A system for fundamentally solving leakage current problems based on accurate fault current identification

Abstract

The present invention relates to the technical field of fault current identification, and discloses a leakage nature solution system based on accurate fault current identification, comprising a thermal infrared image acquisition module, a current monitoring module, a temperature acquisition module, a current acquisition unit control module, a historical leakage fault information storage module and an analysis module. The current acquisition unit control module analyzes current information data and temperature information data of an accessed electrical device to obtain a state judgment index of the current acquisition unit, and controls two identical and parallel current acquisition units to monitor the output current of the electrical device in turn based on the state judgment index, thereby realizing dynamic management of the current acquisition unit. This dynamic management mechanism not only improves the accuracy and stability of current data acquisition, but also enables timely replacement of acquisition units that may have problems, effectively reducing monitoring errors and data loss problems caused by acquisition unit failures, thereby improving data reliability and reducing the false alarm rate of faults.

Description

Technical Field

[0001] This invention relates to the field of fault current identification technology, and specifically to a leakage current essence solution system based on accurate fault current identification. Background Technology

[0002] In the field of electrical equipment operation monitoring, the accurate and stable collection of electrical equipment operation data and the timely and accurate determination of whether electrical equipment has leakage faults are of vital importance to ensuring the safe operation of electrical equipment and preventing electrical accidents.

[0003] Currently, leakage faults in electrical equipment are typically detected by real-time data acquisition units (such as current sensors) and temperature sensors. By analyzing the changes in current and temperature, the operating status of the electrical equipment is determined to be abnormal. If an abnormality is found, the equipment is inspected to identify the type of leakage fault.

[0004] However, electrical equipment often operates for extended periods, even 24 hours a day. If a current sensor operates continuously, it generates significant heat. Current sensors typically contain resistive elements, and according to the physical characteristics of resistance, its value changes with temperature. When a current sensor generates high heat during prolonged operation, its internal temperature rises, causing a corresponding change in resistance. This results in a lower measured current value, reducing the accuracy of the current measurement and ultimately affecting the assessment of the electrical equipment's operating status. Furthermore, when electrical equipment malfunctions, it is usually shut down for staff to inspect it one by one. Less experienced staff often spend considerable time troubleshooting, wasting significant time and causing substantial economic losses for the company. Summary of the Invention

[0005] The purpose of this invention is to provide a leakage current essence solution system based on accurate fault current identification, thereby solving the above-mentioned technical problems.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A leakage current identification-based system for resolving electrical equipment leakage current issues, applicable to electrical equipment, comprising:

[0008] Thermal infrared image acquisition module, used to acquire thermal infrared image data of electrical equipment;

[0009] The current monitoring module includes two identical and parallel current acquisition units, which are used to monitor the output current of electrical equipment in turn and collect current information data of electrical equipment.

[0010] The temperature acquisition module includes two temperature sensors, which correspond one-to-one with the current acquisition unit and are used to acquire temperature information data from the current acquisition unit.

[0011] The current acquisition unit control module is used to analyze the current and temperature information data of the connected electrical equipment, obtain the status judgment index of the current acquisition unit, and determine whether it is necessary to switch the current acquisition unit to the electrical equipment based on the status judgment index.

[0012] The historical leakage fault information storage module is used to store historical leakage fault information data.

[0013] The analysis module is used to analyze historical leakage current information data, current information data within a preset time period past the current time, and thermal infrared image data to determine the leakage current fault type of electrical equipment.

[0014] As a further aspect of the present invention: the process of obtaining the state judgment index includes:

[0015] S1; Obtain the temperature change curve of the current acquisition unit of the connected electrical equipment over time;

[0016] S2: Analyze the temperature change curve of the current acquisition unit of the connected electrical equipment over time to obtain the temperature change curve per unit time over time.

[0017] S3: Based on the temperature change curve of the current acquisition unit of the connected electrical equipment over time and the change curve of the temperature change per unit time over time, analyze the temperature abnormality index of the current acquisition unit of the connected electrical equipment.

[0018] S4: Based on the temperature anomaly index and the current working duration of the current acquisition unit of the connected electrical equipment, the current status judgment index of the current acquisition unit of the connected electrical equipment at the current moment is obtained through analysis.

[0019] As a further aspect of the present invention: In step S3, the formula is used:

[0020] ;

[0021] Calculate the temperature anomaly index of the current acquisition unit of the connected electrical equipment at the current moment. ;

[0022] in, As the first judgment function, when hour, ;when hour, ; For current acquisition units connected to electrical equipment; The temperature change per unit time of the current acquisition unit connected to the electrical equipment at the current moment; Set a preset temperature change adjustment coefficient for the current moment; Preset the temperature change value per unit time; The current temperature value of the current acquisition unit connected to the electrical equipment; Preset temperature values ​​for the current acquisition units connected to electrical equipment; The temperature change curve of the current acquisition unit connected to the electrical equipment over time; Preset duration; This is the cumulative value of the preset temperature within a preset time period; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant; This is the third preset constant.

[0023] As a further aspect of the present invention: through the formula:

[0024] ;

[0025] Calculate the judgment index of the current acquisition unit of the connected electrical equipment at the current moment. ;

[0026] in, For the second judgment function, when hour, ;when hour, ; Preset temperature anomaly index; The duration of operation of the current acquisition unit connected to the electrical equipment during this connection; This refers to the service life (in years) of the current acquisition unit. The actual number of years of use of the current acquisition unit connected to the electrical equipment; Preset the duration of a single work session; This is the first adjustment factor.

[0027] As a further aspect of the present invention: the process of whether or not it is necessary to switch the current acquisition unit connected to the electrical equipment is as follows:

[0028] when At this time, there is no need to switch the current acquisition unit connected to the electrical equipment;

[0029] Otherwise, it is necessary to switch the current acquisition unit connected to the electrical equipment.

[0030] As a further aspect of the present invention: a preset temperature change adjustment coefficient is used at the current moment. The process of obtaining it is as follows:

[0031] S10: Before formal commissioning, obtain the preset temperature change curve of the current acquisition unit as a function of working time;

[0032] S20: Analyze the preset temperature change curve of the current acquisition unit with the working time to obtain the preset temperature change curve per unit time with time.

[0033] S30: Based on the preset curves of the current temperature, the temperature change per unit time over time, and the temperature change of the current acquisition unit over the working time, analyze the preset temperature change value adjustment coefficient at the current moment. .

[0034] As a further aspect of the present invention: through the formula:

[0035] ;

[0036] Calculate the adjustment coefficient for the preset temperature change value at the current moment. ;

[0037] in, The first working duration from the current acquisition unit of the connected electrical equipment to the current time. The temperature change value per unit time is preset for the first working duration of the current acquisition unit; The preset temperature value corresponding to the first working time of the current acquisition unit; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant.

[0038] As a further aspect of the present invention: the process for determining the leakage fault type of electrical equipment is as follows:

[0039] S100: Classify historical leakage current information data according to leakage current fault type;

[0040] S200: Acquire the current change curve over time and thermal infrared image data of the location of the leakage fault within the first specified time period past the fault warning time for each type of leakage fault.

[0041] S300: The trained convolutional neural network model extracts features from the current-time curves of each leakage fault type and the thermal infrared image data of the leakage fault location to obtain the temperature change features and current change features of each leakage fault type.

[0042] S400: By analyzing the current information data at the current time and the current change characteristics of each leakage fault type, the current feature similarity is obtained, and the leakage fault type with the current feature similarity higher than the preset similarity is set as the reference leakage fault.

[0043] S500: By analyzing thermal infrared image data, multiple feature locations are obtained. The trained convolutional neural network model is used to analyze the thermal infrared image data of each feature location and the temperature change characteristics of the reference leakage fault in turn to obtain the similarity between the temperature characteristics of each feature location and each reference leakage fault.

[0044] S600: Determine whether there is a fault at each feature location and the corresponding leakage fault type based on the similarity of temperature characteristics.

[0045] The beneficial effects of this invention are:

[0046] (1) The present invention analyzes the current information data and temperature information data of the connected electrical equipment through the current acquisition unit control module to obtain the status judgment index of the current acquisition unit, and controls two identical and parallel current acquisition units to monitor the output current of the electrical equipment in turn according to the status judgment index, thereby realizing the dynamic management of the current acquisition unit. This dynamic management mechanism not only improves the accuracy and stability of current data acquisition, but also replaces the acquisition unit that may have problems in time, effectively reducing the monitoring error and data loss caused by acquisition unit failure, thereby improving the reliability of data and reducing the false alarm rate of fault. The analysis module establishes the feature model corresponding to different leakage fault types based on the historical leakage information data stored in the historical leakage fault information storage module, and then compares and matches the current information data and thermal infrared image data within the past preset time period with these feature models to determine whether the electrical equipment has a leakage fault and the type of leakage fault.

[0047] (2) The analysis module of this invention establishes feature models corresponding to different leakage fault types based on the historical leakage fault information data stored in the historical leakage fault information storage module. Then, it compares and matches the current information data and thermal infrared image data within a preset time period past the current time with these feature models to determine whether the electrical equipment has a leakage fault and the type of leakage fault. This allows less experienced staff to directly carry out repairs based on the determined fault type, avoiding a lot of wasted time and reducing economic losses to the enterprise. Attached Figure Description

[0048] The invention will now be further described with reference to the accompanying drawings.

[0049] Figure 1 This is a system module framework diagram of one embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] See also Figure 1 As shown, in one embodiment, a leakage current essence solution system based on accurate fault current identification is provided, applicable to electrical equipment, the system comprising:

[0052] Thermal infrared image acquisition module, used to acquire thermal infrared image data of electrical equipment;

[0053] The current monitoring module includes two identical and parallel current acquisition units, which are used to monitor the output current of electrical equipment in turn and collect current information data of electrical equipment.

[0054] The temperature acquisition module includes two temperature sensors, which correspond one-to-one with the current acquisition unit and are used to acquire temperature information data from the current acquisition unit.

[0055] The current acquisition unit control module is used to analyze the current and temperature information data of the connected electrical equipment, obtain the status judgment index of the current acquisition unit, and determine whether it is necessary to switch the current acquisition unit to the electrical equipment based on the status judgment index.

[0056] The historical leakage fault information storage module is used to store historical leakage fault information data.

[0057] The analysis module is used to analyze historical leakage current information data, current information data within a preset time period past the current time, and thermal infrared image data to determine the leakage current fault type of electrical equipment.

[0058] Through the above technical solution, this embodiment acquires thermal infrared image data of electrical equipment through a thermal infrared image acquisition module; then, two identical and parallel current acquisition units alternately monitor the output current of the electrical equipment to acquire current information data; next, a temperature sensor acquires temperature information data of the corresponding current acquisition unit; the current acquisition unit control module analyzes the current and temperature information data of the connected electrical equipment to obtain a status judgment index for the current acquisition unit, and determines whether to switch the current acquisition unit connected to the electrical equipment based on the status judgment index; the analysis module analyzes the historical leakage fault information data, current information data within a preset time period, and thermal infrared image data stored in the historical leakage fault information storage module to determine whether the electrical equipment has a leakage fault; this not only improves the accuracy and stability of current data acquisition, but also allows the current acquisition unit control module to analyze the current and temperature information data of the connected electrical equipment... The system analyzes and obtains the status judgment index of the current acquisition unit. Based on the status judgment index, it controls two identical and parallel current acquisition units to monitor the output current of electrical equipment in turn, realizing dynamic management of the current acquisition units. This dynamic management mechanism not only improves the accuracy and stability of current data acquisition, but also allows for timely replacement of acquisition units that may have problems, effectively reducing monitoring errors and data loss caused by acquisition unit failures, thereby improving data reliability and reducing the false alarm rate. The analysis module establishes feature models corresponding to different leakage fault types based on historical leakage fault information stored in the historical leakage fault information storage module. Then, it compares and matches the current information data and thermal infrared image data within a preset time period to determine whether the electrical equipment has a leakage fault and the type of leakage fault. This allows less experienced personnel to directly perform repairs based on the determined fault type, avoiding wasting a lot of time and reducing economic losses to the enterprise.

[0059] As one embodiment of the present invention, the process of obtaining the state judgment index includes:

[0060] S1; Obtain the temperature change curve of the current acquisition unit of the connected electrical equipment over time;

[0061] S2: Analyze the temperature change curve of the current acquisition unit of the connected electrical equipment over time to obtain the temperature change curve per unit time over time.

[0062] S3: Based on the temperature change curve of the current acquisition unit of the connected electrical equipment over time and the change curve of the temperature change per unit time over time, analyze the temperature abnormality index of the current acquisition unit of the connected electrical equipment.

[0063] S4: Based on the temperature anomaly index and the current working duration of the current acquisition unit of the connected electrical equipment, the current status judgment index of the current acquisition unit of the connected electrical equipment at the current moment is obtained through analysis.

[0064] Through the above technical solution, this embodiment obtains the temperature change curve of the current acquisition unit of the connected electrical equipment over time; then, based on the temperature change curve of the current acquisition unit of the connected electrical equipment over time, it analyzes the temperature change curve of the unit temperature over time to obtain the temperature change curve of the unit temperature over time; then, based on the temperature change curve of the current acquisition unit of the connected electrical equipment over time and the temperature change curve of the unit temperature over time, it analyzes the temperature abnormality index of the current acquisition unit of the connected electrical equipment to obtain the current status judgment index of the current acquisition unit of the connected electrical equipment at the current moment; this can more realistically reflect the working status of the current acquisition unit at the current moment, automatically switch the current acquisition unit of the connected electrical equipment, avoid data drift caused by the current acquisition unit working for a long time, indirectly improve the reliability of the collected electrical equipment status data, and also help extend the service life of the equipment and reduce the equipment replacement cost.

[0065] As one embodiment of the present invention, in step S3, the formula is:

[0066] ;

[0067] Calculate the temperature anomaly index of the current acquisition unit of the connected electrical equipment at the current moment. ;

[0068] in, As the first judgment function, when hour, ;when hour, ; For current acquisition units connected to electrical equipment; The temperature change per unit time of the current acquisition unit connected to the electrical equipment at the current moment; Set a preset temperature change adjustment coefficient for the current moment; Preset the temperature change value per unit time; The current temperature value of the current acquisition unit connected to the electrical equipment; Preset temperature values ​​for the current acquisition units connected to electrical equipment; The temperature change curve of the current acquisition unit connected to the electrical equipment over time; Preset duration; This is the cumulative value of the preset temperature within a preset time period; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant; This is the third preset constant;

[0069] Through the above technical solution, this embodiment The current acquisition unit of the connected electrical equipment is preset with a unit time temperature change value at the current moment; The difference between the current temperature change per unit time of the current acquisition unit connected to the electrical equipment and the preset temperature change per unit time at the current moment is calculated using the formula... In the first judgment function in It refers to This is used to determine whether the temperature change per unit time of the current acquisition unit of the connected electrical equipment exceeds the preset temperature change per unit time at the current moment. This indicates that the temperature change per unit time of the current acquisition unit connected to the electrical equipment exceeds the preset temperature change per unit time at the current moment. Therefore, there is a risk of abnormal temperature at the current acquisition unit, and the difference between the current acquisition unit's temperature change per unit time and the preset temperature change per unit time at the current moment is... The larger the current, the greater the risk of abnormal temperature fluctuations in the current acquisition unit. ;when If the temperature change per unit time of the current acquisition unit connected to the electrical equipment does not exceed the preset temperature change per unit time at the current moment, then there is no risk of abnormal temperature at the current acquisition unit. ; The difference between the current temperature value of the current acquisition unit of the connected electrical equipment and the preset temperature value of the current acquisition unit of the connected electrical equipment is expressed in the formula. In the first judgment function in It refers to This is used to determine whether the current temperature value of the current acquisition unit of the connected electrical equipment exceeds the preset temperature value of the current acquisition unit of the connected electrical equipment. If the temperature value of the current acquisition unit of the connected electrical equipment exceeds the preset temperature value, it indicates that there is an abnormal risk in the current acquisition unit. Furthermore, the difference between the current temperature value and the preset temperature value of the current acquisition unit of the connected electrical equipment is significant. The larger the value, the greater the risk of abnormalities when connecting to the current acquisition unit. ;when If the temperature reading of the current acquisition unit connected to the electrical equipment does not exceed the preset temperature value of the current acquisition unit, then there is no risk of abnormal temperature readings from the current acquisition unit. ; The current acquisition unit of the connected electrical equipment measures the cumulative temperature value over a preset time period from the current time. The difference between the cumulative temperature value within a preset time period and the preset cumulative temperature value within a preset time period is obtained from the current acquisition unit of the connected electrical equipment; in the formula In the first judgment function in It refers to This is used to determine whether the cumulative temperature value of the current acquisition unit of the connected electrical equipment within the past preset time exceeds the preset cumulative temperature value within the preset time. If the current acquisition unit of the connected electrical equipment shows a temperature reading that exceeds the preset temperature value within the same preset time period, it indicates an abnormal temperature risk. Furthermore, the difference between the current acquisition unit's temperature reading and the preset temperature value within the same preset time period is significant. The larger the current sensor size, the greater the risk of abnormal temperature fluctuations in the current acquisition unit. ;when If the current acquisition unit of the connected electrical equipment does not exceed the preset temperature cumulative value within the preset time period, then there is no risk of abnormal temperature at the connected current acquisition unit. By evaluating the temperature status of the current acquisition unit connected to the electrical equipment from three dimensions—temperature change per unit time, current temperature, and cumulative temperature over a preset time period—it is possible to gain a more comprehensive and accurate understanding of the temperature dynamics during operation.

[0070] It should be noted that the preset temperature change value per unit time The preset temperature value of the current acquisition unit connected to the electrical equipment Preset duration First weighting coefficient Second weighting coefficient Third weighting coefficient First preset constant Second preset constant and the third preset constant These are preset values, obtained based on experience, and will not be detailed here.

[0071] As one embodiment of the present invention, the formula is as follows:

[0072] ;

[0073] Calculate the judgment index of the current acquisition unit of the connected electrical equipment at the current moment. ;

[0074] in, For the second judgment function, when hour, ;when hour, ; Preset temperature anomaly index; The duration of operation of the current acquisition unit connected to the electrical equipment during this connection; This refers to the service life (in years) of the current acquisition unit. The actual number of years of use of the current acquisition unit connected to the electrical equipment; Preset the duration of a single work session; This is the first adjustment factor;

[0075] Through the above technical solution, this embodiment The difference between the current temperature anomaly index of the current acquisition unit connected to the electrical equipment and the preset temperature anomaly index is calculated using the formula... In the middle, the second judgment function In It refers to This is used to determine whether the temperature anomaly index of the current acquisition unit of the connected electrical equipment exceeds the preset temperature anomaly index at the current moment. When the current acquisition unit connected to the electrical equipment exceeds the preset temperature anomaly index, it indicates a significant risk of temperature anomalies. Therefore, it is necessary to switch to another current acquisition unit connected to the electrical equipment. If the temperature anomaly index of the current acquisition unit connected to the electrical equipment does not exceed the preset temperature anomaly index, then there is no risk of temperature anomaly in the current acquisition unit, and it is not necessary to switch the current acquisition unit. ; This is the ratio of the actual number of years the current acquisition unit is used to the service life of the current acquisition unit in the electrical equipment. The current acquisition unit of the connected electrical equipment is preset with a single working duration for its current status. This is the ratio of the actual number of years the current acquisition unit has been in use to its service life in years. The larger the value, the higher the aging degree of the current acquisition unit connected to the electrical equipment, and the closer it is to the critical point of expected scrapping or severe performance degradation. Therefore, by reducing the single working time of the current acquisition unit, the power-on time of the component can be reduced, the heat generation can be reduced, and the component parameter drift caused by long-term operation can be reduced. To a certain extent, the acquisition accuracy of the current acquisition unit can be maintained, ensuring that the acquired current data can accurately reflect the actual operating status of the electrical equipment. The difference between the current acquisition unit's current access duration and the current acquisition unit's current state during the current access to the electrical equipment is preset in the formula. In the middle, the second judgment function in It refers to This is used to determine whether the current acquisition unit of the connected electrical equipment has exceeded the current state preset single working time of the current acquisition unit of the connected electrical equipment. If the current acquisition unit connected to the electrical equipment operates for a duration exceeding the preset single-operation duration for its current state, it indicates a significant risk of malfunction. Therefore, it is necessary to switch to another current acquisition unit connected to the electrical equipment. ;when If the current acquisition unit connected to the electrical equipment has not exceeded its current preset single-cycle working time, then there is no risk of abnormal temperature from the connected current acquisition unit, and it is not necessary to switch the current acquisition unit. ;

[0076] It should be noted that the preset temperature anomaly index Service life (in years) of the current acquisition unit Preset single work duration and the first adjustment factor These are preset values, obtained based on experience, and will not be detailed here.

[0077] As one embodiment of the present invention, the process of determining whether it is necessary to switch the current acquisition unit connected to the electrical equipment is as follows:

[0078] when At this time, there is no need to switch the current acquisition unit connected to the electrical equipment;

[0079] Otherwise, it is necessary to switch the current acquisition unit connected to the electrical equipment;

[0080] Through the above technical solution, in this embodiment when When, explain and This indicates that the temperature anomaly index of the current acquisition unit connected to the electrical equipment at the current moment has not exceeded the preset temperature anomaly index, and the current acquisition unit's current working time has not exceeded the current state preset single working time of the current acquisition unit connected to the electrical equipment. Therefore, there is no need to switch the current acquisition unit connected to the electrical equipment; when If the current acquisition unit connected to the electrical equipment is abnormal, it indicates that at least one of the current status and operating time of the current acquisition unit is abnormal at the current moment, so it is necessary to switch the current acquisition unit connected to the electrical equipment.

[0081] As one embodiment of the present invention, a preset temperature change value adjustment coefficient is used at the current moment. The process of obtaining it is as follows:

[0082] S10: Before formal commissioning, obtain the preset temperature change curve of the current acquisition unit as a function of working time;

[0083] S20: Analyze the preset temperature change curve of the current acquisition unit with the working time to obtain the preset temperature change curve per unit time with time.

[0084] S30: Based on the preset curves of the current temperature, the temperature change per unit time over time, and the temperature change of the current acquisition unit over the working time, analyze the preset temperature change value adjustment coefficient at the current moment. ;

[0085] As one embodiment of the present invention, the formula is as follows:

[0086] ;

[0087] Calculate the adjustment coefficient for the preset temperature change value at the current moment. ;

[0088] in, The first working duration from the current acquisition unit of the connected electrical equipment to the current time. The temperature change value per unit time is preset for the first working duration of the current acquisition unit; The preset temperature value corresponding to the first working time of the current acquisition unit; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant;

[0089] Through the above technical solution, this embodiment This is the ratio of the preset temperature change value per unit time to the preset temperature change value per unit time for the first working period of the current acquisition unit. The larger the ratio, the larger the adjustment coefficient of the preset temperature change value at the current moment. The difference between the preset temperature value of the current acquisition unit corresponding to the first working time and the current temperature value of the current acquisition unit connected to the electrical equipment at the current time; when When this occurs, it indicates that the ratio of the preset temperature change per unit time corresponding to the first working time of the current acquisition unit to the preset temperature change per unit time is greater than the value of the preset temperature change per unit time. Therefore, the adjustment coefficient can be increased, and can be as close as 1. When the current acquisition unit corresponds to the first working time, the preset temperature change value per unit time is less than the preset temperature change value per unit time. Therefore, the adjustment coefficient can be reduced, and can be as close to 0 as possible.

[0090] It should be noted that the preset temperature change value per unit time corresponding to the first working time of the current acquisition unit is obtained based on the preset change curve of the temperature change per unit time over time; the preset temperature value of the current acquisition unit corresponding to the first working time is obtained based on the preset change curve of the temperature of the current acquisition unit over the working time. The specific acquisition process is existing technology and will not be described in detail here.

[0091] It should be noted that the first weight coefficient For, the second weighting coefficient Preset constant No. 1 and the second preset constant These are preset values, obtained based on experience, and will not be detailed here.

[0092] As one embodiment of the present invention, the historical leakage information data includes leakage fault type, leakage fault location, current information data within a first specified time period after the fault warning time, and thermal infrared image data of the leakage fault location.

[0093] As one embodiment of the present invention, the process for determining the leakage fault type of electrical equipment is as follows:

[0094] S100: Classify historical leakage current information data according to leakage current fault type;

[0095] S200: Acquire the current change curve over time and thermal infrared image data of the location of the leakage fault within the first specified time period past the fault warning time for each type of leakage fault.

[0096] S300: The trained convolutional neural network model extracts features from the current-time curves of each leakage fault type and the thermal infrared image data of the leakage fault location to obtain the temperature change features and current change features of each leakage fault type.

[0097] S400: By analyzing the current information data at the current time and the current change characteristics of each leakage fault type, the current feature similarity is obtained, and the leakage fault type with the current feature similarity higher than the preset similarity is set as the reference leakage fault.

[0098] S500: By analyzing thermal infrared image data, multiple feature locations are obtained. The trained convolutional neural network model is used to analyze the thermal infrared image data of each feature location and the temperature change characteristics of the reference leakage fault in turn to obtain the similarity between the temperature characteristics of each feature location and each reference leakage fault.

[0099] S600: Determines whether there is a fault at each feature location and the corresponding leakage fault type based on the similarity of temperature characteristics;

[0100] Through the above technical solution, this embodiment classifies historical leakage current information data according to leakage fault type; then, it acquires the current-time variation curve and thermal infrared image data of the leakage fault location within a first specified time period past the fault warning time for each leakage fault type; next, it uses a trained convolutional neural network model to extract features from the current-time variation curve and thermal infrared image data of the leakage fault location for each leakage fault type, obtaining the temperature change features and current change features for each leakage fault type; finally, it analyzes the current information data at the current time with the current change features of each leakage fault type to obtain the current feature similarity. Leakage fault types with current feature similarity higher than a preset similarity are designated as reference leakage faults. Finally, by analyzing thermal infrared image data, multiple feature locations are obtained. A trained convolutional neural network model is then used to analyze the temperature change characteristics of the thermal infrared image data and the reference leakage faults at each feature location, obtaining the temperature feature similarity between each feature location and each reference leakage fault. Next, based on the temperature feature similarity, it is determined whether a fault exists at each feature location and the corresponding leakage fault type. Finally, the actual maintenance and testing results are fed back into the system to optimize the convolutional neural network model and adjust parameters such as the similarity threshold, continuously improving the system's performance.

[0101] It should be noted that the selection rule for the feature location can be that the temperature difference between the location and the temperature outside the preset range exceeds a preset temperature value; the preset range can be a circular area centered on the location, and the radius of the circle can be preset based on experience, which will not be detailed here.

[0102] It should be noted that the first specified duration is a preset value. Through experimental research and analysis on different types of leakage faults, it was found that this duration can fully reflect the changes in current and temperature before the fault occurs. The preset similarity is a preset value. The training process of the convolutional neural network model is based on existing technology and obtained through experience, and will not be described in detail here.

[0103] It should be noted that the process of obtaining temperature feature similarity and current feature similarity is existing technology and will not be described in detail here.

[0104] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A leakage current fundamental solution system based on accurate fault current identification, applicable to electrical equipment, characterized in that, The system includes: Thermal infrared image acquisition module, used to acquire thermal infrared image data of electrical equipment; The current monitoring module includes two identical and parallel current acquisition units, which are used to monitor the output current of electrical equipment in turn and collect current information data of electrical equipment. The temperature acquisition module includes two temperature sensors, which correspond one-to-one with the current acquisition unit and are used to acquire temperature information data from the current acquisition unit. The current acquisition unit control module is used to analyze the current and temperature information data of the connected electrical equipment, obtain the status judgment index of the current acquisition unit, and determine whether it is necessary to switch the current acquisition unit to the electrical equipment based on the status judgment index. The historical leakage fault information storage module is used to store historical leakage fault information data. The analysis module is used to analyze historical leakage current information data, current information data within a preset time period past the current time, and thermal infrared image data to determine the leakage current fault type of electrical equipment. The process of obtaining the state judgment index includes: S1; Obtain the temperature change curve of the current acquisition unit of the connected electrical equipment over time; S2: Analyze the temperature change curve of the current acquisition unit of the connected electrical equipment over time to obtain the temperature change curve per unit time over time. S3: Based on the temperature change curve of the current acquisition unit of the connected electrical equipment over time and the change curve of the temperature change per unit time over time, analyze the temperature abnormality index of the current acquisition unit of the connected electrical equipment. S4: Based on the temperature anomaly index and the current working duration of the current acquisition unit of the connected electrical equipment, the current status judgment index of the current acquisition unit of the connected electrical equipment at the current moment is obtained through analysis.

2. The leakage current essence solution system based on accurate fault current identification according to claim 1, characterized in that, In step S3, using the formula: ； Calculate the temperature anomaly index of the current acquisition unit of the connected electrical equipment at the current moment. ; in, As the first judgment function, when hour, ;when hour, ; For current acquisition units connected to electrical equipment; The temperature change per unit time of the current acquisition unit connected to the electrical equipment at the current moment; Set a preset temperature change adjustment coefficient for the current moment; Preset the temperature change value per unit time; The current temperature value of the current acquisition unit connected to the electrical equipment; Preset temperature values ​​for the current acquisition units connected to electrical equipment; The temperature change curve of the current acquisition unit connected to the electrical equipment over time; The current time; Preset duration; This is the cumulative value of the preset temperature within a preset time period; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant; This is the third preset constant.

3. The leakage current essence solution system based on accurate fault current identification according to claim 2, characterized in that, Through the formula: ； Calculate the judgment index of the current acquisition unit of the connected electrical equipment at the current moment. ; in, For the second judgment function, when hour, ;when hour, ; Preset temperature anomaly index; The duration of operation of the current acquisition unit connected to the electrical equipment during this connection; This refers to the service life (in years) of the current acquisition unit. The actual number of years of use of the current acquisition unit connected to the electrical equipment; Preset the duration of a single work session; This is the first adjustment factor.

4. The leakage current essence solution system based on accurate fault current identification according to claim 3, characterized in that, The process for determining whether to switch the current acquisition unit connected to the electrical equipment is as follows: when At this time, there is no need to switch the current acquisition unit connected to the electrical equipment; Otherwise, it is necessary to switch the current acquisition unit connected to the electrical equipment.

5. The leakage current essence solution system based on accurate fault current identification according to claim 4, characterized in that, Current time preset temperature change value adjustment coefficient The process of obtaining it is as follows: S10: Before formal commissioning, obtain the preset temperature change curve of the current acquisition unit as a function of working time; S20: Analyze the preset temperature change curve of the current acquisition unit with the working time to obtain the preset temperature change curve per unit time with time. S30: Based on the preset curves of the current temperature, the temperature change per unit time over time, and the temperature change of the current acquisition unit over the working time, analyze the preset temperature change value adjustment coefficient at the current moment. .

6. The leakage current essence solution system based on accurate fault current identification according to claim 5, characterized in that, Through the formula: ； Calculate the adjustment coefficient for the preset temperature change value at the current moment. ; in, The first working duration from the current acquisition unit of the connected electrical equipment to the current time. The temperature change value per unit time is preset for the first working duration of the current acquisition unit; The preset temperature value corresponding to the first working time of the current acquisition unit; This is the first weighting coefficient; This is the second weighting coefficient; This is the third weighting coefficient; This is the first preset constant; This is the second preset constant.

7. The leakage current essence solution system based on accurate fault current identification according to claim 6, characterized in that, The process for determining the type of leakage fault in electrical equipment is as follows: S100: Classify historical leakage current information data according to leakage current fault type; S200: Acquire the current change curve over time and thermal infrared image data of the location of the leakage fault within the first specified time period past the fault warning time for each type of leakage fault. S300: The trained convolutional neural network model extracts features from the current-time curves of each leakage fault type and the thermal infrared image data of the leakage fault location to obtain the temperature change features and current change features of each leakage fault type. S400: By analyzing the current information data at the current time and the current change characteristics of each leakage fault type, the current feature similarity is obtained, and the leakage fault type with the current feature similarity higher than the preset similarity is set as the reference leakage fault. S500: By analyzing thermal infrared image data, multiple feature locations are obtained. The trained convolutional neural network model is used to analyze the thermal infrared image data of each feature location and the temperature change characteristics of the reference leakage fault in turn to obtain the similarity between the temperature characteristics of each feature location and each reference leakage fault. S600: Determine whether there is a fault at each feature location and the corresponding leakage fault type based on the similarity of temperature characteristics.

Images