Fault processing method and device for Bluetooth module of electric energy meter and electric energy meter

Abstract

The invention discloses a fault processing method and device for a Bluetooth module of an electric energy meter and the electric energy meter. The fault processing method comprises the following steps: S1, acquiring working parameters of the Bluetooth module; s2, analyzing the acquired working parameters of the Bluetooth module through a preset fault detection algorithm; s3, when a fault of the Bluetooth module is detected, generating a fault diagnosis report; s4, based on the fault type, automatically taking corresponding processing measures; s5, carrying out self-inspection on the Bluetooth module, and judging whether the fault is repaired or not; s6, if the fault is not repaired, continuing to execute corresponding processing measures until the fault is repaired or preset processing times are reached; s7, synchronizing data and results in the fault processing process to a data management platform; and S8, displaying the operation state and the fault information of the Bluetooth module on a user terminal interface. According to the invention, the central processing unit receives and analyzes the sensor data, so that the fault type of the Bluetooth module can be quickly and accurately identified, and the real-time performance and the accuracy of fault detection are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy meters, and in particular to a method and device for handling a fault of a Bluetooth module of an electric energy meter, and an electric energy meter. Background Art

[0002] With the development of smart grids, electric energy meters play an increasingly important role in power systems. Electric energy meters are not only used to measure and record energy consumption, but also can transmit data in real time to a data management platform through wireless communication modules (such as Bluetooth modules) to achieve remote monitoring, data analysis and management. However, the Bluetooth modules in existing electric energy meters are prone to various faults during operation, such as communication interruption, power failure, signal interference and temperature abnormalities, which can seriously affect the data transmission reliability and user experience of the electric energy meter.

[0003] At present, the existing technology has the following defects in Bluetooth module fault detection and processing:

[0004] Traditional energy meters usually only have simple fault detection functions, and cannot monitor the operating status of the Bluetooth module in real time, nor can they accurately diagnose the type of fault. This makes it difficult for the energy meter to detect the problem in time after a fault occurs, and it often needs to wait for user feedback or regular manual inspections, which delays the timing of fault handling and affects the normal operation of the energy meter.

[0005] When the Bluetooth module of an existing energy meter fails, manual intervention is usually required to handle the failure. This not only increases the operation and maintenance costs and workload, but may also cause long-term data transmission interruptions, reducing the reliability of the energy meter and user satisfaction. Especially in some remote areas or unattended scenarios, manual intervention is even more inconvenient and inefficient.

[0006] The fault handling measures in the prior art are often relatively simple, usually just a simple restart or module replacement, lacking specific handling solutions for different fault types. This one-size-fits-all approach cannot effectively solve complex and diverse fault problems, and is likely to cause waste of resources or improper handling.

[0007] Existing electric energy meters lack systematic data management and analysis capabilities during fault handling. Fault information recording and analysis are often done manually, and the integrity and accuracy of the data are difficult to guarantee. At the same time, the data and results of the fault handling process are not effectively synchronized to the data management platform, which cannot provide reliable data support for subsequent fault analysis and maintenance.

[0008] In summary, the existing technology has many deficiencies in the detection and processing of Bluetooth module faults in electric energy meters. There is an urgent need for a systematic solution that can monitor the operating status of the Bluetooth module in real time, accurately diagnose the fault type, and automatically handle and recover from the fault. Summary of the invention

[0009] An object of the present invention is to provide a fault handling method, device and electric energy meter for a Bluetooth module of an electric energy meter. The present invention receives and analyzes sensor data through a central processing unit, can quickly and accurately identify the fault type of the Bluetooth module, and significantly improves the real-time and accuracy of fault detection.

[0010] A method for troubleshooting a Bluetooth module of an electric energy meter according to an embodiment of the present invention comprises the following steps:

[0011] S1. Real-time monitoring of the operating status of the Bluetooth module of the electric energy meter and obtaining the working parameters of the Bluetooth module;

[0012] S2. Analyze the acquired working parameters of the Bluetooth module through a preset fault detection algorithm to identify the fault type of the Bluetooth module;

[0013] S3. When a Bluetooth module failure is detected, the failure information is automatically recorded and a failure diagnosis report is generated;

[0014] S4. Automatically take corresponding processing measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0015] S5. Perform a self-check on the Bluetooth module to determine whether the fault has been repaired;

[0016] S6. If the fault is not repaired, continue to execute corresponding processing measures until the fault is repaired or the preset number of processing times is reached;

[0017] S7. Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0018] S8. Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions.

[0019] Optionally, the S1 specifically includes:

[0020] S11. Install multiple sensors at different parts of the electric energy meter to collect working parameters of the Bluetooth module. The sensors include:

[0021] Current sensor, used to detect the power status of the Bluetooth module;

[0022] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0023] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0024] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0025] S12, the sensor is connected to the central processing unit through a data bus to transmit the collected working parameter data in real time;

[0026] S13, obtaining the working parameters of the Bluetooth module, including:

[0027] Communication status parameter P comm , which is detected in real time by the communication status detection module and transmitted to the central processing unit through the data bus;

[0028] Power status parameter P power , the current consumption of the Bluetooth module is detected by a current sensor and transmitted to the central processing unit through the data bus;

[0029] Signal strength parameter P signal , the signal strength of the Bluetooth module is detected by the wireless signal strength sensor and transmitted to the central processing unit through the data bus;

[0030] Working temperature parameter P temp ,The current operating temperature of the Bluetooth module is detected by the temperature sensor and is transmitted to the central processing unit through the data bus;

[0031] S14, performing data filtering and denoising on the data collected by each sensor through the data acquisition module.

[0032] Optionally, the S2 specifically includes:

[0033] S21, the central processing unit receives the working parameter data from the sensor, including the communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0034] S22. Based on quantum neural network technology, develop a fault detection algorithm and build a multi-layer quantum neural network model, where the input layer is the preprocessed communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0035] Q input =[P comm ,P power ,P signal ,P temp ];

[0036] S23. Use a label embedding method based on quantum entanglement to associate the fault type label with the quantum state, thereby increasing the perception capability of the multi-layer quantum neural network model to complex fault modes.

[0037]

[0038] Among them, y0 and y1 are quantum tags of fault types;

[0039] Using the quantum supervised learning algorithm, the parameters of the multi-layer quantum neural network model are iteratively adjusted by combining quantum state measurement and classical optimization, so that the probability distribution of the fault type output by the multi-layer quantum neural network model is consistent with the quantum label:

[0040]

[0041] Among them, |ψ i > is the quantum state output by the model, |Φ labeli > is the corresponding quantum label, λ is the regularization parameter, w j is the weight parameter;

[0042] S24. Introduce quantum bit operations in the multi-layer quantum neural network model to capture failure modes and improve the detection capability of various types of failures:

[0043] |ψ>=α|0>+β|1>;

[0044] Among them, α and β are complex coefficients, satisfying |α| 2 +|β| 2 =1;

[0045] S25. Combining quantum entanglement and quantum transcendence technology, the multi-layer quantum neural network model can process high-dimensional data and improve the accuracy of fault detection;

[0046]

[0047] S26, real-time input of the currently monitored communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp into the trained multi-layer quantum neural network model;

[0048] The multi-layer quantum neural network model outputs the probability distribution P of each fault type through quantum neural network calculation. fault_type ;

[0049] P fault_type =QNN(Q input );

[0050] S27, according to the probability distribution P fault_type , select the fault type with the highest probability as the detection result;

[0051] Fault_Type=argmax(P fault_type ).

[0052] Optionally, the S3 specifically includes:

[0053] S31. When the central processing unit detects that the Bluetooth module has a fault, it automatically records the fault information, including the fault type, fault occurrence time, fault parameter value and fault duration;

[0054] S32. The recorded fault types include communication status fault, power status fault, signal strength fault and abnormal temperature fault;

[0055] S33, the recorded fault parameter value includes the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , fault occurrence time T fault and fault duration ΔT fault ;

[0056] S34, fault occurrence time T fault The specific time point when the fault is detected. The record format is:

[0057] YYYY-MM-DDHH:MM:SS;

[0058] S35, fault duration ΔT fault The time interval from fault detection to recovery:

[0059] ΔT fault =T recovery T fault ;

[0060] Among them, T recovery The time point when the failure is restored to normal;

[0061] S36. Automatically generate a fault diagnosis report based on the recorded fault information. The report content includes:

[0062] Fault type;

[0063] Time when the fault occurred;

[0064] Duration of the fault;

[0065] Fault parameter value;

[0066] Troubleshooting measures;

[0067] Troubleshooting results;

[0068] S37. The fault diagnosis report is transmitted to the data management platform via the data bus and synchronized to the user terminal interface.

[0069] Optionally, the S4 specifically includes:

[0070] S41, when the central processing unit identifies the fault type, it automatically takes corresponding processing measures based on the fault type;

[0071] S42, for communication status failure, when P is detected comm <P comm_min or P comm >P comm_max When the error occurs, perform the following actions:

[0072] Try restarting the Bluetooth module;

[0073] If the communication status still does not return to normal after restart, switch to the backup communication channel;

[0074] S43, for power supply status failure, when P power <P power_min or P power >P power_max When the error occurs, perform the following actions:

[0075] Check the power connection status;

[0076] If the power status does not return to normal, switch to the backup power module;

[0077] S44, for signal strength failure, when P is detected signal <P signal_min or P signal >P signal_max When the error occurs, perform the following actions:

[0078] Adjust the direction or position of the antenna;

[0079] If the signal strength still does not return to normal, switch to the backup communication channel;

[0080] S45, for abnormal temperature fault, when P is detected temp <P temp_min or P temp >P temp_max When the error occurs, perform the following actions:

[0081] Stop the Bluetooth module and cool it down;

[0082] If the temperature returns to normal, restart the Bluetooth module;

[0083] S46. The execution status and results of all treatment measures are recorded in the central processing unit and synchronized to the data management platform;

[0084] S47, updating the fault diagnosis report according to the execution result of the processing measures, the report content includes the processing measures, processing time and processing results;

[0085] S48. If all automatic processing measures fail to resolve the fault, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

[0086] Optionally, the S5 specifically includes:

[0087] S51, after executing the corresponding fault handling measures, the central processing unit performs a self-test on the Bluetooth module to detect its working status and parameters;

[0088] S52: During the self-test process, the working parameters of the Bluetooth module are re-obtained, including the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0089] S53, comparing the working parameters obtained during the self-test process with the preset normal working range to determine whether the Bluetooth module has returned to normal:

[0090] I P comm_min ≤P comm ≤P comm_max andP power_min ≤P power ≤

[0091] P power_max andP signal_min ≤P signal ≤P signal_max andP temp_min ≤P temp ≤

[0092] P temp_max ,thenstatus="Normal";

[0093] Else,status="Abnormal";

[0094] S54: According to the comparison result, determine whether the fault has been repaired:

[0095] If all the working parameters of the Bluetooth module are within the normal range, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test results and time;

[0096] If any operating parameter is not within the normal range, the fault has not been repaired and the corresponding treatment measures should be continued.

[0097] Optionally, the S6 specifically includes:

[0098] S61, after executing the self-check S5, if it is detected that the fault of the Bluetooth module has not been repaired, the central processing unit continues to execute corresponding fault handling measures;

[0099] S62, preset the maximum number of processing times, and record the current number of processing times;

[0100] S63. When it is detected that the fault has not been repaired, continue to perform the processing measures according to the following steps:

[0101] Increase the current processing count;

[0102] According to the fault type, re-execute the corresponding processing measures in claim 5;

[0103] Update the implementation status and results of the processing measures and record them in the central processing unit;

[0104] S64, self-check the Bluetooth module and re-acquire the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , and determine whether the fault has been repaired:

[0105] S65. If the working parameters of the Bluetooth module return to normal, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test result and time;

[0106] S66: If the fault has not been repaired and the current processing times are less than the preset maximum processing times, return to step S63 and continue to execute corresponding processing measures;

[0107] S67. If the current processing times have reached the preset maximum processing times, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

[0108] A fault handling device for an electric energy meter Bluetooth module, comprising:

[0109] Multiple sensors are installed at different parts of the electric energy meter to collect the working parameters of the Bluetooth module. The sensors include:

[0110] Current sensor, used to detect the power status of the Bluetooth module;

[0111] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0112] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0113] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0114] A data bus, connected to the sensor, for transmitting the collected working parameter data to the central processing unit in real time;

[0115] Central processing unit, configured as:

[0116] Receive and record operating parameter data from sensors, including communication status parameters, power status parameters, signal strength parameters, and operating temperature parameters;

[0117] Based on the preset fault detection algorithm, the received working parameter data is analyzed to identify the fault type of the Bluetooth module;

[0118] When a Bluetooth module fault is detected, the fault information is automatically recorded, including the fault type, fault occurrence time, fault parameter value and fault duration, and a fault diagnosis report is generated;

[0119] Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0120] Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached;

[0121] Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0122] Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions;

[0123] A fault detection algorithm module, integrated in the central processing unit, is configured to develop a fault detection algorithm based on quantum neural network technology, build a multi-layer quantum neural network model, analyze the working parameter data, and output the probability distribution of the fault type;

[0124] a data management platform, in communication with the central processing unit, configured to receive and store data and results from the fault handling process to support fault analysis and maintenance;

[0125] The user terminal interface communicates with the central processing unit and is configured to display the operating status, fault information and fault handling suggestions of the Bluetooth module.

[0126] An electric energy meter for troubleshooting of an electric energy meter Bluetooth module, comprising:

[0127] The main body of the electric energy meter is used to measure and record the electric energy consumption data;

[0128] Bluetooth module for wireless data transmission;

[0129] The fault handling module is integrated in the main body of the electric energy meter and is used to monitor the operating status of the Bluetooth module in real time, including:

[0130] Current sensor, used to detect the power status of the Bluetooth module;

[0131] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0132] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0133] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0134] Central processing unit, configured as:

[0135] Receive working parameter data from each sensor, analyze the received working parameter data based on a preset fault detection algorithm, and identify the fault type of the Bluetooth module;

[0136] When a Bluetooth module fault is detected, the fault information is automatically recorded and a fault diagnosis report is generated;

[0137] Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0138] Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached;

[0139] Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0140] Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions;

[0141] A storage unit, connected to the central processing unit, for storing a fault detection algorithm and a fault diagnosis report;

[0142] The power module provides power support for the energy meter and Bluetooth module.

[0143] The beneficial effects of the present invention are:

[0144] 1. The present invention integrates multiple sensors in the electric energy meter to monitor the working parameters of the Bluetooth module in real time, including communication status, power status, signal strength and operating temperature. The central processing unit receives and analyzes the sensor data, which can quickly and accurately identify the fault type of the Bluetooth module, significantly improving the real-time and accuracy of fault detection.

[0145] 2. The present invention designs an automated fault handling solution. When a Bluetooth module fault is detected, the system can automatically record the fault information and generate a fault diagnosis report. According to the fault type, corresponding handling measures are automatically taken, such as restarting the Bluetooth module, switching the communication channel, etc., without manual intervention, which improves the efficiency and reliability of fault handling.

[0146] 3. After executing the fault handling measures, the system of the present invention performs a self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, the system will continue to execute the corresponding handling measures until the fault is repaired or the preset number of processing times is reached. Through this mechanism, it is ensured that the fault of the Bluetooth module can be effectively solved, and the operating stability of the electric energy meter is further improved.

[0147] 4. The present invention adopts a fault detection algorithm based on quantum neural network technology, constructs a multi-layer quantum neural network model, and analyzes the working parameters of the Bluetooth module. By introducing quantum entanglement and quantum supervised learning algorithms, the accuracy of fault detection and the ability to perceive complex fault modes are improved, overcoming the limitations of traditional algorithms in processing complex data. BRIEF DESCRIPTION OF THE DRAWINGS

[0148] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0149] Figure 1 A method and device for troubleshooting a Bluetooth module of an electric energy meter and a flow chart of the electric energy meter proposed by the present invention;

[0150] Figure 2 A method and device for handling a fault of a Bluetooth module of an electric energy meter and a structural block diagram of the electric energy meter proposed by the present invention. DETAILED DESCRIPTION

[0151] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0152] refer to Figure 1-2 , a method for troubleshooting a Bluetooth module of an electric energy meter, comprising the following steps:

[0153] S1. Real-time monitoring of the operating status of the Bluetooth module of the electric energy meter and obtaining the working parameters of the Bluetooth module;

[0154] S2. Analyze the acquired working parameters of the Bluetooth module through a preset fault detection algorithm to identify the fault type of the Bluetooth module;

[0155] S3. When a Bluetooth module failure is detected, the failure information is automatically recorded and a failure diagnosis report is generated;

[0156] S4. Automatically take corresponding processing measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0157] S5. Perform a self-check on the Bluetooth module to determine whether the fault has been repaired;

[0158] S6. If the fault is not repaired, continue to execute corresponding processing measures until the fault is repaired or the preset number of processing times is reached;

[0159] S7. Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0160] S8. Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions.

[0161] In this implementation, S1 specifically includes:

[0162] S11. Install multiple sensors at different parts of the electric energy meter to collect working parameters of the Bluetooth module. The sensors include:

[0163] Current sensor, used to detect the power status of the Bluetooth module;

[0164] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0165] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0166] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0167] S12, the sensor is connected to the central processing unit through a data bus to transmit the collected working parameter data in real time;

[0168] S13, obtaining the working parameters of the Bluetooth module, including:

[0169] Communication status parameter P comm , which is detected in real time by the communication status detection module and transmitted to the central processing unit through the data bus;

[0170] Power status parameter P power, the current consumption of the Bluetooth module is detected by a current sensor and transmitted to the central processing unit through the data bus;

[0171] Signal strength parameter P signal , the signal strength of the Bluetooth module is detected by the wireless signal strength sensor and transmitted to the central processing unit through the data bus;

[0172] Working temperature parameter P temp ,The current operating temperature of the Bluetooth module is detected by the temperature sensor and is transmitted to the central processing unit through the data bus;

[0173] S14, performing data filtering and denoising on the data collected by each sensor through the data acquisition module.

[0174] In this implementation, S2 specifically includes:

[0175] S21, the central processing unit receives the working parameter data from the sensor, including the communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0176] S22. Based on quantum neural network technology, develop a fault detection algorithm and build a multi-layer quantum neural network model, where the input layer is the preprocessed communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0177] Q input =[P comm ,P power ,P signal ,P temp ];

[0178] S23. Use a label embedding method based on quantum entanglement to associate the fault type label with the quantum state, thereby increasing the perception capability of the multi-layer quantum neural network model to complex fault modes.

[0179]

[0180] Among them, y0 and y1 are quantum tags of fault types;

[0181] Using the quantum supervised learning algorithm, the parameters of the multi-layer quantum neural network model are iteratively adjusted by combining quantum state measurement and classical optimization, so that the probability distribution of the fault type output by the multi-layer quantum neural network model is consistent with the quantum label:

[0182]

[0183] Among them, |ψ i > is the quantum state output by the model, is the corresponding quantum label, λ is the regularization parameter, w j is the weight parameter;

[0184] S24. Introduce quantum bit operations in the multi-layer quantum neural network model to capture failure modes and improve the detection capability of various types of failures:

[0185] |ψ>=α|0>+β|1>;

[0186] Among them, α and β are complex coefficients, satisfying |α| 2 +|β| 2 =1;

[0187] S25. Combining quantum entanglement and quantum transcendence technology, the multi-layer quantum neural network model can process high-dimensional data and improve the accuracy of fault detection;

[0188]

[0189] S26, real-time input of the currently monitored communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp into the trained multi-layer quantum neural network model;

[0190] The multi-layer quantum neural network model outputs the probability distribution P of each fault type through quantum neural network calculation. fault_type ;

[0191] P fault_type =QNN(Q input );

[0192] S27, according to the probability distribution P fault_type , select the fault type with the highest probability as the detection result;

[0193] Fault_Type=argmax(P fault_type ).

[0194] In this implementation, S3 specifically includes:

[0195] S31. When the central processing unit detects that the Bluetooth module has a fault, it automatically records the fault information, including the fault type, fault occurrence time, fault parameter value and fault duration;

[0196] S32. The recorded fault types include communication status fault, power status fault, signal strength fault and abnormal temperature fault;

[0197] S33, the recorded fault parameter value includes the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , fault occurrence time T fault and fault duration ΔT fault ;

[0198] S34, fault occurrence time T fault The specific time point when the fault is detected. The record format is:

[0199] YYYY-MM-DDHH:MM:SS;

[0200] S35, fault duration ΔT fault The time interval from fault detection to recovery:

[0201] ΔT fault =T recovery T fault ;

[0202] Among them, T recovery The time point when the failure is restored to normal;

[0203] S36. Automatically generate a fault diagnosis report based on the recorded fault information. The report content includes:

[0204] Fault type;

[0205] Time when the fault occurred;

[0206] Duration of the fault;

[0207] Fault parameter value;

[0208] Troubleshooting measures;

[0209] Troubleshooting results;

[0210] S37. The fault diagnosis report is transmitted to the data management platform via the data bus and synchronized to the user terminal interface.

[0211] In this implementation, S4 specifically includes:

[0212] S41, when the central processing unit identifies the fault type, it automatically takes corresponding processing measures based on the fault type;

[0213] S42, for communication status failure, when P is detected comm <Pcomm_min or P comm >P comm_max When the error occurs, perform the following actions:

[0214] Try restarting the Bluetooth module;

[0215] If the communication status still does not return to normal after restart, switch to the backup communication channel;

[0216] S43, for power supply status failure, when P power <P power_min or P power >P power_max When the error occurs, perform the following actions:

[0217] Check the power connection status;

[0218] If the power status does not return to normal, switch to the backup power module;

[0219] S44, for signal strength failure, when P is detected signal <P signal_min or P signal >P signal_max When the error occurs, perform the following actions:

[0220] Adjust the direction or position of the antenna;

[0221] If the signal strength still does not return to normal, switch to the backup communication channel;

[0222] S45, for abnormal temperature fault, when P is detected temp <P temp_min or P temp >P temp_max When the error occurs, perform the following actions:

[0223] Stop the Bluetooth module and cool it down;

[0224] If the temperature returns to normal, restart the Bluetooth module;

[0225] S46. The execution status and results of all treatment measures are recorded in the central processing unit and synchronized to the data management platform;

[0226] S47, updating the fault diagnosis report according to the execution result of the processing measures, the report content includes the processing measures, processing time and processing results;

[0227] S48. If all automatic processing measures fail to resolve the fault, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

[0228] In this implementation, S5 specifically includes:

[0229] S51, after executing the corresponding fault handling measures, the central processing unit performs a self-test on the Bluetooth module to detect its working status and parameters;

[0230] S52: During the self-test process, the working parameters of the Bluetooth module are re-obtained, including the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ;

[0231] S53, comparing the working parameters obtained during the self-test process with the preset normal working range to determine whether the Bluetooth module has returned to normal:

[0232] I P comm_min ≤P comm ≤P comm_max P power_min ≤P power ≤

[0233] P power_max P signal_min ≤P signal ≤P signal_max P temp_min ≤P temp ≤

[0234] P temp_max ,thenstatus="Normal";

[0235] Else,status="Abnormal";

[0236] S54: According to the comparison result, determine whether the fault has been repaired:

[0237] If all the working parameters of the Bluetooth module are within the normal range, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test results and time;

[0238] If any operating parameter is not within the normal range, the fault has not been repaired and the corresponding treatment measures should be continued.

[0239] In this implementation, S6 specifically includes:

[0240] S61, after executing the self-check S5, if it is detected that the fault of the Bluetooth module has not been repaired, the central processing unit continues to execute corresponding fault handling measures;

[0241] S62, preset the maximum number of processing times, and record the current number of processing times;

[0242] S63. When it is detected that the fault has not been repaired, continue to perform the processing measures according to the following steps:

[0243] Increase the current processing count;

[0244] According to the fault type, re-execute the corresponding processing measures in claim 5;

[0245] Update the implementation status and results of the processing measures and record them in the central processing unit;

[0246] S64, self-check the Bluetooth module and re-acquire the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , and determine whether the fault has been repaired:

[0247] S65. If the working parameters of the Bluetooth module return to normal, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test result and time;

[0248] S66: If the fault has not been repaired and the current processing times are less than the preset maximum processing times, return to step S63 and continue to execute corresponding processing measures;

[0249] S67. If the current processing times have reached the preset maximum processing times, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

[0250] A fault handling device for an electric energy meter Bluetooth module, comprising:

[0251] Multiple sensors are installed in different parts of the energy meter to collect the working parameters of the Bluetooth module. The sensors include:

[0252] Current sensor, used to detect the power status of the Bluetooth module;

[0253] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0254] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0255] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0256] A data bus, connected to the sensor, for transmitting the collected working parameter data to the central processing unit in real time;

[0257] Central processing unit, configured as:

[0258] Receive and record operating parameter data from sensors, including communication status parameters, power status parameters, signal strength parameters, and operating temperature parameters;

[0259] Based on the preset fault detection algorithm, the received working parameter data is analyzed to identify the fault type of the Bluetooth module;

[0260] When a Bluetooth module fault is detected, the fault information is automatically recorded, including the fault type, fault occurrence time, fault parameter value and fault duration, and a fault diagnosis report is generated;

[0261] Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0262] Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached;

[0263] Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0264] Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions;

[0265] A fault detection algorithm module, integrated in the central processing unit, is configured to develop a fault detection algorithm based on quantum neural network technology, build a multi-layer quantum neural network model, analyze the working parameter data, and output the probability distribution of the fault type;

[0266] a data management platform, in communication with the central processing unit, configured to receive and store data and results from the fault handling process to support fault analysis and maintenance;

[0267] The user terminal interface communicates with the central processing unit and is configured to display the operating status, fault information and fault handling suggestions of the Bluetooth module.

[0268] An electric energy meter for troubleshooting of an electric energy meter Bluetooth module, comprising:

[0269] The main body of the electric energy meter is used to measure and record the electric energy consumption data;

[0270] Bluetooth module for wireless data transmission;

[0271] The fault handling module is integrated in the main body of the electric energy meter and is used to monitor the operating status of the Bluetooth module in real time, including:

[0272] Current sensor, used to detect the power status of the Bluetooth module;

[0273] Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module;

[0274] Temperature sensor, used to detect the working temperature of the Bluetooth module;

[0275] A communication status detection module is used to detect the communication status of the Bluetooth module;

[0276] Central processing unit, configured as:

[0277] Receive working parameter data from each sensor, analyze the received working parameter data based on a preset fault detection algorithm, and identify the fault type of the Bluetooth module;

[0278] When a Bluetooth module fault is detected, the fault information is automatically recorded and a fault diagnosis report is generated;

[0279] Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel;

[0280] Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached;

[0281] Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance;

[0282] Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions;

[0283] A storage unit, connected to the central processing unit, for storing a fault detection algorithm and a fault diagnosis report;

[0284] The power module provides power support for the energy meter and Bluetooth module.

[0285] Embodiment 1:

[0286] In the power system of a large community, multiple smart energy meters are installed to monitor and record the energy consumption data of each household. These energy meters are equipped with Bluetooth modules to achieve wireless data transmission. However, as time goes by, the Bluetooth modules of some energy meters have experienced varying degrees of failure, such as communication interruption, weak signal, power failure and temperature abnormality, which seriously affects the stability of data transmission and user experience. In order to solve this problem, the community management department decided to apply the energy meter Bluetooth module fault handling method and device of the present invention to perform fault detection and processing.

[0287] In actual applications, the operating status and fault data of the cell's electric energy meter are monitored in real time by sensors and transmitted to the central processing unit. Specifically, the current sensor detects the power status of the Bluetooth module, the wireless signal strength sensor detects the signal strength, the temperature sensor detects the operating temperature, and the communication status detection module monitors the communication status. The central processing unit analyzes the received operating parameter data based on a preset fault detection algorithm and identifies the fault type of the Bluetooth module.

[0288] Once a fault is detected, the system automatically records the fault information and generates a fault diagnosis report. For example, when it is detected that the communication status parameter of the Bluetooth module of a certain electric energy meter is lower than the preset minimum value, the central processing unit identifies the communication interruption fault and automatically records the fault information, including the fault type, fault occurrence time, fault parameter value and fault duration. Subsequently, the system automatically tries to restart the Bluetooth module. If the communication status still does not return to normal after restarting, it switches to the backup communication channel.

[0289] During the self-check process, the system re-acquires the working parameters of the Bluetooth module and determines whether the fault has been repaired. If the fault has not been repaired, the system continues to execute the corresponding processing measures until the fault is repaired or the preset number of processing times is reached. For example, after restarting and switching communication channels many times, the system finally solved the problem of weak signal by adjusting the antenna direction.

[0290] Specific data proves:

[0291] In order to verify the effectiveness of the present invention, we conducted a one-month test on 20 electric energy meters in the community. During the test, the operating status of the Bluetooth module and the fault handling effect were recorded and compared with the traditional method. The comparison data between the traditional method and the present invention method are shown in Table 1:

[0292] Table 1 Comparison data of energy meter Bluetooth module fault handling methods

[0293]

[0294] From the above data, it can be seen that the fault handling method of the present invention significantly shortens the fault duration and improves the fault repair success rate. In the traditional method, the average fault handling duration is 182.25 minutes and the repair success rate is 67.6%; while in the method of the present invention, the average fault handling duration is only 10.95 minutes, and the repair success rate is increased to 93.35%.

[0295] Through the application of the present invention, the efficiency of handling Bluetooth module faults of electric energy meters in a residential area is greatly improved, which not only ensures the stability of data transmission, but also reduces maintenance costs and significantly improves user experience.

[0296] The present invention integrates multiple sensors in the electric energy meter to monitor the working parameters of the Bluetooth module in real time, including communication status, power status, signal strength and working temperature. The central processing unit receives and analyzes the sensor data, and can quickly and accurately identify the fault type of the Bluetooth module, significantly improving the real-time and accuracy of fault detection.

[0297] The present invention designs an automated fault handling solution. When a Bluetooth module fault is detected, the system can automatically record the fault information and generate a fault diagnosis report. According to the fault type, corresponding handling measures are automatically taken, such as restarting the Bluetooth module, switching the communication channel, etc., without manual intervention, thereby improving the efficiency and reliability of fault handling.

[0298] After executing the fault handling measures, the system of the present invention performs a self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, the system will continue to execute the corresponding handling measures until the fault is repaired or the preset number of processing times is reached. Through this mechanism, it is ensured that the fault of the Bluetooth module can be effectively solved, and the operating stability of the electric energy meter is further improved.

[0299] The present invention adopts a fault detection algorithm based on quantum neural network technology, constructs a multi-layer quantum neural network model, and analyzes the working parameters of the Bluetooth module. By introducing quantum entanglement and quantum supervised learning algorithms, the accuracy of fault detection and the ability to perceive complex fault modes are improved, overcoming the limitations of traditional algorithms in processing complex data.

[0300] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for troubleshooting a Bluetooth module of an electric energy meter, characterized in that: The steps include: S1. Real-time monitoring of the operating status of the Bluetooth module of the electric energy meter and obtaining the working parameters of the Bluetooth module; S2. Analyze the acquired working parameters of the Bluetooth module through a preset fault detection algorithm to identify the fault type of the Bluetooth module; S3. When a Bluetooth module failure is detected, the failure information is automatically recorded and a failure diagnosis report is generated; S4. Automatically take corresponding processing measures based on the fault type, including restarting the Bluetooth module and switching the communication channel; S5. Perform a self-check on the Bluetooth module to determine whether the fault has been repaired; S6. If the fault is not repaired, continue to execute corresponding processing measures until the fault is repaired or the preset number of processing times is reached; S7. Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance; S8. Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions.

2. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 1, characterized in that: The S1 specifically includes: S11. Install multiple sensors at different parts of the electric energy meter to collect working parameters of the Bluetooth module. The sensors include: Current sensor, used to detect the power status of the Bluetooth module; Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module; Temperature sensor, used to detect the working temperature of the Bluetooth module; A communication status detection module is used to detect the communication status of the Bluetooth module; S12, the sensor is connected to the central processing unit through a data bus to transmit the collected working parameter data in real time; S13, obtaining the working parameters of the Bluetooth module, including: Communication status parameter P comm , which is detected in real time by the communication status detection module and transmitted to the central processing unit through the data bus; Power status parameter P power , the current consumption of the Bluetooth module is detected by a current sensor and transmitted to the central processing unit through the data bus; Signal strength parameter P signal , the signal strength of the Bluetooth module is detected by the wireless signal strength sensor and transmitted to the central processing unit through the data bus; Working temperature parameter P temp ,The current operating temperature of the Bluetooth module is detected by the temperature sensor and is transmitted to the central processing unit through the data bus; S14, performing data filtering and denoising on the data collected by each sensor through the data acquisition module.

3. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 2, characterized in that: The S2 specifically includes: S21, the central processing unit receives the working parameter data from the sensor, including the communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ; S22. Based on quantum neural network technology, develop a fault detection algorithm and build a multi-layer quantum neural network model, where the input layer is the preprocessed communication state parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ; Q input =[P comm ,P power ,P signal ,P temp ]; Among them, Q input Represents the input data of the quantum input layer; S23. Use a label embedding method based on quantum entanglement to associate the fault type label with the quantum state, thereby increasing the perception capability of the multi-layer quantum neural network model to complex fault modes. Among them, y0 and y1 are quantum tags of fault types; Using the quantum supervised learning algorithm, the parameters of the multi-layer quantum neural network model are iteratively adjusted by combining quantum state measurement and classical optimization, so that the probability distribution of the fault type output by the multi-layer quantum neural network model is consistent with the quantum label: Among them, |ψ i > is the quantum state output by the model, is the corresponding quantum label, λ is the regularization parameter, w j is the weight parameter; S24. Introduce quantum bit operations in the multi-layer quantum neural network model to capture failure modes and improve the detection capability of various types of failures: |ψ>=α|0>+β|1>; Among them, α and β are complex coefficients, satisfying |α| 2 +|β| 2 =1, |ψ> represents the quantum state of the quantum bit; S25. Combining quantum entanglement and quantum transcendence technology, the multi-layer quantum neural network model can process high-dimensional data and improve the accuracy of fault detection; Among them, |Φ + > represents the quantum entangled state, which is Bell state or EPR pair; S26, real-time input of the currently monitored communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp into the trained multi-layer quantum neural network model; The multi-layer quantum neural network model outputs the probability distribution P of each fault type through quantum neural network calculation. fault_type ; P fault_type =QNN(Q input ); S27, according to the probability distribution P fault_type , select the fault type with the highest probability as the detection result; Fault_Type=argmax(P fault_type )。 4. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 3, characterized in that: The S3 specifically includes: S31. When the central processing unit detects that the Bluetooth module has a fault, it automatically records the fault information, including the fault type, fault occurrence time, fault parameter value and fault duration; S32. The recorded fault types include communication status fault, power status fault, signal strength fault and abnormal temperature fault; S33, the recorded fault parameter value includes the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , fault occurrence time T fault and fault duration ΔT fault ; S34, fault occurrence time T fault The specific time point when the fault is detected. The record format is: YYYY-MM-DDHH:MM:SS; S35, fault duration ΔT fault The time interval from fault detection to recovery: ΔT fault =T recovery T fault ; Among them, T recovery The time point when the failure is restored to normal; S36. Automatically generate a fault diagnosis report based on the recorded fault information. The report content includes: Fault type; Time when the fault occurred; Duration of the fault; Fault parameter value; Troubleshooting measures; Troubleshooting results; S37. The fault diagnosis report is transmitted to the data management platform via the data bus and synchronized to the user terminal interface.

5. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 4, characterized in that: The S4 specifically includes: S41, when the central processing unit identifies the fault type, it automatically takes corresponding processing measures based on the fault type; S42, for communication status failure, when P is detected comm <P comm_min or P comm >P comm_max When the error occurs, perform the following actions: Try restarting the Bluetooth module; If the communication status still does not return to normal after restart, switch to the backup communication channel; S43, for power supply status failure, when P power <P power_min or P power >P power_max When the error occurs, perform the following actions: Check the power connection status; If the power status does not return to normal, switch to the backup power module; S44, for signal strength failure, when P is detected signal <P signal_min or P signal >P signal_max When the error occurs, perform the following actions: Adjust the direction or position of the antenna; If the signal strength still does not return to normal, switch to the backup communication channel; S45, for abnormal temperature fault, when P is detected temp <P temp_min or P temp >P temp_max When the error occurs, perform the following actions: Stop the Bluetooth module and cool it down; If the temperature returns to normal, restart the Bluetooth module; S46. The execution status and results of all treatment measures are recorded in the central processing unit and synchronized to the data management platform; S47, updating the fault diagnosis report according to the execution result of the processing measures, the report content includes the processing measures, processing time and processing results; S48. If all automatic processing measures fail to resolve the fault, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

6. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 5, characterized in that: The S5 specifically includes: S51, after executing the corresponding fault handling measures, the central processing unit performs a self-test on the Bluetooth module to detect its working status and parameters; S52: During the self-test process, the working parameters of the Bluetooth module are re-obtained, including the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp ; S53, comparing the working parameters obtained during the self-test process with the preset normal working range to determine whether the Bluetooth module has returned to normal: IfP comm_min ≤P comm ≤P comm_max andP power_min ≤P power ≤ P power_max andP signal_min ≤P signal ≤P signal_max andP temp_min ≤P temp ≤ P temp_max ,thenstatus="Normal"; Else,status="Abnormal"; S54: According to the comparison result, determine whether the fault has been repaired: If all the working parameters of the Bluetooth module are within the normal range, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test results and time; If any operating parameter is not within the normal range, the fault has not been repaired and the corresponding treatment measures should be continued.

7. A method for troubleshooting a Bluetooth module of an electric energy meter according to claim 6, characterized in that: The S6 specifically includes: S61, after executing the self-check S5, if it is detected that the fault of the Bluetooth module has not been repaired, the central processing unit continues to execute corresponding fault handling measures; S62, preset the maximum number of processing times, and record the current number of processing times; S63. When it is detected that the fault has not been repaired, continue to perform the processing measures according to the following steps: Increase the current processing count; According to the fault type, re-execute the corresponding processing measures in claim 5; Update the implementation status and results of the processing measures and record them in the central processing unit; S64, self-check the Bluetooth module and re-acquire the communication status parameter P comm , power status parameter P power , signal strength parameter P signal And the operating temperature parameter P temp , and determine whether the fault has been repaired: S65. If the working parameters of the Bluetooth module return to normal, the fault has been repaired, and the fault diagnosis report is updated, recording the self-test result and time; S66: If the fault has not been repaired and the current processing times are less than the preset maximum processing times, return to step S63 and continue to execute corresponding processing measures; S67. If the current processing times have reached the preset maximum processing times, the system generates a manual intervention prompt and displays detailed fault information and recommended manual processing steps on the user terminal interface.

8. A fault handling device for a Bluetooth module of an electric energy meter, characterized in that: include: Multiple sensors are installed at different parts of the electric energy meter to collect the working parameters of the Bluetooth module. The sensors include: Current sensor, used to detect the power status of the Bluetooth module; Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module; Temperature sensor, used to detect the working temperature of the Bluetooth module; A communication status detection module is used to detect the communication status of the Bluetooth module; A data bus, connected to the sensor, for transmitting the collected working parameter data to the central processing unit in real time; Central processing unit, configured as: Receive and record operating parameter data from sensors, including communication status parameters, power status parameters, signal strength parameters, and operating temperature parameters; Based on the preset fault detection algorithm, the received working parameter data is analyzed to identify the fault type of the Bluetooth module; When a Bluetooth module fault is detected, the fault information is automatically recorded, including the fault type, fault occurrence time, fault parameter value and fault duration, and a fault diagnosis report is generated; Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel; Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached; Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance; Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions; A fault detection algorithm module, integrated in the central processing unit, is configured to develop a fault detection algorithm based on quantum neural network technology, build a multi-layer quantum neural network model, analyze the working parameter data, and output the probability distribution of the fault type; a data management platform, in communication with the central processing unit, configured to receive and store data and results from the fault handling process to support fault analysis and maintenance; The user terminal interface communicates with the central processing unit and is configured to display the operating status, fault information and fault handling suggestions of the Bluetooth module.

9. An electric energy meter with a fault handling function for a bluetooth module of the electric energy meter, characterized in that: include: The main body of the electric energy meter is used to measure and record the electric energy consumption data; Bluetooth module for wireless data transmission; The fault handling module is integrated in the main body of the electric energy meter and is used to monitor the operating status of the Bluetooth module in real time, including: Current sensor, used to detect the power status of the Bluetooth module; Wireless signal strength sensor, used to detect the signal strength of the Bluetooth module; Temperature sensor, used to detect the working temperature of the Bluetooth module; A communication status detection module is used to detect the communication status of the Bluetooth module; Central processing unit, configured as: Receive working parameter data from each sensor, analyze the received working parameter data based on a preset fault detection algorithm, and identify the fault type of the Bluetooth module; When a Bluetooth module fault is detected, the fault information is automatically recorded and a fault diagnosis report is generated; Automatically take appropriate measures based on the fault type, including restarting the Bluetooth module and switching the communication channel; Perform self-check on the Bluetooth module to determine whether the fault has been repaired. If the fault has not been repaired, continue to execute corresponding processing measures until the fault is repaired or the preset processing times are reached; Synchronize the data and results of the fault handling process to the data management platform for subsequent analysis and maintenance; Display the operating status and fault information of the Bluetooth module on the user terminal interface, and provide user feedback and operation suggestions; A storage unit, connected to the central processing unit, for storing a fault detection algorithm and a fault diagnosis report; The power module provides power support for the energy meter and Bluetooth module.

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