations:

[0098] 101. Obtain user parameters of the user facing the air conditioner when the air conditioner is running and operating parameters of the air conditioner.

[0099] In the embodiment of the present invention, optionally, the user parameters of the user may include the user's voice information (such as: the user asks why the air conditioner has a poor cooling effect), the user's behavioral action information (such as: the user rubs his hands, the user puts on a coat, etc.), the user's facial expression information, the user's actual somatosensory information and the user's expected somatosensory information for the air conditioner. Further optionally, when the user parameters of the user include at least the user's actual somatosensory information and the user's expected somatosensory information for the air conditioner, the user parameters of the user may also include the information similarity between the user's actual somatosensory information and the user's expected somatosensory information for the air conditioner. Optionally, the operating parameters of the air conditioner may include one or more combinations of the operating temperature of the air conditioner, the operating wind speed of the air conditioner, the operating wind volume of the air conditioner, the operating wind direction of the air conditioner, and the operating humidity of the air conditioner, which are not limited in the embodiment of the present invention.

[0100] 102. Determine whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner.

[0101] In an embodiment of the present invention, optionally, the current operating conditions of the air conditioner may include conditions corresponding to the operation of the air conditioner according to the operating parameters of the air conditioner, and the preset fault conditions may include conditions corresponding to the possibility of a fault occurring during the operation of the air conditioner (such as: the probability of a fault occurring), which is not limited in the embodiment of the present invention.

[0102] In the embodiment of the present invention, optionally, the operating parameters of the air conditioner may include the actual operating parameters of the air conditioner (such as: the actual operating temperature of the air conditioner) and the theoretical operating parameters of the air conditioner, and the user parameters of the user may include the actual user parameters of the user obtained by the air conditioner running according to the actual operating parameters of the air conditioner (such as: the actual perceived temperature of the user) and the theoretical user parameters of the user obtained by the air conditioner running according to the theoretical operating parameters of the air conditioner. Among them, the theoretical operating parameters of the air conditioner and the theoretical user parameters used may be obtained by simulating the operating conditions of the air conditioner using numerical twin technology. Specifically, when the actual operating parameters of the air conditioner do not meet the theoretical operating parameters of the air conditioner, it can be determined that the air conditioner is operating abnormally (that is, the current operating conditions of the air conditioner meet the preset fault conditions); when the actual user parameters of the user do not meet the theoretical user parameters of the user, it can also be determined that the air conditioner is operating abnormally, which is not limited in the embodiment of the present invention.

[0103] In an embodiment of the present invention, the current operating condition of the air conditioner may further include conditions corresponding to the life of the air conditioner (the life of the air conditioner may include the life of air conditioner components and / or the life of the air conditioner) and / or the use performance of the air conditioner (the use performance of the air conditioner may include the use performance of air conditioner components and / or the use performance of the air conditioner). Specifically, when the air conditioner is running, it may be detected whether the actual life of the air conditioner meets the theoretical life of the air conditioner. When it is detected that it does not meet, it is determined that the current operating condition of the air conditioner does not meet the preset fault condition; it may also be detected whether the actual use performance of the air conditioner meets the attenuation curve corresponding to the theoretical use performance of the air conditioner, or whether it meets the attenuation formula corresponding to the theoretical use performance of the air conditioner. When it is detected that it does not meet, it is determined that the current operating condition of the air conditioner does not meet the preset fault condition.

[0104] In the embodiment of the present invention, if the judgment result of step 102 is yes, step 103 is executed; if the judgment result of step 102 is no, step 104 can be executed, or the process can be terminated, which is not limited in the embodiment of the present invention.

[0105] 103. Predict the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner.

[0106] In an embodiment of the present invention, optionally, the predicted fault condition of the air conditioner can be used to indicate the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner. The predicted fault type of the air conditioner includes a combination of one or more of the temperature parameter fault type of the air conditioner, the air outlet parameter fault type of the air conditioner, and the humidity parameter fault type of the air conditioner, which is not limited in the embodiment of the present invention.

[0107] 104. Control the air conditioner to operate according to its operating parameters.

[0108] It can be seen that implementation Figure 2The described air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters can determine whether the air-conditioning has an operation fault according to the user parameters of the user facing the air-conditioning and the operation parameters of the air-conditioning obtained when the air-conditioning is running, and can improve the accuracy of judging whether the air-conditioning has an operation fault. When it is accurately determined that the air-conditioning has an operation fault, the predicted fault condition of the air-conditioning is predicted according to the user parameters and the operation parameters, and can improve the accuracy of predicting the fault condition when the air-conditioning is running, which is beneficial to subsequently improving the accuracy and timeliness of air-conditioning fault prevention through accurately predicted fault conditions during air-conditioning operation, and is beneficial to reducing the occurrence of situations where users are unable to start the air-conditioning for operation due to air-conditioning faults, and is beneficial to improving the intelligence of the air-conditioning.

[0109] In an optional embodiment, after predicting the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner, the method may further include:

[0110] Determine the fault parameters of the predicted fault components of the air conditioner according to the predicted fault condition of the air conditioner;

[0111] Obtaining standard component parameters of predicted faulty components;

[0112] Determine the failure prevention requirements of the predicted failure component based on the standard component parameters of the predicted failure component and the failure parameters of the predicted failure component;

[0113] Generate a failure prevention coefficient of the predicted failure component according to the failure prevention demand of the predicted failure component;

[0114] According to the failure prevention coefficient of the predicted failure component, preventive processing is performed on the failure parameters of the predicted failure component.

[0115] In an embodiment of the present invention, the predicted fault component of the air conditioner is a component predicted to fail among all components of the air conditioner. Optionally, the predicted fault component of the air conditioner may include a combination of one or more of the temperature control component of the air conditioner, the wind speed control component of the air conditioner, the wind direction control component of the air conditioner, the air volume control component of the air conditioner, and the humidity control component of the air conditioner. Optionally, the fault parameters of the predicted fault component may include component fault parameters of the predicted fault component and / or circuit fault parameters of the circuit to which the predicted fault component is connected. Among them, the component fault parameters of the predicted fault component may include a combination of one or more of component aging parameters, component displacement parameters of the predicted fault component, and component damage parameters of the predicted fault component. Among them, the circuit fault parameters of the circuit to which the predicted fault component is connected may include a combination of one or more of the route aging parameters of the circuit, the route displacement parameters of the circuit, and the route damage parameters of the circuit, etc., which are not limited in the embodiment of the present invention.

[0116] In an embodiment of the present invention, optionally, standard component parameters for predicting a faulty component may include a combination of one or more of the component position of the predicted faulty component, a standard circuit route required for the component to be connected, component shape, component volume, component surface area, component surface roughness, and component material, etc., which is not limited in the embodiment of the present invention.

[0117] In an embodiment of the present invention, optionally, the fault prevention demand of the predicted fault component may include the demand for replacing the predicted fault component and / or the demand for adjusting the predicted fault component (such as: adjusting the current position of the predicted fault component back to the standard position of the predicted fault component), which is not limited in the embodiment of the present invention.

[0118] It can be seen that this optional embodiment can accurately determine the fault parameters of the predicted fault components of the air conditioner according to the predicted fault situation of the air conditioner, and determine the fault prevention requirements of the predicted fault components according to the acquired standard component parameters of the predicted fault components and the accurately determined fault parameters of the predicted fault components, which can improve the accuracy and reliability of determining the fault prevention requirements of the predicted fault components, and generate a fault prevention coefficient of the predicted fault component according to the accurately determined fault prevention requirements of the predicted fault components, which can improve the accuracy of generating the fault prevention coefficient, thereby facilitating improving the accuracy and timeliness of preventive processing of the fault parameters of the predicted fault components according to the accurately generated fault prevention coefficient of the predicted fault components, reducing the occurrence of errors in the generation of the fault prevention coefficient that lead to errors in the prevention of the air conditioner, and further facilitating reducing the occurrence of secondary failures of the predicted fault components due to errors in the prevention of the air conditioner.

[0119] In yet another optional embodiment, after predicting the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner, the method may further include:

[0120] Get the failure frequency of air conditioner failure;

[0121] Detecting a frequency threshold interval of a fault frequency at which a fault of the air conditioner occurs;

[0122] If it is detected that the fault frequency of the air conditioner fault is within the first preset frequency threshold interval, the fault prediction strength required for predicting the air conditioner is increased, and the fault prediction of the air conditioner is performed according to the increased fault prediction strength;

[0123] If it is determined that the fault frequency of the air conditioner fault is within the second preset frequency threshold interval, a fault prediction is performed on the air conditioner according to the acquired current fault prediction strength of the air conditioner;

[0124] If it is determined that the fault frequency of the air conditioner fault is within the third preset frequency threshold interval, the fault prediction strength required for predicting the air conditioner is reduced, and the air conditioner fault is predicted according to the reduced fault prediction strength.

[0125] In the embodiment of the present invention, optionally, the fault frequency of the air conditioner fault may include the number of times the air conditioner has failed in the past preset time period (such as: from the time the user installed the air conditioner to the present). Optionally, the interval minimum value of the first preset frequency threshold interval is greater than the interval maximum value of the second preset frequency threshold interval, and the interval minimum value of the second preset frequency threshold interval is greater than the interval maximum value of the third preset frequency threshold interval. Optionally, the fault prediction strength (such as: the number of fault predictions, the fault prediction frequency, etc.) can be the strength of predicting whether a fault will occur during the operation of the air conditioner within a set prediction time period, which is not limited in the embodiment of the present invention.

[0126] It can be seen that this optional embodiment is capable of detecting the frequency threshold interval in which the acquired fault frequency of the air conditioner fails, and can improve the detection accuracy and reliability of the frequency threshold interval in which the fault frequency of the air conditioner fails, and when it is detected that it is in the first preset frequency threshold interval, it is selected to increase the fault prediction strength required for predicting the air conditioner and predict the air conditioner according to the increased fault prediction strength; when it is detected that it is in the second preset frequency threshold interval, it is selected to predict the air conditioner according to the current fault prediction strength of the air conditioner obtained; when it is detected that it is in the third preset frequency threshold interval, it is selected to reduce the fault prediction strength required for predicting the air conditioner and predict the air conditioner according to the reduced fault prediction strength, which can improve the accuracy of determining the fault prediction strength of the air conditioner by accurately detecting the frequency threshold interval in which the fault frequency is located, and intelligently select the corresponding fault prediction strength to predict the air conditioner, which is conducive to improving the efficiency and speed of subsequent prediction of air conditioner failures.

[0127] Embodiment 2

[0128] See also Figure 3 , Figure 3 1 is a flow chart of an air conditioning operation fault prediction method based on user parameters and air conditioning parameters disclosed in an embodiment of the present invention. Figure 3 The air conditioning operation fault prediction method based on user parameters and air conditioning parameters described above can be applied to an air conditioning operation fault prediction device based on user parameters and air conditioning parameters, wherein the device may include a fault prediction device or a fault prediction server, wherein the fault prediction server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. Figure 3 As shown, the air conditioning operation fault prediction method based on user parameters and air conditioning parameters may include the following operations:

[0129] 201. Obtain user parameters of the user facing the air conditioner when the air conditioner is running and operating parameters of the air conditioner.

[0130] 202. Determine whether a current operating condition of the air conditioner meets a preset fault condition based on the user parameters of the user and the operating parameters of the air conditioner.

[0131] In the embodiment of the present invention, if the judgment result of step 202 is yes, step 203 is executed; if the judgment result of step 202 is no, step 209 can be executed, or the present process can be terminated, which is not limited in the embodiment of the present invention.

[0132] 203. Perform difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result.

[0133] In the embodiment of the present invention, optionally, the difference analysis result may include the difference corresponding to each information type in the multiple information types, and the difference may include a first type of difference and a second type of difference, the first type of difference may include a difference obtained by comparing the actual operating parameters of the air conditioner with the theoretical operating parameters of the air conditioner, and the second type of difference may include a difference obtained by comparing the actual user parameters of the user with the theoretical user parameters of the user. Optionally, the information type may include a combination of one or more of a temperature type, a wind speed type, a wind direction type, an air volume type, and a humidity type. Optionally, the information difference may be 70%, 80%, or any other numerical value analyzed, which is not limited in the embodiment of the present invention. , the embodiment of the present invention is not limited.

[0134] For example, assuming that the actual perception information indicates that the user does not feel the wind, but the predicted perception information indicates that the user needs to feel the wind, it can be analyzed that the information difference corresponding to each wind information type in the wind speed information type, wind direction information type and wind volume information type is 1.

[0135] 204. Select one of all information types with the largest corresponding difference value as the target information type.

[0136] 205. Determine a predicted fault type of the air conditioner according to the target information type.

[0137] In an embodiment of the present invention, specifically, first target sub-information matching the target information type in all first sub-information contained in actual information (the actual information may include actual operating parameters of the air conditioner and actual user parameters of the user) and second target sub-information matching the target information type in all second sub-information contained in theoretical information (theoretical information may include theoretical operating parameters of the air conditioner and theoretical user parameters of the user) can be input into a pre-trained fault type identification model for type identification to obtain a predicted fault type of the air conditioner, which is not limited in the embodiment of the present invention.

[0138] For example, assuming that the target information type is temperature type, all actual temperature-related data actually perceived by the user in the actual information and all theoretical temperature-related data that the user theoretically needs to perceive in the theoretical information can be input into the above-mentioned fault type identification model for type identification to obtain the predicted fault type of the air conditioner (such as: the fault type corresponding to the exhaustion of the refrigerant in the air conditioner).

[0139] 206. Determine a target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type.

[0140] In the embodiment of the present invention, optionally, the target fault degree corresponding to the predicted fault type may be the component fault degree of the predicted fault component corresponding to the predicted fault type. The component fault degree may be a quotient obtained by dividing the component fault parameter of the predicted fault component by the component standard parameter of the predicted fault component, which is not limited in the embodiment of the present invention.

[0141] 207. Control the air conditioner to operate according to its operating parameters.

[0142] In the embodiment of the present invention, for other descriptions of step 201, step 202 and step 207, please refer to the detailed description of step 101, step 102 and step 104 in the first embodiment, which is not limited in the embodiment of the present invention.

[0143] It can be seen that implementation Figure 3The described air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters can determine whether the air-conditioning has an operation fault according to the user parameters of the user facing the air-conditioning and the operation parameters of the air-conditioning obtained when the air-conditioning is running, and can improve the accuracy of judging whether the air-conditioning has an operation fault. When it is accurately determined that the air-conditioning has an operation fault, the predicted fault condition of the air-conditioning is predicted according to the user parameters and the operation parameters, and can improve the accuracy of predicting the fault condition when the air-conditioning is running, which is beneficial to subsequently improving the accuracy and timeliness of air-conditioning fault prevention through accurately predicted fault conditions during air-conditioning operation, and is beneficial to reducing the occurrence of situations where users are unable to start the air-conditioning for operation due to air-conditioning faults, and is beneficial to improving the intelligence of the air-conditioning. In addition, it is also possible to perform a difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result, and select one of all the information types contained in the difference analysis result with the largest corresponding difference value as the target information type, so as to improve the screening accuracy of the target information type and reduce the occurrence of subsequent processing of information types that do not need to be screened. The predicted fault type of the air conditioner is determined according to the target information type, which can improve the accuracy of determining the predicted fault type of the air conditioner, and the target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type, which can improve the accuracy of determining the target fault degree corresponding to the predicted fault type, thereby facilitating improving the prediction accuracy and reliability of fault conditions during air conditioning operation (the fault conditions include predicted fault types and target fault degrees corresponding to the predicted fault types).

[0144] In an optional embodiment, determining the predicted fault type of the air conditioner according to the target information type in step 205 may include:

[0145] According to the target information type, one of the preset fault type sets corresponding to the target information type is searched as the predicted fault type of the air conditioner.

[0146] In the embodiment of the present invention, optionally, a preset fault type set may be stored in the above-mentioned fault type identification model, and the preset fault type set may include a combination of one or more of a temperature fault type subset, a wind speed fault type subset, a wind volume fault type subset, a wind direction fault type subset, and a humidity fault type subset. Wherein, each parameter type subset in the fault type set includes one or more of such parameter types, which is not limited in the embodiment of the present invention.

[0147] For example, the temperature fault type subset includes one or more temperature fault types (eg, the refrigerant is consumed, the refrigerant life reaches an upper limit, etc.).

[0148] It can be seen that this optional embodiment can search for the predicted fault type of the air conditioner corresponding to the target information type from a preset fault type set according to the target information type, which can improve the search accuracy and reliability of the predicted fault type of the air conditioner and reduce the occurrence of subsequent processing of fault types that do not need to be found.

[0149] In another optional embodiment, determining the target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type in the above step 206 may include:

[0150] The target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type and the fault degree corresponding to each difference value interval in the preset plurality of difference value intervals.

[0151] In the embodiment of the present invention, optionally, the number of intervals of all preset difference value intervals may be 2, 3, or any other preset value. Optionally, all interval values ​​of each difference value interval and all interval values ​​of the remaining difference value intervals in all difference value intervals except the difference value interval do not have the same value, which is not limited in the embodiment of the present invention.

[0152] For example, it is assumed that there is a difference value interval A and a difference value interval B. The intersection between the difference value interval A and the difference value interval B is empty.

[0153] It can be seen that this optional embodiment can determine the target fault degree corresponding to the predicted fault type of the air conditioner based on the target difference corresponding to the target information type and the fault degree corresponding to the preset multiple difference value intervals, and can improve the accuracy and reliability of determining the target fault degree corresponding to the predicted fault type, thereby facilitating the subsequent improvement of the accuracy and timeliness of prevention of the air conditioner through the accurately determined target fault degree.

[0154] In this optional embodiment, as an optional embodiment, the method may further include:

[0155] generating fault prevention processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0156] According to the fault prevention processing information of the air conditioner, a fault prevention processing operation is performed on the air conditioner.

[0157] In an embodiment of the present invention, optionally, the fault prevention processing information can be stored in the background service platform of the air conditioner (such as: the air conditioner intelligent management software in the smart phone). Among them, the fault prevention processing information can at least include fault prevention processing measures for the air conditioner fault situation analyzed according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner. Among them, the fault prevention processing measures can include preventive processing suggestions, and the preventive processing suggestions can include processing suggestions for users to perform fault prevention on the air conditioner by themselves, and / or processing suggestions for dispatching air conditioner prevention personnel to perform fault prevention on the air conditioner, which is not limited in the embodiment of the present invention.

[0158] It can be seen that this optional implementation method can generate fault prevention and processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner, thereby improving the accuracy and timeliness of the generation of the fault prevention and processing information, and performing fault prevention and processing operations on the air conditioner according to the accurately generated fault prevention and processing information, thereby improving the accuracy and timeliness of the fault prevention and processing operations performed on the air conditioner, and through timely preventive processing operations, it can reduce the occurrence of situations where users are unable to start the air conditioner to work due to air conditioner failure, thereby helping to improve the intelligence of the air conditioner and enhance the user experience.

[0159] In this optional implementation, optionally, performing a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner may include:

[0160] When the target fault degree contained in the fault prevention processing information of the air conditioner is less than or equal to the preset fault degree threshold, directly performing the fault prevention processing operation on the air conditioner;

[0161] When the target fault degree contained in the fault prevention processing information of the air conditioner is greater than the preset fault degree threshold, the target operating components matching the predicted fault type among all operating components of the air conditioner are suspended, and the fault prevention processing operation is performed on the air conditioner after the target operating components are suspended.

[0162] In the embodiment of the present invention, optionally, all operating components of the air conditioner can be operated simultaneously, or a part of the operating components can be selected to operate, and the remaining operating components can be stopped. Optionally, the preset fault degree threshold can be 70%, or 80%, or any other set value, which is not limited in the embodiment of the present invention.

[0163] It can be seen that this optional implementation method can also choose to directly perform fault prevention processing operations on the air conditioner when the target fault degree contained in the fault prevention processing information of the air conditioner is relatively small, which can improve the accuracy and processing efficiency of performing fault prevention processing operations on the air conditioner, and there is no need to suspend the operating state of the air conditioner, which is beneficial to ensure that the air conditioner is in an operating state while reducing the possibility of air conditioning failure; and when the target fault degree contained in the fault prevention processing information of the air conditioner is relatively large, it is selected to suspend the faulty components of the air conditioner first and then perform fault prevention processing operations on the air conditioner, so as to avoid as much as possible the situation where the air conditioner continues to run when a fault may occur, resulting in an increase in the target fault degree, which is beneficial to better protect the components of the air conditioner.

[0164] In another optional embodiment, the user parameters of the user may include the current user parameters of the user, and the operating parameters of the air conditioner may include the current operating parameters of the air conditioner. Also, judging whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner in step 202 may include:

[0165] Analyze the target probability of air conditioner failure based on the user's user parameters and air conditioner operating parameters;

[0166] Determine whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold;

[0167] If it is determined that the target probability of the air conditioner malfunctioning is greater than or equal to the probability threshold, it is determined that the current operating condition of the air conditioner meets the preset malfunction condition.

[0168] In the embodiment of the present invention, optionally, the target possibility of the air conditioner failure can be the possibility degree of the air conditioner failure. Optionally, the predetermined possibility threshold can be 60%, or 75%, or any other set numerical value, which is not limited in the embodiment of the present invention.

[0169] It can be seen that this optional embodiment can analyze the target possibility of the air conditioner failure based on the user parameters and the operating parameters of the air conditioner, can improve the analysis accuracy of the target possibility of the air conditioner failure, and determine whether the accurately analyzed target possibility is greater than or equal to a predetermined possibility threshold, and when the judgment is yes, determine that the current operating condition of the air conditioner meets the preset fault condition, which can improve the determination accuracy of the current operating condition of the air conditioner that meets the preset fault condition, and can also reduce the occurrence of subsequent preventive treatment of air conditioners that have not failed due to misjudgment.

[0170] In this optional embodiment, the user parameters of the user may further include the user's historical user parameters, and the operating parameters of the air conditioner may further include the historical operating parameters of the air conditioner. And, as an optional implementation, the method may further include:

[0171] If it is determined that the target probability of the air conditioner failure is less than the probability threshold, the historical failure conditions of the air conditioner failure are analyzed based on the historical user parameters of the user and the historical operating parameters of the air conditioner;

[0172] Determining whether the historical fault condition of the air conditioner fault is used to indicate that the number of historical faults of the air conditioner faults in the past preset time period is greater than or equal to a preset number threshold;

[0173] If it is determined that the historical fault conditions of the air conditioner are used to indicate that the number of historical faults of the air conditioner within the past preset time period is greater than or equal to a preset number threshold, it is determined that the current operating conditions of the air conditioner meet the preset fault conditions.

[0174] For example, if the air conditioner is currently operating normally, but it has failed twice in the previous 72 hours, which is more than the specified one time, it can be determined that the air conditioner may still fail.

[0175] It can be seen that this optional implementation method can still determine that the current operating conditions of the air conditioner meet the preset fault conditions when it is judged that the air conditioner has failed a large number of times within the past preset time period, which can reduce the occurrence of missed judgments of possible air conditioner failures, thereby facilitating the improvement of the accuracy of subsequent predictions of the air conditioner's predicted fault conditions when it is accurately judged that the air conditioner may fail.

[0176] In this optional embodiment, the target probability of the air conditioner failure may include a first probability of the air conditioner failure obtained by analyzing the user parameters of the user and a second probability of the air conditioner failure obtained by analyzing the operating parameters of the air conditioner. And, as another optional implementation, determining whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold may include:

[0177] respectively determining whether the first possibility is greater than or equal to a first preset possibility threshold and whether the second possibility is greater than or equal to a second preset possibility threshold;

[0178] If it is determined that the first probability is less than the first preset probability threshold, and the second probability is less than the second preset probability threshold, then it is determined that the target probability of the air conditioner failure is less than the predetermined probability threshold;

[0179] If it is determined that the first possibility is greater than or equal to the first preset possibility threshold, and / or the second possibility is greater than or equal to the second preset possibility threshold, then the target possibility of determining that the air conditioner fails is greater than or equal to the possibility threshold.

[0180] In the embodiment of the present invention, optionally, the first preset possibility threshold may be smaller than the second preset possibility threshold, may be larger than the second preset possibility threshold, or may be equal to the second preset possibility threshold, which is not limited in the embodiment of the present invention.

[0181] For example, the user's expected perceived temperature is 28°C, but the user's actual perceived temperature is 23°C. At this time, the temperature controlled by the air conditioner differs by 5°C, which is greater than the specified 3°C. It can be determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold, and thus it can be determined that the current operating conditions of the air conditioner meet the preset failure conditions.

[0182] It can be seen that this optional implementation can respectively determine whether the first possibility is greater than or equal to the first preset possibility threshold and whether the second possibility is greater than or equal to the second preset possibility threshold, and when it is determined that at least one of the first possibility and the second possibility is greater than or equal to the corresponding possibility threshold, it is determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold, which can occasionally improve the accuracy of determining that the air conditioner may fail, which is beneficial to improving the accuracy of subsequent predictions of the predicted failure conditions of the air conditioner when it is determined that the air conditioner may fail.

[0183] Embodiment 3

[0184] See also Figure 4 , Figure 4 : is a schematic diagram of a structure of an air conditioning operation fault prediction device based on user parameters and air conditioning parameters disclosed in an embodiment of the present invention. Figure 4 The air conditioning operation fault prediction device based on user parameters and air conditioning parameters described may include a fault prediction device or a fault prediction server, wherein the fault prediction server may include a cloud server or a local server, which is not limited in the embodiment of the present invention. Figure 4 As shown, the air conditioning operation fault prediction device based on user parameters and air conditioning parameters may include:

[0185] The acquisition module 301 is used to acquire the user parameters of the user facing the air conditioner when the air conditioner is running and the operating parameters of the air conditioner.

[0186] The judgment module 302 is used to judge whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner.

[0187] The prediction module 303 is used to predict the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner when the judgment module 302 judges that the current operating condition of the air conditioner meets the preset fault condition.

[0188] It can be seen that implementation Figure 4 The air-conditioning operation fault prediction device based on user parameters and air-conditioning parameters described above can judge whether the air-conditioning has an operation fault according to the user parameters of the user facing the air-conditioning and the operation parameters of the air-conditioning obtained when the air-conditioning is running, and can improve the accuracy of judging whether the air-conditioning has an operation fault. When it is accurately judged that the air-conditioning has an operation fault, the predicted fault condition of the air-conditioning is predicted according to the user parameters and the operation parameters, and can improve the prediction accuracy of the fault condition when the air-conditioning is running, which is beneficial to subsequently improve the accuracy and timeliness of air-conditioning fault prevention through accurately predicted fault conditions during air-conditioning operation, and is beneficial to reduce the occurrence of situations where users are unable to start the air-conditioning for operation due to air-conditioning faults, and thus is beneficial to improving the intelligence of the air-conditioning.

[0189] In an optional embodiment, the predicted fault condition of the air conditioner can be used to represent the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner. The operating parameters of the air conditioner may include the actual operating parameters of the air conditioner and the theoretical operating parameters of the air conditioner, and the user parameters of the user may include the actual user parameters of the user obtained by operating the air conditioner according to the actual operating parameters of the air conditioner and the theoretical user parameters of the user obtained by operating the air conditioner according to the theoretical operating parameters of the air conditioner. And, the prediction module 303 predicts the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner, which may specifically include:

[0190] Performing difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result, wherein the difference analysis result includes a difference corresponding to each of the multiple information types;

[0191] Select the one with the largest difference value from all information types as the target information type;

[0192] According to the target information type, the predicted fault type of the air conditioner is determined, and according to the target difference corresponding to the target information type, the target fault degree corresponding to the predicted fault type of the air conditioner is determined.

[0193] It can be seen that this optional embodiment can perform a difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user and the theoretical user parameters of the user to obtain a difference analysis result, and filter out one of the information types with the largest corresponding difference value from all the information types contained in the difference analysis result as the target information type, which can improve the screening accuracy of the target information type and reduce the occurrence of subsequent processing of information types that do not need to be screened. The predicted fault type of the air conditioner is determined according to the target information type, which can improve the accuracy of determining the predicted fault type of the air conditioner, and the target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type, which can improve the accuracy of determining the target fault degree corresponding to the predicted fault type, thereby helping to improve the prediction accuracy and reliability of fault conditions during air conditioning operation (the fault conditions include predicted fault types and target fault degrees corresponding to the predicted fault types).

[0194] In this optional embodiment, as an optional implementation, the prediction module 303 determines the predicted fault type of the air conditioner according to the target information type, which may specifically include:

[0195] According to the target information type, one of the preset fault type sets corresponding to the target information type is searched as the predicted fault type of the air conditioner.

[0196] It can be seen that this optional implementation method can search for the predicted fault type of the air conditioner corresponding to the target information type from the preset fault type set according to the target information type, which can improve the search accuracy and reliability of the predicted fault type of the air conditioner and reduce the occurrence of subsequent processing of fault types that do not need to be found.

[0197] In this optional embodiment, as another optional implementation, the prediction module 303 determines the target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type, and the method may specifically include:

[0198] The target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type and the fault degree corresponding to each difference value interval in the preset plurality of difference value intervals.

[0199] It can be seen that this optional implementation method can determine the target fault degree corresponding to the predicted fault type of the air conditioner based on the target difference corresponding to the target information type and the fault degree corresponding to the preset multiple difference value intervals, and can improve the accuracy and reliability of determining the target fault degree corresponding to the predicted fault type, thereby facilitating the subsequent improvement of the accuracy and timeliness of prevention of the air conditioner through accurately determined target fault degrees.

[0200] In this optional embodiment, as another optional embodiment, as Figure 5 As shown, the device may also include:

[0201] A generating module 304, configured to generate fault prevention processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner;

[0202] The execution module 305 is used to execute a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner.

[0203] It can be seen that this optional implementation method can generate fault prevention and processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner, thereby improving the accuracy and timeliness of the generation of the fault prevention and processing information, and performing fault prevention and processing operations on the air conditioner according to the accurately generated fault prevention and processing information, thereby improving the accuracy and timeliness of the fault prevention and processing operations performed on the air conditioner, and through timely preventive processing operations, it can reduce the occurrence of situations where users are unable to start the air conditioner to work due to air conditioner failure, thereby helping to improve the intelligence of the air conditioner and enhance the user experience.

[0204] In this optional implementation, optionally, the execution module 305 may perform the fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner, and the method may specifically include:

[0205] When the target fault degree contained in the fault prevention processing information of the air conditioner is less than or equal to the preset fault degree threshold, directly performing the fault prevention processing operation on the air conditioner;

[0206] When the target fault degree contained in the fault prevention processing information of the air conditioner is greater than the preset fault degree threshold, the target operating components matching the predicted fault type among all operating components of the air conditioner are suspended, and the fault prevention processing operation is performed on the air conditioner after the target operating components are suspended.

[0207] It can be seen that this optional implementation method can also choose to directly perform fault prevention processing operations on the air conditioner when the target fault degree contained in the fault prevention processing information of the air conditioner is relatively small, which can improve the accuracy and processing efficiency of performing fault prevention processing operations on the air conditioner, and there is no need to suspend the operating state of the air conditioner, which is beneficial to ensure that the air conditioner is in an operating state while reducing the possibility of air conditioning failure; and when the target fault degree contained in the fault prevention processing information of the air conditioner is relatively large, it is selected to suspend the faulty components of the air conditioner first and then perform fault prevention processing operations on the air conditioner, so as to avoid as much as possible the situation where the air conditioner continues to run when a fault may occur, resulting in an increase in the target fault degree, which is beneficial to better protect the components of the air conditioner.

[0208] In another optional embodiment, the user parameters of the user may include the current user parameters of the user, and the operating parameters of the air conditioner may include the current operating parameters of the air conditioner. And the method in which the judgment module 302 judges whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner may specifically include:

[0209] Analyze the target probability of air conditioner failure based on the user's user parameters and air conditioner operating parameters;

[0210] Determine whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold;

[0211] If it is determined that the target probability of the air conditioner malfunctioning is greater than or equal to the probability threshold, it is determined that the current operating condition of the air conditioner meets the preset malfunction condition.

[0212] It can be seen that this optional embodiment can analyze the target possibility of the air conditioner failure based on the user parameters and the operating parameters of the air conditioner, can improve the analysis accuracy of the target possibility of the air conditioner failure, and determine whether the accurately analyzed target possibility is greater than or equal to a predetermined possibility threshold, and when the judgment is yes, determine that the current operating condition of the air conditioner meets the preset fault condition, which can improve the determination accuracy of the current operating condition of the air conditioner that meets the preset fault condition, and can also reduce the occurrence of subsequent preventive treatment of air conditioners that have not failed due to misjudgment.

[0213] In this optional embodiment, the user parameters of the user may further include the user's historical user parameters, and the operating parameters of the air conditioner may further include the historical operating parameters of the air conditioner. And, as an optional implementation, if Figure 5 As shown, the device may also include:

[0214] An analysis module 306 is used to analyze historical fault conditions of the air conditioner according to historical user parameters of the user and historical operating parameters of the air conditioner if the determination module 302 determines that the target probability of the air conditioner failure is less than the probability threshold;

[0215] The judgment module 302 is further used to judge whether the historical fault situation of the air conditioner fault is used to indicate that the number of historical faults of the air conditioner faults in the past preset time period is greater than or equal to a preset number threshold;

[0216] The determination module 307 is used to determine whether the current operating condition of the air conditioner meets the preset fault condition if the judgment module 302 determines that the historical fault condition of the air conditioner is used to indicate that the number of historical faults of the air conditioner within the past preset time period is greater than or equal to the preset number threshold.

[0217] It can be seen that this optional implementation method can still determine that the current operating conditions of the air conditioner meet the preset fault conditions when it is judged that the air conditioner has failed a large number of times within the past preset time period, which can reduce the occurrence of missed judgments of possible air conditioner failures, thereby facilitating the improvement of the accuracy of subsequent predictions of the air conditioner's predicted fault conditions when it is accurately judged that the air conditioner may fail.

[0218] In this optional embodiment, the target probability of the air conditioner failure may include a first probability of the air conditioner failure obtained by analyzing the user parameters of the user and a second probability of the air conditioner failure obtained by analyzing the operating parameters of the air conditioner. And, as another optional implementation, the method in which the judgment module 302 judges whether the target probability of the air conditioner failure is greater than or equal to the predetermined probability threshold may specifically include:

[0219] respectively determining whether the first possibility is greater than or equal to a first preset possibility threshold and whether the second possibility is greater than or equal to a second preset possibility threshold;

[0220] If it is determined that the first probability is less than the first preset probability threshold, and the second probability is less than the second preset probability threshold, then it is determined that the target probability of the air conditioner failure is less than the predetermined probability threshold;

[0221] If it is determined that the first possibility is greater than or equal to the first preset possibility threshold, and / or the second possibility is greater than or equal to the second preset possibility threshold, then the target possibility of determining that the air conditioner fails is greater than or equal to the possibility threshold.

[0222] It can be seen that this optional implementation can respectively determine whether the first possibility is greater than or equal to the first preset possibility threshold and whether the second possibility is greater than or equal to the second preset possibility threshold, and when it is determined that at least one of the first possibility and the second possibility is greater than or equal to the corresponding possibility threshold, it is determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold, which can occasionally improve the accuracy of determining that the air conditioner may fail, which is beneficial to improving the accuracy of subsequent predictions of the predicted failure conditions of the air conditioner when it is determined that the air conditioner may fail.

[0223] Embodiment 4

[0224] See also Figure 6 , Figure 6 FIG. 1 is a schematic diagram of the structure of another air conditioning operation fault prediction device based on user parameters and air conditioning parameters disclosed in an embodiment of the present invention. Figure 6 As shown, the air conditioning operation fault prediction device based on user parameters and air conditioning parameters may include:

[0225] A memory 401 storing executable program codes;

[0226] a processor 402 coupled to the memory 401;

[0227] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the air-conditioning operation fault prediction method based on user parameters and air-conditioning parameters described in the first embodiment of the present invention or the second embodiment of the present invention.

[0228] Embodiment 5

[0229] 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 of the air conditioning operation fault prediction method based on user parameters and air conditioning parameters described in Embodiment 1 or Embodiment 2 of the present invention.

[0230] Embodiment 6

[0231] 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 of the air conditioning operation fault prediction method based on user parameters and air conditioning parameters described in Example 1 or Example 2.

[0232] 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, that is, 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.

[0233] 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.

[0234] Finally, it should be noted that the method and device for predicting air-conditioning operation faults based on user parameters and air-conditioning parameters disclosed in the embodiment of the present invention disclose 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, those skilled in the art should understand that the technical schemes described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced 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 embodiments of the present invention.

Claims

1. A method for predicting air-conditioning operation failure based on user parameters and air-conditioning parameters, characterized in that: The method comprises: Acquire user parameters of the user facing the air conditioner during operation and operating parameters of the air conditioner; Determining whether a current operating condition of the air conditioner meets a preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner; When it is determined that the current operating condition of the air conditioner meets the preset fault condition, a predicted fault condition of the air conditioner is predicted according to the user parameters of the user and the operating parameters of the air conditioner.

2. The air conditioning operation fault prediction method based on user parameters and air conditioning parameters according to claim 1, characterized in that: The predicted fault condition of the air conditioner is used to indicate the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner; The operating parameters of the air conditioner include actual operating parameters of the air conditioner and theoretical operating parameters of the air conditioner, and the user parameters of the user include actual user parameters of the user obtained by operating the air conditioner according to the actual operating parameters of the air conditioner and theoretical user parameters of the user obtained by operating the air conditioner according to the theoretical operating parameters of the air conditioner; And, predicting the predicted fault condition of the air conditioner according to the user parameter of the user and the operating parameter of the air conditioner includes: Performing difference analysis on the actual operating parameters of the air conditioner, the theoretical operating parameters of the air conditioner, the actual user parameters of the user, and the theoretical user parameters of the user to obtain a difference analysis result, wherein the difference analysis result includes a difference corresponding to each of the multiple information types; Filter out one of the information types with the largest corresponding difference value from all the information types as the target information type; The predicted fault type of the air conditioner is determined according to the target information type, and the target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type.

3. The air conditioning operation fault prediction method based on user parameters and air conditioning parameters according to claim 2, characterized in that: The step of determining the predicted fault type of the air conditioner according to the target information type includes: According to the target information type, searching for one of the preset fault types corresponding to the target information type from the set of fault types as the predicted fault type of the air conditioner; And, determining the target fault degree corresponding to the predicted fault type of the air conditioner according to the target difference corresponding to the target information type includes: The target fault degree corresponding to the predicted fault type of the air conditioner is determined according to the target difference corresponding to the target information type and the fault degree corresponding to each of the plurality of preset difference value intervals.

4. The air conditioning operation fault prediction method based on user parameters and air conditioning parameters according to claim 2 or 3, characterized in that: The method further comprises: generating fault prevention processing information of the air conditioner according to the predicted fault type of the air conditioner and the target fault degree corresponding to the predicted fault type of the air conditioner; performing a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner; The performing of a fault prevention processing operation on the air conditioner according to the fault prevention processing information of the air conditioner includes: When the target fault degree contained in the fault prevention processing information of the air conditioner is less than or equal to a preset fault degree threshold, directly performing a fault prevention processing operation on the air conditioner; When the target fault degree contained in the fault prevention processing information of the air conditioner is greater than the preset fault degree threshold, the target operating components matching the predicted fault type among all operating components of the air conditioner are suspended, and the fault prevention processing operation is performed on the air conditioner after suspending the target operating components.

5. The air conditioning operation fault prediction method based on user parameters and air conditioning parameters according to any one of claims 1 to 3, characterized in that: The user parameters of the user include the current user parameters of the user, and the operating parameters of the air conditioner include the current operating parameters of the air conditioner; And, judging whether the current operating condition of the air conditioner meets the preset fault condition according to the user parameter of the user and the operating parameter of the air conditioner includes: Analyzing the target probability of failure of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner; Determining whether a target probability of failure of the air conditioner is greater than or equal to a predetermined probability threshold; If it is determined that the target probability of the air conditioner failing is greater than or equal to the probability threshold, it is determined that the current operating condition of the air conditioner meets a preset failure condition.

6. The method for predicting air-conditioning operation failure based on user parameters and air-conditioning parameters according to claim 5, characterized in that: The user parameters of the user also include the historical user parameters of the user, and the operating parameters of the air conditioner also include the historical operating parameters of the air conditioner; And, the method further comprises: If it is determined that the target probability of the air conditioner malfunctioning is less than the probability threshold, analyzing historical malfunction situations of the air conditioner malfunctioning according to historical user parameters of the user and historical operating parameters of the air conditioner; Determining whether the historical fault condition of the air conditioner fault is used to indicate that the number of historical faults of the air conditioner faults within a preset time period in the past is greater than or equal to a preset number threshold; If it is determined that the historical fault conditions of the air conditioner are used to indicate that the number of historical faults of the air conditioner within the past preset time period is greater than or equal to the preset number threshold, it is determined that the current operating condition of the air conditioner meets the preset fault condition.

7. The method for predicting air-conditioning operation failure based on user parameters and air-conditioning parameters according to claim 5, characterized in that: The target probability of the air conditioner malfunctioning includes a first probability of the air conditioner malfunctioning obtained by analyzing the user parameters of the user and a second probability of the air conditioner malfunctioning obtained by analyzing the operating parameters of the air conditioner; And, the step of determining whether the target probability of the air conditioner failure is greater than or equal to a predetermined probability threshold comprises: respectively determining whether the first possibility is greater than or equal to a first preset possibility threshold and whether the second possibility is greater than or equal to a second preset possibility threshold; If it is determined that the first probability is less than the first preset probability threshold, and the second probability is less than the second preset probability threshold, then it is determined that the target probability of the air conditioner failure is less than the predetermined probability threshold; If it is determined that the first possibility is greater than or equal to the first preset possibility threshold, and / or the second possibility is greater than or equal to the second preset possibility threshold, then it is determined that the target possibility of the air conditioner failure is greater than or equal to the possibility threshold.

8. An air conditioning operation fault prediction device based on user parameters and air conditioning parameters, characterized in that: The device comprises: An acquisition module, used to acquire user parameters of the user facing the air conditioner during operation and operating parameters of the air conditioner; A judgment module, used for judging whether the current operating condition of the air conditioner meets a preset fault condition according to the user parameters of the user and the operating parameters of the air conditioner; A prediction module is used to predict the predicted fault condition of the air conditioner according to the user parameters of the user and the operating parameters of the air conditioner when the judgment module determines that the current operating condition of the air conditioner meets the preset fault condition.

9. An air conditioning operation fault prediction device based on user parameters and air conditioning parameters, 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 air conditioning operation fault prediction method based on user parameters and air conditioning parameters as described in any one of claims 1 to 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 air conditioning operation fault prediction method based on user parameters and air conditioning parameters as described in any one of claims 1-7.

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