A fault detection method and detection system for intelligent distribution box

Abstract

The present invention relates to the technical field of fault detection of distribution boxes, and specifically, to a fault detection method and detection system for intelligent distribution boxes. The method comprises the following steps: S1, accessing the intelligent distribution box, and obtaining the operating circuit status and electronic component status in the intelligent distribution box; S2, matching the operating circuit and the electronic component according to the usage correlation, obtaining the operating circuit corresponding to the electronic component, and at the same time, according to the historical operating data of the operating circuit, the influence association between different operating circuits is carried out, and the influence-related circuit of each operating circuit is obtained; by collecting the data of the abnormal circuit and performing the power variable test adjustment, the circuit that is not operating normally can be accurately identified, and by using the logic of restoring normal detection and comparing the test results, the circuit that really needs to be repaired can be effectively screened out to avoid false alarms and missed alarms, and the formulaic decision-making process enables the system to automatically process a large amount of data.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution box fault detection, and in particular to a fault detection method and a detection system for an intelligent distribution box. Background Art

[0002] In the field of intelligent distribution boxes, fault detection plays a vital role. Its main function is to monitor the status of power distribution in real time, identify and locate circuit faults in time, and ensure the stability and safety of the power system.

[0003] At present, the fault detection technology in the intelligent distribution box usually detects whether there is an abnormality in the circuit through real-time monitoring of key parameters such as current and voltage. When abnormal data is found, an alarm will be triggered and the fault information will be recorded for subsequent processing and maintenance. This method can effectively detect faults in most cases and protect equipment from serious damage. However, when a circuit fails, other circuits may be affected and become abnormal, resulting in a large number of faulty circuits requiring fault maintenance in the reporting list, false alarms and missed alarms, and affecting the efficiency of maintenance. Therefore, a fault detection method and detection system for an intelligent distribution box are proposed. Summary of the invention

[0004] The object of the present invention is to provide a fault detection method and a detection system for an intelligent distribution box to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, one of the objectives of the present invention is to provide a fault detection method for an intelligent distribution box, comprising the following steps:

[0006] S1. Access the intelligent distribution box to obtain the operating circuit status and electronic component status in the intelligent distribution box;

[0007] S2. Match the operating circuit and the electronic component according to the usage correlation to obtain the operating circuit corresponding to the electronic component, and at the same time, associate the influences between different operating circuits according to the historical operation data of the operating circuit to obtain the influence-related circuit of each operating circuit;

[0008] S3, diagnose the abnormality of the running circuit state according to the state of the electronic components, and mark the running circuit with abnormal diagnosis as abnormal;

[0009] S4, matching and screening the abnormal operation circuits with the related circuits that affect each operation circuit, obtaining the percentage value of the related circuits that affect each abnormal operation circuit, and then sorting the abnormal operation circuits according to the percentage value comparison;

[0010] S5, combining the sorted abnormal operation circuit list with electronic components in turn to perform power variable adjustment tests, obtain test results of the abnormal operation circuits, and test and delete the abnormal operation circuit list during the test process according to the test results;

[0011] S6. Integrate the test results of the abnormal operation circuit and locate the fault of the abnormal operation circuit.

[0012] As a further improvement of the present technical solution, the S1 is connected to the smart distribution box through a wireless network to extract parameter data collected by sensors inside the smart distribution box, and then the parameter data is classified according to the operating circuit and electronic components, so as to obtain the operating circuit status and electronic component status in real time.

[0013] As a further improvement of the technical solution, the steps of S2 are as follows:

[0014] S2.1. Matching the operating circuits and the electronic components according to the usage correlation, thereby counting the operating circuits controlled by the electronic components and obtaining the operating circuits corresponding to each electronic component;

[0015] S2.2. Collect the historical operation data of each operating circuit, and then combine the historical operation data of different operating circuits to perform fault impact correlation analysis between different operating circuits, and obtain the related circuits that will be affected by the fault of each operating circuit, which are called impact-related circuits.

[0016] As a further improvement of this technical solution, the steps of S3 are as follows:

[0017] S3.1. Predict the normal parameter range of each operating circuit based on the status of electronic components;

[0018] S3.2. The operating circuit state is combined with the predicted normal parameter range for abnormal diagnosis. When the operating circuit state is not within the normal parameter range, it is judged as abnormal. Otherwise, if the operating circuit state is within the normal parameter range, monitoring will continue.

[0019] As a further improvement of the technical solution, the step of S4 is as follows:

[0020] S4.1. Match and screen all marked abnormal operation circuits with the relevant circuits that have impact, and screen out the relevant circuits that have impact on each abnormal operation circuit;

[0021] S4.2. Perform a ratio analysis on the influencing related circuits in combination with all marked abnormal operation circuits, obtain the ratio value of the influencing related circuits of each abnormal operation circuit, and then sort the abnormal operation circuits according to the ratio value comparison.

[0022] As a further improvement of the present technical solution, when S4.2 is sorting the list, the higher the proportion value, the higher the ranking, and vice versa, the higher the proportion value, the lower the ranking.

[0023] As a further improvement of the technical solution, the step of S5 is as follows:

[0024] S5.1. Combine the abnormal operation circuit list with the electronic components in turn to perform power variable test adjustment to obtain the test results of the abnormal operation circuit;

[0025] S5.2. Real-time detection of the test results of S5.1. When the test results show that other abnormally operating circuits have returned to normal after the power variable test adjustment, the abnormally operating circuit that has returned to normal will be deleted from the list of abnormally operating circuits that have not been tested.

[0026] As a further improvement of the present technical solution, the S6 collects the abnormal operating circuit that has been adjusted through the power variable test, and then performs a recovery to normal detection on the test results. When it is detected that the abnormal operating circuit has recovered to normal in the test results of other abnormal operating circuits, it is not retained. On the contrary, when it is detected that the abnormal operating circuit has not recovered to normal in the test results of other abnormal operating circuits, it is retained and reported as a faulty operating circuit for repair.

[0027] The second object of the present invention is to provide a fault detection system for an intelligent distribution box, comprising any one of the above-mentioned fault detection methods for an intelligent distribution box, including an impact association unit, an abnormal circuit sorting unit and a fault location unit;

[0028] The impact association unit is used to access the intelligent distribution box, obtain the operating circuit status and electronic component status in the intelligent distribution box, and at the same time, perform impact association between different operating circuits to obtain the impact-related circuits of each operating circuit;

[0029] The abnormal circuit sorting unit is used to perform abnormal diagnosis on the operating circuit state according to the electronic component state, mark the operating circuit with abnormal diagnosis as abnormal, obtain the proportion value of each abnormal operating circuit affecting the related circuit, and then sort the abnormal operating circuits according to the proportion value comparison;

[0030] The fault locating unit is used to sequentially perform power variable adjustment tests on the sorted abnormal operation circuit list in combination with electronic components, and then integrate the test results of the abnormal operation circuit to locate the fault of the abnormal operation circuit.

[0031] Compared with the prior art, the present invention has the following beneficial effects: by collecting data on abnormal circuits and performing power variable tests and adjustments, circuits that are not operating normally can be accurately identified; at the same time, by using the logic of restoring normal detection and comparing test results, circuits that really need to be repaired can be effectively screened out to avoid false alarms and missed alarms; the formulated decision-making process enables the system to automatically process large amounts of data, reduce manual intervention, improve response speed, promptly detect and repair faulty circuits, and improve the overall reliability and stability of the distribution box. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is the overall flow chart of the present invention;

[0033] Figure 2 A flowchart of the related circuits that will be affected by the failure of each running circuit is obtained for the present invention;

[0034] Figure 3 A flowchart of the present invention for predicting the normal parameter range of each operating circuit according to the state of the electronic components;

[0035] Figure 4 It is a flowchart of the present invention for sorting the list of abnormal operation circuits according to the comparison of the percentage values;

[0036] Figure 5 A flowchart of deleting an abnormal operation circuit that has been restored to normal from a list of abnormal operation circuits that have not been tested in the present invention;

[0037] Figure 6 It is a structural principle diagram of the impact association unit of the present invention.

[0038] The meaning of each number in the figure is:

[0039] 10. Impact association unit; 20. Abnormal circuit sorting unit; 30. Fault location unit. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] like Figure 1-6 As shown, one of the purposes of the present invention is to provide a fault detection method for an intelligent distribution box, comprising the following steps:

[0042] S1. Access the intelligent distribution box to obtain the operating circuit status and electronic component status in the intelligent distribution box;

[0043] S1 connects to the smart distribution box through a wireless network, extracts parameter data collected by the sensors inside the smart distribution box, and then classifies the parameter data according to the operating circuit and electronic components, so as to obtain the operating circuit status and electronic component status in real time. The specific working steps are as follows:

[0044] Sensor data collection: Temperature sensors, current sensors, voltage sensors, etc. are installed inside the distribution box. The sensors regularly or continuously collect parameter data such as current, voltage, and temperature.

[0045] Wireless data transmission: Configure wireless modules such as Wi-Fi, Zigbee or LoRa to achieve data transmission, and then send the data collected by the sensor to the cloud server through the wireless network;

[0046] Data storage: The cloud server receives data and stores it in a database for real-time monitoring and historical analysis;

[0047] Data preprocessing: Remove outliers and noise to ensure data quality, and convert data from different sensors into a unified standard format.

[0048] Parameter classification: extract key features from raw data, such as mean, standard deviation, maximum value, etc.;

[0049] Operation circuit classification: Classify the circuit status according to the current and voltage fluctuation patterns;

[0050] Electronic component classification: Analyze the working status of electronic components such as normal, overload, and failure through sensor data.

[0051] S2. Match the operating circuit and the electronic component according to the usage correlation to obtain the operating circuit corresponding to the electronic component, and at the same time, associate the influences between different operating circuits according to the historical operation data of the operating circuit to obtain the influence-related circuit of each operating circuit;

[0052] The steps of S2 are as follows:

[0053] S2.1. Match the operating circuits and electronic components according to the usage correlation, so as to count the operating circuits controlled by the electronic components and obtain the operating circuit corresponding to each electronic component. The formula is as follows:

[0054]

[0055] Among them, the electronic component is A, the operating circuit is B, For correlation, set the correlation threshold to 0.8. >0.8, the matching electronic component A and the operating circuit B are related.

[0056] S2.2. Collect the historical operation data of each operating circuit, and then combine the historical operation data of different operating circuits to perform fault impact correlation analysis between different operating circuits, and obtain the related circuits that will be affected by the failure of each operating circuit, which are called impact-related circuits. The specific working steps are as follows:

[0057] Data collection: Collect historical operating data of each operating circuit, including but not limited to current, voltage, temperature, power and other parameters. These data should include data on normal operating status and fault status;

[0058] Fault identification: Use classification algorithms to identify fault cases in historical data;

[0059] Fault impact correlation analysis: By analyzing the fault data of different circuits, the impact relationship of the fault between circuits can be determined.

[0060] S3, diagnose the abnormality of the running circuit state according to the state of the electronic components, and mark the running circuit with abnormal diagnosis as abnormal;

[0061] The steps for S3 are as follows:

[0062] S3.1. Predict the normal parameter range of each operating circuit based on the status of electronic components;

[0063] Collect circuit parameter data under normal operating conditions, record the specifications and rated parameters of each electronic component, use statistical methods to analyze the data distribution under normal conditions, and determine the range of normal parameters based on statistical data.

[0064] S3.2. The operating circuit state is combined with the predicted normal parameter range for abnormal diagnosis. When the operating circuit state is not within the normal parameter range, it is judged as abnormal. Otherwise, if the operating circuit state is within the normal parameter range, monitoring will continue.

[0065] S4, matching and screening the abnormal operation circuits with the related circuits that affect each operation circuit, obtaining the percentage value of the related circuits that affect each abnormal operation circuit, and then sorting the abnormal operation circuits according to the percentage value comparison;

[0066] The steps of S4 are as follows:

[0067] S4.1. Match and screen all marked abnormal operation circuits with the relevant circuits that have impact, and screen out the relevant circuits that have impact on each abnormal operation circuit;

[0068] S4.2. Perform a ratio analysis on the influencing related circuits in combination with all marked abnormal operation circuits, obtain the ratio value of the influencing related circuits of each abnormal operation circuit, and then sort the abnormal operation circuits according to the ratio value comparison.

[0069] S4.2 When sorting the list, the higher the percentage value, the higher the ranking. Conversely, the higher the percentage value, the lower the ranking. The specific working steps are as follows:

[0070] Data collation: Collect and mark all circuits identified as abnormal, and determine the impact of each abnormally operating circuit on related circuits;

[0071] Screening and matching: All abnormal operation circuits are matched and screened with the relevant circuits that are affected, and the corresponding relationship between each abnormal circuit and the relevant circuits that are affected is established;

[0072] Proportion analysis: Calculate the proportion of each abnormal operation circuit affecting related circuits. The formula is as follows:

[0073]

[0074] Where F is the proportion, N is the number of related circuits affected, and M is the number of all abnormal circuits marked. For each abnormal circuit, calculate the total number of related circuits affected by it, and compare these numbers with the total number of all abnormal circuits to obtain the proportion value;

[0075] Sorting and comparison: Sort all abnormal operating circuits according to their proportion values, with circuits with higher proportion values ​​at the front. Then list the sorted abnormal operating circuits and their proportion values ​​of related circuits to generate a final report.

[0076] S5, combining the sorted abnormal operation circuit list with electronic components in turn to perform power variable adjustment tests, obtain test results of the abnormal operation circuits, and test and delete the abnormal operation circuit list during the test process according to the test results;

[0077] The steps of S5 are as follows:

[0078] S5.1. Combine the abnormal operation circuit list with the electronic components in turn to perform power variable test adjustment to obtain the test results of the abnormal operation circuit;

[0079] S5.2. Real-time detection of the test results of S5.1. When the test results show that the abnormal operation circuit has other abnormal operation circuits restored to normal after the power variable test adjustment, the abnormal operation circuit restored to normal will be deleted from the list of abnormal operation circuits that have not been tested. The specific working steps are as follows:

[0080] Preparation phase: prepare an initial list of abnormal operating circuits and configure electronic components and power variable test equipment;

[0081] Power variable test adjustment: select each abnormal circuit in the list in turn to perform power variable test adjustment, adjust the power variable for each abnormal circuit and record the test results;

[0082] Real-time monitoring: Real-time monitoring of the circuit status after the test, checking whether any circuit has returned to normal, and judging whether each running circuit has returned to normal and whether the circuit status has returned to the normal parameter range;

[0083] Update the abnormal circuit list: If the test results show that a circuit has returned to normal after the test, delete the circuit from the list and generate an updated abnormal circuit list, removing the circuit that has returned to normal. The formula is as follows:

[0084]

[0085] if Representation circuit Return to normal, then:

[0086]

[0087] Among them, L is the list of abnormal operation circuits, Run the circuit for the ith anomaly in the list, For the test results, represents the jth abnormal operating circuit being tested.

[0088] S6. Integrate the test results of the abnormal operation circuit and locate the fault of the abnormal operation circuit.

[0089] S6 collects the abnormal operation circuit adjusted by the power variable test, and then performs a normal recovery test on the test results. When it is detected that the abnormal operation circuit has recovered to normal in the test results of other abnormal operation circuits, it is not retained. On the contrary, when it is detected that the abnormal operation circuit has not recovered to normal in the test results of other abnormal operation circuits, it is retained and reported as a faulty operation circuit for repair. The formula is as follows:

[0090]

[0091] in, For the circuit The test results are in the circuit In the test results, the status of recovery to normal is 1 for recovery to normal, and 0 for failure to recover to normal.

[0092] when That is, there is at least one circuit The test results returned normal and exist If the test result returns to normal, Indicates that the circuit is not retained ;

[0093] On the contrary, the circuit If all other circuits do not return to normal, Indicates reserved circuit And report the repair.

[0094] The second object of the present invention is to provide a fault detection system for an intelligent distribution box, including any one of the above-mentioned fault detection methods for an intelligent distribution box, including an impact association unit 10, an abnormal circuit sorting unit 20 and a fault location unit 30;

[0095] The impact association unit 10 is used to access the intelligent distribution box, obtain the operating circuit status and electronic component status in the intelligent distribution box, and at the same time, perform impact association between different operating circuits to obtain the impact-related circuits of each operating circuit;

[0096] The abnormal circuit sorting unit 20 is used to perform abnormal diagnosis on the operating circuit state according to the electronic component state, mark the operating circuit with abnormal diagnosis as abnormal, obtain the proportion value of each abnormal operating circuit affecting the related circuit, and then sort the abnormal operating circuits according to the proportion value comparison;

[0097] The fault location unit 30 is used to sequentially perform power variable adjustment tests on the sorted abnormal operation circuit list in combination with electronic components, and then integrate the test results of the abnormal operation circuit to locate the fault of the abnormal operation circuit.

[0098] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A fault detection method for an intelligent distribution box, characterized in that: The steps include: S1. Access the intelligent distribution box to obtain the operating circuit status and electronic component status in the intelligent distribution box; S2. Match the operating circuit and the electronic component according to the usage correlation to obtain the operating circuit corresponding to the electronic component, and at the same time, associate the influences between different operating circuits according to the historical operation data of the operating circuit to obtain the influence-related circuit of each operating circuit; S3, diagnose the abnormality of the running circuit state according to the state of the electronic components, and mark the running circuit with abnormal diagnosis as abnormal; S4, matching and screening the abnormal operation circuits with the relevant circuits that affect each operation circuit, obtaining the percentage value of the relevant circuits that affect each abnormal operation circuit, and then sorting the abnormal operation circuits according to the percentage value comparison; S5, combining the sorted abnormal operation circuit list with electronic components in turn to perform power variable adjustment tests, obtain test results of the abnormal operation circuits, and test and delete the abnormal operation circuit list during the test process according to the test results; S6. Integrate the test results of the abnormal operation circuit and locate the fault of the abnormal operation circuit; The S6 collects the test results of the abnormal operating circuit after the power variable adjustment test, and performs a normal recovery detection based on the test results. When it is detected that the variable parameters of a certain abnormal operating circuit are restored to the normal operating parameter values ​​during the power variable adjustment test of other abnormal operating circuits, they are not retained. Conversely, when it is detected that the variable parameters of a certain abnormal operating circuit have not been restored to the normal operating parameter values ​​during the power variable adjustment test of other abnormal operating circuits, they are retained and reported as a faulty operating circuit for repair.

2. A fault detection method for an intelligent distribution box according to claim 1, characterized in that: The S1 extracts parameter data collected by sensors inside the intelligent distribution box through a wireless network connection with the intelligent distribution box, and then classifies the parameter data according to the operating circuit and electronic components, thereby obtaining the operating circuit status and electronic component status in real time.

3. A fault detection method for an intelligent distribution box according to claim 1, characterized in that: The steps of S2 are as follows: S2.

1. Matching the operating circuits and the electronic components according to the usage correlation, thereby counting the operating circuits controlled by the electronic components and obtaining the operating circuits corresponding to each electronic component; S2.

2. Collect the historical operation data of each operating circuit, and then combine the historical operation data of different operating circuits to perform fault impact correlation analysis between different operating circuits, and obtain the related circuits that will be affected by the fault of each operating circuit, which are called impact-related circuits.

4. A fault detection method for an intelligent distribution box according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. Predict the normal parameter range of each operating circuit based on the status of electronic components; S3.

2. The operating circuit state is combined with the predicted normal parameter range for abnormal diagnosis. When the operating circuit state is not within the normal parameter range, it is judged as abnormal. On the contrary, if the operating circuit state is within the normal parameter range, monitoring will continue.

5. The fault detection method for an intelligent distribution box according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Match and screen all marked abnormal operation circuits with the relevant circuits that have impact, and screen out the relevant circuits that have impact on each abnormal operation circuit; S4.

2. Perform a ratio analysis on the influencing related circuits in combination with all marked abnormal operation circuits, obtain the ratio value of the influencing related circuits of each abnormal operation circuit, and then sort the abnormal operation circuits according to the ratio value comparison.

6. A fault detection method for an intelligent distribution box according to claim 5, characterized in that: When the S4.2 is used to sort the list, the higher the percentage value, the higher the ranking; conversely, the lower the percentage value, the lower the ranking.

7. A fault detection method for an intelligent distribution box according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. Combine the abnormal operation circuit list with the electronic components in turn to perform power variable test adjustment to obtain the test results of the abnormal operation circuit; S5.

2. Real-time detection of the test results of S5.

1. When the test results show that other abnormally operating circuits have returned to normal after the power variable test adjustment, the abnormally operating circuit that has returned to normal will be deleted from the list of abnormally operating circuits that have not been tested.

8. A fault detection system for an intelligent distribution box is implemented, comprising a fault detection method for an intelligent distribution box according to any one of claims 1 to 7, characterized in that: It comprises an impact association unit (10), an abnormal circuit sorting unit (20) and a fault location unit (30); The impact association unit (10) is used to access the intelligent distribution box, obtain the operating circuit status and electronic component status in the intelligent distribution box, and simultaneously perform impact association between different operating circuits to obtain the impact-related circuits of each operating circuit; The abnormal circuit sorting unit (20) is used to perform abnormal diagnosis on the operating circuit state according to the electronic component state, mark the operating circuit diagnosed as abnormal as abnormal, obtain the percentage value of each abnormal operating circuit affecting related circuits, and then sort the abnormal operating circuits according to the percentage value comparison; The fault locating unit (30) is used to sequentially combine the sorted abnormal operation circuit list with electronic components to perform power variable adjustment tests, and then integrate the test results of the abnormal operation circuits to locate faults in the abnormal operation circuits.

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