A power failure detection method and system for an air conditioning device

Abstract

The present application relates to a power failure detection method and system for an air conditioning device. The method includes respectively obtaining the main board voltage detection value, transformer voltage detection value, and plug voltage detection value when the air conditioning device is powered on, and performing data cleaning processing to obtain the preprocessed air conditioning operation data. Furthermore, a power phase waveform among the main board, transformer, and power plug of the air conditioning device is drawn, and the power phase sequence balance relationship of the air conditioning device is analyzed. The abnormal power phase sequence is analyzed in combination with the historical fault data of the air conditioning device and the power phase sequence balance relationship. According to the analysis results, a power failure analysis model for analyzing the power failure of the air conditioning device is constructed. The power failure analysis model performs power failure analysis on the power phase data in the power failure state of the air conditioning device to obtain the power failure detection data corresponding to the current power failure phase. The present application has the effect of improving the intelligent degree of power failure detection of the air conditioning device.

Description

Technical Field

[0001] This application relates to the technical field of fault detection, and particularly to a power failure detection method and system for air conditioning equipment. Background Art

[0002] At present, as an indispensable part of modern home and office environments, the normal operation of air conditioning equipment is crucial for the comfort of the indoor environment. Whether the power supply of the air conditioning equipment can operate normally determines the stability of the use of the air conditioning equipment. When a power failure occurs in the air conditioning equipment, it cannot be powered on for temperature adjustment work. Therefore, it is necessary to further improve the power failure detection of air conditioning equipment.

[0003] The existing power failure detection methods for air conditioning equipment usually involve maintenance personnel using instruments such as electric pens or voltmeters to check the power supply components and sockets of the air conditioning equipment one by one. Based on the inspection results and combined with the maintenance experience of the maintenance personnel, the power failure is judged and repaired manually. The traditional power failure detection method relies on the manual experience of the maintenance personnel, is prone to human judgment errors, wastes human resources, and there is room for further optimization of the air conditioning fault detection method. Summary of the Invention

[0004] In order to improve the intelligent level of power failure detection for air conditioning equipment and establish a unified standard for power failure detection of air conditioning power supplies, this application provides a power failure detection method and system for air conditioning equipment.

[0005] In a first aspect, the above-mentioned invention object of this application is achieved through the following technical solutions:

[0006] A power failure detection method for air conditioning equipment, comprising:

[0007] Respectively obtain the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioning equipment when it is powered on, and perform data cleaning processing to obtain the preprocessed air conditioning operation data;

[0008] Obtain the power phase waveforms among the main board, transformer, and power plug of the air conditioning equipment according to the air conditioning operation data, and analyze the power phase sequence balance relationship of the air conditioning equipment based on the power phase waveforms;

[0009] Obtain the historical fault data of the air conditioning equipment, analyze the abnormal power phase sequence in combination with the power phase sequence balance relationship, and construct a power failure analysis model for analyzing the power failure of the air conditioning equipment according to the analysis results;

[0010] Obtain the power phase data in the power failure state of the air conditioning equipment power supply, input the power phase data into the power failure analysis model for power failure analysis, and obtain the power failure detection data corresponding to the current power failure phase.

[0011] By adopting the above technical solution, the power operation parameters of the air-conditioning equipment are comprehensively collected through the detected values of the main board voltage, transformer voltage, and plug voltage of the air-conditioning equipment in the powered-on state. The invalid interference data is screened out through data cleaning. The power phase balance relationship is analyzed through the power phase waveforms among the main board, transformer, and power plug, which helps to conduct a detailed comparison and analysis of the key device parameters related to the power phase sequence, improve the analysis accuracy of the power phase balance relationship, and take the historical fault data as a reference to conduct abnormal power phase sequence analysis in combination with the power phase balance relationship, thereby constructing a power fault analysis model to facilitate more convenient analysis of the power fault of the air-conditioning equipment, improve the fault analysis efficiency, conduct fault analysis on the power phase data in the fault state through the model uniformly, and form a standardized air-conditioning power fault detection standard, which helps to improve the intelligent level of the power fault detection of the air-conditioning equipment.

[0012] In a preferred example of the present application, it can be further configured as follows: obtaining the power phase waveforms among the main board, transformer, and power plug of the air-conditioning equipment according to the air-conditioning operation data, and analyzing the power phase balance relationship of the air-conditioning equipment according to the power phase waveforms, specifically including:

[0013] Respectively draw the operation phase waveforms of the main board, transformer, and power plug of the air-conditioning equipment according to the air-conditioning operation data, and perform phase association in the order of operation time to obtain the power phase waveform of the air-conditioning equipment;

[0014] Calculate the waveform deviation between adjacent phase waveforms according to the power phase waveform, and analyze the power phase deviation trend of the air-conditioning equipment according to the waveform deviation to obtain phase deviation analysis data;

[0015] According to the power phase waveform and the phase deviation analysis data, split the power phase waveform into a power phase stable group and a power phase unstable group with the initial position of the phase deviation as the boundary;

[0016] Conduct power phase sequence comparison and analysis on the power phase stable group and the power phase unstable group respectively, extract the unbalanced phase sequence characteristics according to the comparison results, and construct the power phase balance relationship of the air-conditioning equipment according to the common characteristics among the unbalanced phase sequence characteristics.

[0017] By adopting the above technical solution, the operation data of the air conditioner is plotted into the operation phase waveforms of the main board, transformer, and power plug of the air conditioner equipment, which helps to more intuitively observe the differences in the power operation phases. The power phase waveforms are plotted in sequence according to the operation time, and the power phase deviation trend analysis is carried out through the waveform deviation calculation of adjacent phase waveforms, which helps to improve the analysis accuracy of the power phase deviation. Taking the initial position where the phase deviation occurs as the boundary, the power phase waveform is split, and the unbalanced phase sequence characteristics are extracted through the combined comparison of the phase stable group and the phase unstable group. Furthermore, based on the common characteristics among the unbalanced phase sequence characteristics, the power phase sequence balance relationship is constructed, which helps to improve the analysis accuracy of the power phase sequence balance relationship.

[0018] In a preferred example of the present application, it can be further configured as follows: obtaining the historical fault data of the air conditioner equipment, analyzing the abnormal power phase sequence in combination with the power phase sequence balance relationship, and constructing a power fault analysis model for analyzing the power fault of the air conditioner equipment according to the analysis result, specifically including:

[0019] Obtaining the historical fault data of the air conditioner equipment, using the historical fault data as training samples to perform data training on the power phase sequence balance relationship, and obtaining the historical unbalanced phase sequence characteristics related to historical faults according to the training result;

[0020] According to the historical unbalanced phase sequence characteristics and the corresponding abnormal phase sequence sites, performing a feature commonality analysis of the abnormal power phase sequence characteristics on the power phase sequence balance relationship to obtain the feature commonality association relationship of the abnormal power phase sequence characteristics;

[0021] Constructing a power fault analysis model for analyzing the power fault of the air conditioner equipment according to the feature commonality association relationship.

[0022] By adopting the above technical solution, using the historical fault data of the air conditioner equipment as training samples and substituting them into the power phase sequence balance relationship for data training, so as to obtain the historical unbalanced phase sequence characteristics related to historical faults according to the training result, which helps to enrich the training samples of the power phase sequence balance relationship. Through the historical unbalanced phase sequence and the corresponding abnormal phase sequence sites, taking the phase sequence site as the association point, a combined analysis of the feature commonality of the abnormal power phase sequence characteristics is carried out on the power phase sequence balance relationship, which helps to improve the analysis accuracy of the feature commonality association relationship of the abnormal power phase sequence characteristics, and thus construct a power fault analysis model that more conforms to the actual situation of power faults, which helps to improve the analysis accuracy of the power fault of the air conditioner equipment.

[0023] In a preferred example, the present application can be further configured as follows: acquiring power phase data in the power failure state of the air conditioning equipment, inputting the power phase data into the power failure analysis model for power failure analysis, and obtaining power failure detection data corresponding to the current power failure phase, specifically including:

[0024] Performing phase fitting analysis on the power phase data in the failure state and the power phase sequence balance relationship in the power failure analysis model to obtain abnormal phase sequence characteristics corresponding to the power failure state;

[0025] Through a preset fault code generation mechanism, performing fault code conversion processing on the abnormal phase sequence characteristics to obtain fault code parameters corresponding to the current power failure;

[0026] Performing fault code matching processing on the fault code parameters with a preset power failure database, and selecting the power failure type with the highest matching degree for power failure location to obtain power failure detection data corresponding to the current fault power phase.

[0027] By adopting the above technical solution, performing phase fitting processing on the power phase data in the failure state and the power phase sequence balance relationship in the power failure analysis model, and obtaining abnormal phase sequence characteristics corresponding to the power failure state through the parameter fitting difference of the corresponding phases, which helps to improve the analysis accuracy of the abnormal phase sequence characteristics, and performing fault code conversion processing on the abnormal phase sequence characteristics through a preset fault code generation mechanism, which helps to find the corresponding fault data in the database by comparing the fault code parameters, so as to select the power failure type with the highest fault code matching degree for fault location, obtain power failure detection data corresponding to the current fault power phase, which helps to improve the accuracy of fault type judgment and provides an effective reference for power failure maintenance.

[0028] In a preferred example, the present application can be further configured as follows: respectively acquiring the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioning equipment in the powered-on state and performing data cleaning processing to obtain preprocessed air conditioning operation data, specifically including:

[0029] Acquiring the main board voltage detection value of the air conditioning equipment in the powered-on state, comparing the main board voltage detection value with the preset main board operating voltage to obtain main board operation data;

[0030] Respectively acquiring the primary voltage of the transformer winding and the secondary voltage of the transformer winding, and analyzing whether the power transformer of the air conditioning equipment is in a stable voltage transformation state to obtain transformer operation data;

[0031] Acquiring the plug voltage detection value corresponding to the power supply of the air conditioning equipment, and analyzing whether the plug voltage detection value is adapted to the preset rated voltage of the air conditioning equipment to obtain plug operation data corresponding to the power supply of the air conditioning equipment;

[0032] Data cleaning processing is respectively performed on the main board operation data, transformer operation data, and plug operation data to obtain preprocessed air conditioner operation data.

[0033] By adopting the above technical solution, independent data collection and comparative analysis are respectively performed on the main board operation data, transformer operation data, and plug operation data of the air conditioner device, so as to carefully check the operation conditions of the key components related to the power supply failure of the air conditioner device, which helps to improve the accuracy of troubleshooting the fault source, and invalid interference data is screened out through data cleaning, reducing the data processing workload for power supply failure detection and analysis and improving the effectiveness of the data.

[0034] In a second aspect, the above object of the present application is achieved by the following technical solution:

[0035] A power supply failure detection system for an air conditioner device, comprising:

[0036] A data collection module, configured to respectively obtain the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioner device under the powered-on state and perform data cleaning processing to obtain preprocessed air conditioner operation data;

[0037] A data analysis module, configured to obtain the power phase waveforms among the main board, transformer, and power plug of the air conditioner device according to the air conditioner operation data, and analyze the power phase sequence balance relationship of the air conditioner device according to the power phase waveforms;

[0038] A model construction module, configured to obtain the historical fault data of the air conditioner device, analyze the abnormal power phase sequence in combination with the power phase sequence balance relationship, and construct a power supply failure analysis model for analyzing the power supply failure of the air conditioner device according to the analysis results;

[0039] A fault detection module, configured to obtain the power phase data in the power supply failure state of the air conditioner device, input the power phase data into the power supply failure analysis model for power supply failure analysis, and obtain the power supply failure detection data corresponding to the current power supply failure phase.

[0040] By adopting the above technical solution, the power operation parameters of the air conditioner equipment are comprehensively collected through the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioner equipment in the powered-on state. The invalid interference data is screened out through data cleaning. The power phase waveform among the main board, transformer, and power plug is used to analyze the power phase sequence balance relationship, which helps to conduct a detailed comparison and analysis of the key device parameters related to the power phase sequence, improve the analysis accuracy of the power phase sequence balance relationship, and take the historical fault data as a reference to conduct abnormal power phase sequence analysis in combination with the power phase sequence balance relationship, thereby constructing a power fault analysis model to facilitate more convenient analysis of the power fault of the air conditioner equipment, improve the fault analysis efficiency, and uniformly conduct fault analysis on the power phase data in the fault state through the model to form a standardized air conditioner power fault detection standard, which helps to improve the intelligent level of the power fault detection of the air conditioner equipment.

[0041] In a third aspect, the above object of the present application is achieved through the following technical solutions:

[0042] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above power fault detection method for the air conditioner equipment are implemented.

[0043] In a fourth aspect, the above object of the present application is achieved through the following technical solutions:

[0044] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the above power fault detection method for the air conditioner equipment are implemented.

[0045] In summary, the present application includes at least one of the following beneficial technical effects:

[0046] 1. By the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioner equipment in the powered-on state, the power operation parameters of the air conditioner equipment are comprehensively collected, the invalid interference data is screened out through data cleaning, the power phase waveform among the main board, transformer, and power plug is used to analyze the power phase sequence balance relationship, which helps to conduct a detailed comparison and analysis of the key device parameters related to the power phase sequence, improve the analysis accuracy of the power phase sequence balance relationship, and take the historical fault data as a reference to conduct abnormal power phase sequence analysis in combination with the power phase sequence balance relationship, thereby constructing a power fault analysis model to facilitate more convenient analysis of the power fault of the air conditioner equipment, improve the fault analysis efficiency, and uniformly conduct fault analysis on the power phase data in the fault state through the model to form a standardized air conditioner power fault detection standard, which helps to improve the intelligent level of the power fault detection of the air conditioner equipment;

[0047] 2. Plotting the air conditioner operation data into the operation phase waveforms of the main board, transformer, and power plug of the air conditioner equipment helps to more intuitively observe the differences in the power operation phases, and correlating and plotting them in the order of operation time to form the power phase waveforms. Analyzing the trend of power phase deviation through calculating the waveform deviation between adjacent phase waveforms helps to improve the accuracy of power phase deviation analysis. Taking the initial position where the phase deviation occurs as the boundary, splitting the power phase waveforms, and extracting the unbalanced phase sequence characteristics through the combined comparison of the phase stable group and the phase unstable group. Furthermore, constructing the power phase sequence balance relationship based on the common characteristics among the unbalanced phase sequence characteristics helps to improve the accuracy of the analysis of the power phase sequence balance relationship.

[0048] 3. Using the historical fault data of the air conditioner equipment as training samples and substituting them into the power phase sequence balance relationship for data training, so as to obtain the historical unbalanced phase sequence characteristics related to historical faults according to the training results. This helps to enrich the training samples of the power phase sequence balance relationship, and through the historical unbalanced phase sequence and the abnormal phase sequence sites, taking the phase sequence sites as the correlation points, jointly analyzing the common characteristics of the abnormal power phase sequence characteristics in the power phase sequence balance relationship helps to improve the accuracy of the analysis of the correlation relationship of the common characteristics of the abnormal power phase sequence characteristics, and thus constructing a power fault analysis model that more conforms to the actual situation of power faults helps to improve the accuracy of power fault analysis of the air conditioner equipment. Description of the Drawings

[0049] Figure 1 is the implementation flowchart of a power fault detection method for an air conditioner equipment in this embodiment.

[0050] Figure 2 is the implementation flowchart of step S10 of a power fault detection method for an air conditioner equipment in this embodiment.

[0051] Figure 3 is the implementation flowchart of step S20 of a power fault detection method for an air conditioner equipment in this embodiment.

[0052] Figure 4 is the implementation flowchart of step S30 of a power fault detection method for an air conditioner equipment in this embodiment.

[0053] Figure 5 is the implementation flowchart of step S40 of a power fault detection method for an air conditioner equipment in this embodiment.

[0054] Figure 6 is the structural block diagram of a power fault detection system for an air conditioner equipment in this embodiment.

[0055] Figure 7 is the internal structural schematic diagram of a computer device for implementing a power fault detection method for an air conditioner equipment. Specific Embodiment

[0056] The present application will be further described in detail below with reference to the accompanying drawings.

[0057] In one embodiment, as Figure 1 shown, the present application discloses a method for detecting a power failure of an air conditioning device, specifically including the following steps:

[0058] S10: Respectively obtain the main board voltage detection value, the transformer voltage detection value, and the plug voltage detection value of the air conditioning device under the powered-on state, and perform data cleaning processing to obtain the preprocessed air conditioning operation data.

[0059] Specifically, as Figure 2 shown, step S10 includes:

[0060] S101: Obtain the main board voltage detection value of the air conditioning device under the powered-on state, compare the main board voltage detection value with the preset main board operating voltage, and obtain the main board operation data.

[0061] Specifically, under the powered-on state of the air conditioning device, collect the main board voltage detection value through a multimeter, compare it with the preset main board operating voltage, and judge whether the main board voltage meets the preset operating voltage according to the comparison result. If it meets, it means that the main board voltage operates normally, and use the main board voltage detection value under the normal operating state as the main board operation data.

[0062] S102: Respectively obtain the primary voltage of the transformer winding and the secondary voltage of the transformer winding, and analyze whether the power transformer of the air conditioning device is in a stable voltage transformation state to obtain the transformer operation data.

[0063] Specifically, collect the primary voltage of the transformer winding and the secondary voltage of the transformer winding through a multimeter, analyze whether the voltage change of the power transformer is in a stable voltage transformation state according to the primary voltage of the winding and the secondary voltage of the winding, and collect the stable voltage transformation transformer operation data to obtain the transformer operation data.

[0064] S103: Obtain the plug voltage detection value corresponding to the power supply of the air conditioning device, and analyze whether the plug voltage detection value is adapted to the preset rated voltage of the air conditioning device to obtain the plug operation data corresponding to the power supply of the air conditioning device.

[0065] Specifically, obtain the plug voltage detection value corresponding to the power supply of the air conditioning device through a multimeter, compare and analyze the collected plug voltage detection value with the preset rated voltage of the air conditioning device, and use the plug voltage detection value adapted to the preset rated voltage as the plug operation data of the power supply operation.

[0066] S104: Perform data cleaning on the main board operation data, transformer operation data, and plug operation data respectively to obtain the preprocessed air conditioner operation data.

[0067] Specifically, screen out the data in the main board operation data, transformer operation data, and plug operation data that does not match the corresponding rated voltage value, so as to obtain the preprocessed air conditioner operation data.

[0068] S20: Obtain the power phase waveforms among the main board, transformer, and power plug of the air conditioner device according to the air conditioner operation data, and analyze the power phase sequence balance relationship of the air conditioner device based on the power phase waveforms.

[0069] Specifically, as Figure 3 shown, step S20 includes:

[0070] S201: Draw the operation phase waveforms of the main board, transformer, and power plug of the air conditioner device respectively according to the air conditioner operation data, and perform phase correlation in the order of operation time to obtain the power phase waveform of the air conditioner device.

[0071] Specifically, draw the operation phase waveforms of the main board, transformer, and power plug of the air conditioner device respectively according to the air conditioner operation data, and correlate the phases of the main board, transformer, and power plug in the order of operation time to obtain the power phase waveform of the power operation of the air conditioner device.

[0072] S202: Calculate the waveform deviation between adjacent phase waveforms according to the power phase waveform, and analyze the power phase deviation trend of the air conditioner device based on the waveform deviation to obtain the phase deviation analysis data.

[0073] Specifically, calculate the waveform deviation between adjacent phase waveforms according to the power phase waveform, and analyze the change of the power phase deviation of the air conditioner device in the order of operation time, so as to obtain the power phase deviation trend of the air conditioner device, and use the power phase deviation trend as the phase deviation analysis data.

[0074] S203: Split the power phase waveform into a power phase stable group and a power phase unstable group with the initial position of the phase deviation as the boundary according to the power phase waveform and the phase deviation analysis data.

[0075] Specifically, according to the power phase waveform and the phase deviation analysis data, mark the phase point where the phase deviation starts as the initial position of the phase deviation, and split the power phase waveform into a power phase stable group and a power phase unstable group with the initial position of the phase deviation as the boundary. At the same time, group the corresponding phase deviation analysis data of the power phase stable group and the power phase unstable group respectively.

[0076] S204: Perform power phase sequence comparison and analysis for the power supply phase stable group and the power supply phase unstable group respectively. Extract unbalanced phase sequence features according to the comparison results, and construct the power supply phase sequence balance relationship of the air-conditioning equipment based on the common features among the unbalanced phase sequence features.

[0077] Specifically, perform power phase sequence comparison and analysis for the power supply phase unstable group and the power supply phase stable group. Extract the unbalanced phase sequence features in the power supply phase unstable group that are different from those in the power supply phase stable group according to the comparison results, and analyze the common features among the unbalanced phase sequence features to obtain the power supply phase sequence balance relationship of the air-conditioning equipment.

[0078] S30: Obtain the historical fault data of the air-conditioning equipment, analyze the abnormal power supply phase sequence in combination with the power supply phase sequence balance relationship, and construct a power fault analysis model for analyzing the power faults of the air-conditioning equipment according to the analysis results.

[0079] Specifically, as Figure 4 shown, step S30 includes:

[0080] S301: Obtain the historical fault data of the air-conditioning equipment, perform data training on the power supply phase sequence balance relationship with the historical fault data as the training samples, and obtain the historical unbalanced phase sequence features related to the historical faults according to the training results.

[0081] Specifically, extract the historical fault data from the historical maintenance database of the air-conditioning equipment, use the historical fault data as the training samples, substitute them into the power supply phase sequence balance relationship for data training, and screen the unbalanced phase sequence features in the historical fault data according to the training results to obtain the historical unbalanced phase sequence features related to the historical faults.

[0082] S302: Perform feature commonality analysis of the abnormal power supply phase sequence features on the power supply phase sequence balance relationship according to the historical unbalanced phase sequence features and the corresponding abnormal phase sequence sites, and obtain the feature commonality correlation relationship of the abnormal power supply phase sequence features.

[0083] Specifically, according to the historical unbalanced phase sequence features and the corresponding abnormal phase sequence sites, take the phase sequence site as the correlation point, perform abnormal power supply phase sequence feature analysis on the power supply phase sequence balance relationship, and extract the feature commonality parameters of the abnormal power supply phase sequence features for feature commonality correlation relationship analysis to obtain the feature commonality correlation relationship of the abnormal power supply phase sequence features.

[0084] S303: Construct a power fault analysis model for analyzing the power faults of the air-conditioning equipment according to the feature commonality correlation relationship.

[0085] Specifically, construct a power fault analysis model for the data framework according to the feature commonality correlation relationship, and create a unified analysis standard for power fault analysis to analyze the power faults of the air-conditioning equipment.

[0086] S40: Obtain the power phase data under the power failure state of the air conditioning equipment, input the power phase data into the power failure analysis model for power failure analysis, and obtain the power failure detection data corresponding to the current power failure phase.

[0087] Specifically, as Figure 5 shown, step S40 includes:

[0088] S401: Perform phase fitting analysis on the power phase data in the fault state and the power phase sequence balance relationship in the power failure analysis model to obtain the abnormal phase sequence characteristics corresponding to the power failure state.

[0089] Specifically, input the power phase data in the fault state into the power failure analysis model, perform phase fitting with the power phase sequence balance relationship in the power failure analysis model, and extract the abnormal phase sequence characteristic parameters that do not conform to the power phase sequence balance relationship according to the fitting result to obtain the abnormal phase sequence characteristics corresponding to the power failure state.

[0090] S402: Through a preset fault code generation mechanism, perform fault code conversion processing on the abnormal phase sequence characteristics to obtain the fault code parameters corresponding to the current power failure.

[0091] Specifically, perform fault code conversion processing on the abnormal phase sequence characteristics through the fault code generation mechanism of the threshold, and reduce the comparison steps between the abnormal phase sequence characteristic parameters through the fault code parameters.

[0092] S403: Perform fault code matching processing on the fault code parameters and a preset power failure library, and select the power failure type with the highest matching degree for power failure location to obtain the power failure detection data corresponding to the current fault power phase.

[0093] Specifically, perform fault code matching processing on the fault code parameters and a preset power failure database, select the power failure type with the highest matching degree from the database for power failure location to obtain the fault type corresponding to the current power failure, so as to obtain the power failure detection data corresponding to the current fault power phase.

[0094] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0095] In one embodiment, a power failure detection system for an air conditioning equipment is provided. The power failure detection system for the air conditioning equipment corresponds one-to-one to the power failure detection method of the air conditioning equipment in the above embodiment. As Figure 6As shown in the figure, the power failure detection system of the air conditioning equipment includes a data acquisition module, a data analysis module, a model construction module, and a fault detection module. The detailed descriptions of each functional module are as follows:

[0096] The data acquisition module is used to respectively obtain the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioning equipment under the power-on state, and perform data cleaning processing to obtain the preprocessed air conditioning operation data.

[0097] The data analysis module is used to obtain the power phase waveforms between the main board, transformer, and power plug of the air conditioning equipment according to the air conditioning operation data, and analyze the power phase sequence balance relationship of the air conditioning equipment according to the power phase waveforms.

[0098] The model construction module is used to obtain the historical fault data of the air conditioning equipment, analyze the abnormal power phase sequence in combination with the power phase sequence balance relationship, and construct a power fault analysis model for analyzing the power fault of the air conditioning equipment according to the analysis results.

[0099] The fault detection module is used to obtain the power phase data under the power failure state of the air conditioning equipment, input the power phase data into the power fault analysis model for power fault analysis, and obtain the power fault detection data corresponding to the current power fault phase.

[0100] Preferably, the data analysis module specifically includes:

[0101] The phase analysis sub-module is used to respectively draw the operation phase waveforms of the main board, transformer, and power plug of the air conditioning equipment according to the air conditioning operation data, and perform phase correlation in the order of operation time to obtain the power phase waveform of the air conditioning equipment.

[0102] The deviation analysis sub-module is used to calculate the waveform deviation between adjacent phase waveforms according to the power phase waveform, and analyze the power phase deviation trend of the air conditioning equipment according to the waveform deviation to obtain phase deviation analysis data.

[0103] The data grouping sub-module is used to split the power phase waveform into a power phase stable group and a power phase unstable group with the initial position of the phase deviation as the boundary according to the power phase waveform and the phase deviation analysis data.

[0104] The relationship construction sub-module is used to perform power phase sequence comparison and analysis on the power phase stable group and the power phase unstable group respectively, extract the unbalanced phase sequence characteristics according to the comparison results, and construct the power phase sequence balance relationship of the air conditioning equipment according to the common characteristics between the unbalanced phase sequence characteristics.

[0105] Preferably, the model construction module specifically includes:

[0106] A data training sub-module, which is used to obtain the historical fault data of the air conditioner equipment, perform data training on the power supply phase sequence balance relationship with the historical fault data as the training samples, and obtain the historical unbalanced phase sequence characteristics related to the historical faults according to the training results.

[0107] A commonality analysis sub-module, which is used to perform feature commonality analysis of abnormal power supply phase sequence characteristics on the power supply phase sequence balance relationship according to the historical unbalanced phase sequence characteristics and the corresponding abnormal phase sequence sites, and obtain the feature commonality correlation relationship of the abnormal power supply phase sequence characteristics.

[0108] A model construction sub-module, which is used to construct a power supply fault analysis model for analyzing the power supply faults of the air conditioner equipment according to the feature commonality correlation relationship.

[0109] Preferably, the fault detection module specifically includes:

[0110] An abnormal analysis sub-module, which is used to perform phase fitting analysis on the power supply phase data in the fault state and the power supply phase sequence balance relationship in the power supply fault analysis model to obtain the abnormal phase sequence characteristics corresponding to the power supply fault state.

[0111] A data transcoding sub-module, which is used to perform fault code conversion processing on the abnormal phase sequence characteristics through a preset fault code generation mechanism to obtain the fault code parameters corresponding to the current power supply fault.

[0112] A fault location sub-module, which is used to perform fault code matching processing on the fault code parameters with a preset power supply fault library, and select the power supply fault type with the highest matching degree for power supply fault location to obtain the power supply fault detection data corresponding to the current fault power supply phase.

[0113] Preferably, the data acquisition module specifically includes:

[0114] A main board data acquisition sub-module, which is used to obtain the main board voltage detection value of the air conditioner equipment under the powered-on state, compare the main board voltage detection value with the preset main board operating voltage, and obtain the main board operating data.

[0115] A transformer data acquisition sub-module, which is used to obtain the primary voltage of the transformer winding and the secondary voltage of the transformer winding respectively, and analyze whether the power supply transformer of the air conditioner equipment is in a stable voltage transformation state to obtain the transformer operating data.

[0116] A plug data acquisition sub-module, which is used to obtain the plug voltage detection value corresponding to the power supply of the air conditioner equipment, and analyze whether the plug voltage detection value is adapted to the preset rated voltage of the air conditioner equipment to obtain the plug operating data corresponding to the power supply of the air conditioner equipment.

[0117] A data processing sub-module, which is used to perform data cleaning processing on the main board operating data, transformer operating data and plug operating data respectively to obtain the preprocessed air conditioner operating data.

[0118] For the specific limitations of the power failure detection system of the air conditioning equipment, reference can be made to the limitations of the power failure detection method of the air conditioning equipment in the above text, which will not be elaborated here. Each module in the above power failure detection system of the air conditioning equipment can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0119] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 7 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the power failure detection data of the air conditioning equipment. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a power failure detection method for an air conditioning equipment.

[0120] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of a power failure detection method for an air conditioning equipment as follows.

[0121] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0122] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example for illustration. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0123] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A power failure detection method for an air conditioning device, characterized in that, Including: Obtain the main board voltage detection value, transformer voltage detection value, and plug voltage detection value of the air conditioner equipment under the power-on state respectively, and perform data cleaning processing to obtain the preprocessed air conditioner operation data; Obtain the power phase waveforms among the main board, transformer, and power plug of the air conditioner equipment according to the air conditioner operation data, and analyze the power phase sequence balance relationship of the air conditioner equipment according to the power phase waveforms; Obtain the historical fault data of the air conditioner equipment, analyze the abnormal power phase sequence in combination with the power phase sequence balance relationship, and construct a power fault analysis model for analyzing the power fault of the air conditioner equipment according to the analysis results; Obtain the power phase data under the power fault state of the air conditioner equipment, input the power phase data into the power fault analysis model for power fault analysis, and obtain the power fault detection data corresponding to the current power fault phase; Among them, the obtaining the historical fault data of the air conditioner equipment, analyzing the abnormal power phase sequence in combination with the power phase sequence balance relationship, and constructing a power fault analysis model for analyzing the power fault of the air conditioner equipment according to the analysis results specifically includes: Obtain the historical fault data of the air conditioner equipment, perform data training on the power phase sequence balance relationship with the historical fault data as the training sample, and obtain the historical unbalanced phase sequence characteristics related to the historical faults according to the training results; Perform feature commonality analysis on the abnormal power phase sequence characteristics of the power phase sequence balance relationship according to the historical unbalanced phase sequence characteristics and the corresponding abnormal phase sequence sites, and obtain the feature commonality correlation relationship of the abnormal power phase sequence characteristics; Construct a power fault analysis model for analyzing the power fault of the air conditioner equipment according to the feature commonality correlation relationship; Among them, the obtaining the power phase data under the power fault state of the air conditioner equipment, inputting the power phase data into the power fault analysis model for power fault analysis, and obtaining the power fault detection data corresponding to the current power fault phase specifically includes: Perform phase fitting analysis on the power phase data in the fault state and the power phase sequence balance relationship in the power fault analysis model to obtain the abnormal phase sequence characteristics corresponding to the power fault state; Through a preset fault code generation mechanism, perform fault code conversion processing on the abnormal phase sequence characteristics to obtain the fault code parameters corresponding to the current power fault; Perform fault code matching processing on the fault code parameters with a preset power fault library, and select the power fault type with the highest matching degree for power fault location to obtain the power fault detection data corresponding to the current fault power phase.

2. The power failure detection method for an air conditioning device according to claim 1, characterized in that, The obtaining the power phase waveforms among the main board, transformer, and power plug of the air conditioner equipment according to the air conditioner operation data, and analyzing the power phase sequence balance relationship of the air conditioner equipment according to the power phase waveforms specifically includes: Respectively draw the operation phase waveforms of the main board, transformer, and power plug of the air conditioner equipment according to the air conditioner operation data, and perform phase association in the order of operation time to obtain the power phase waveforms of the air conditioner equipment; Calculate the waveform deviation between adjacent phase waveforms according to the power phase waveforms, and analyze the power phase deviation trend of the air conditioner equipment according to the waveform deviation to obtain phase deviation analysis data; According to the power supply phase waveform and the phase deviation analysis data, the power supply phase waveform is split into a power supply phase stable group and a power supply phase unstable group with the initial position of the phase deviation as the boundary; The power supply phase sequence comparison and analysis are respectively carried out for the power supply phase stable group and the power supply phase unstable group. According to the comparison results, the unbalanced phase sequence characteristics are extracted, and the power supply phase sequence balance relationship of the air-conditioning equipment is constructed based on the common characteristics among the unbalanced phase sequence characteristics.

3. The power failure detection method of the air conditioning equipment according to claim 1, characterized in that The motherboard voltage detection value, the transformer voltage detection value, and the plug voltage detection value of the air-conditioning equipment in the powered-on state are respectively obtained and subjected to data cleaning processing to obtain the preprocessed air-conditioning operation data, specifically including: Obtain the motherboard voltage detection value of the air-conditioning equipment in the powered-on state, compare the motherboard voltage detection value with the preset motherboard operating voltage to obtain the motherboard operation data; Respectively obtain the primary voltage of the transformer winding and the secondary voltage of the transformer winding, and analyze whether the power transformer of the air-conditioning equipment is in a stable voltage transformation state to obtain the transformer operation data; Obtain the plug voltage detection value corresponding to the power supply of the air-conditioning equipment, and analyze whether the plug voltage detection value is adapted to the preset rated voltage of the air-conditioning equipment to obtain the plug operation data corresponding to the power supply of the air-conditioning equipment; Perform data cleaning processing on the motherboard operation data, the transformer operation data, and the plug operation data respectively to obtain the preprocessed air-conditioning operation data.

4. A power failure detection system for an air conditioning device, characterized in that, Including: A data acquisition module, which is used to respectively obtain the motherboard voltage detection value, the transformer voltage detection value, and the plug voltage detection value of the air-conditioning equipment in the powered-on state and perform data cleaning processing to obtain the preprocessed air-conditioning operation data; A data analysis module, which is used to obtain the power supply phase waveform among the motherboard, the transformer, and the power plug of the air-conditioning equipment according to the air-conditioning operation data, and analyze the power supply phase sequence balance relationship of the air-conditioning equipment according to the power supply phase waveform; A model construction module, which is used to obtain the historical fault data of the air-conditioning equipment, analyze the abnormal power supply phase sequence in combination with the power supply phase sequence balance relationship, and construct a power supply fault analysis model for analyzing the power supply fault of the air-conditioning equipment according to the analysis results; A fault detection module, which is used to obtain the power supply phase data in the power supply fault state of the air-conditioning equipment, input the power supply phase data into the power supply fault analysis model for power supply fault analysis, and obtain the power supply fault detection data corresponding to the current power supply fault phase; Among them, the model construction module specifically includes: A data training sub-module, which is used to obtain the historical fault data of the air-conditioning equipment, perform data training on the power supply phase sequence balance relationship with the historical fault data as the training samples, and obtain the historical unbalanced phase sequence characteristics related to the historical faults according to the training results; A commonality analysis sub-module, which is used to perform feature commonality analysis on the abnormal power supply phase sequence characteristics of the power supply phase sequence balance relationship according to the historical unbalanced phase sequence characteristics and the corresponding abnormal phase sequence sites, and obtain the feature commonality correlation relationship of the abnormal power supply phase sequence characteristics; A model construction sub-module, which is used to construct a power supply fault analysis model for analyzing the power supply fault of the air-conditioning equipment according to the feature commonality correlation relationship; Among them, the fault detection module specifically includes: Anomaly analysis sub-module, configured to perform phase fitting analysis on the power supply phase data in the fault state with the power supply phase sequence balance relationship in the power supply fault analysis model, so as to obtain the abnormal phase sequence characteristics corresponding to the power supply fault state; Data transcoding sub-module, configured to perform fault code conversion processing on the abnormal phase sequence characteristics through a preset fault code generation mechanism, so as to obtain the fault code parameters corresponding to the current power supply fault; Fault location sub-module, configured to perform fault code matching processing on the fault code parameters with a preset power supply fault library, and select the power supply fault type with the highest matching degree for power supply fault location, so as to obtain the power supply fault detection data corresponding to the current fault power supply phase.

5. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the power supply fault detection method of the air conditioning equipment according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the power supply fault detection method of the air conditioning equipment according to any one of claims 1 to 3.

Images