Intelligent operation and maintenance management system for transformer substation relay protection pressing plate

Abstract

The invention relates to the technical field of data processing, in particular to an intelligent operation and maintenance management system for a relay protection pressing plate of a transformer substation, and the system comprises a data collection module which is used for collecting the operation state data of the relay protection pressing plate of the transformer substation; the data processing module is used for preprocessing the running state data and extracting state features; the state evaluation module is used for training the initial model to obtain an intelligent evaluation model, evaluating the running state of the relay protection pressing plate and outputting a result; the filtering adjustment module is used for determining a multi-dimensional feature distinguishing filtering coefficient according to the state feature matching accuracy of the protection pressing plate; the identifier adjusting module is used for determining a key state identifier weight according to a fluctuation value of running state data transmission in unit time; and the compensation adjustment module is used for determining the dynamic compensation gain of the running state data quality according to the reference drift error rate of the state characteristics in the single period. The operation and maintenance management stability of the relay protection pressing plate is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an intelligent operation and maintenance management system for substation relay protection circuit boards. Background Technology

[0002] In current technologies, with the deepening of smart grid construction, the level of intelligent operation and maintenance of substations has become an important indicator for measuring the modernization of the power grid. Traditional operation and maintenance management of relay protection circuit boards mainly relies on manual inspection and operation, which has the following technical shortcomings: In terms of condition monitoring, existing technologies mainly rely on regular manual inspections, visually checking the position of the circuit boards. This method is inefficient and prone to missed detections and misjudgments. Although some existing digital solutions have achieved automatic acquisition of circuit board status, the strong electromagnetic interference environment within substations generally results in a large amount of noise in the acquired signals, seriously affecting the accuracy of condition feature extraction. Existing condition assessment methods are mostly based on simple threshold judgments or static rule bases, lacking self-learning and adaptive capabilities, leading to insufficient stability in the operation and maintenance management of relay protection circuit boards.

[0003] Chinese Patent Publication No. CN108448539A discloses an active anti-malfunction method for relay protection in intelligent substations. The method includes the following steps: performing relay protection device status diagnosis to determine whether the relay protection device is in a normal state; when the relay protection device is in an abnormal state, determining whether the status rules corresponding to the relay protection device's pressure plate status, related device status, and primary equipment operating status match the normal state, thereby identifying the abnormal pressure plate; performing an operation rehearsal for the abnormal pressure plate, and issuing a corresponding operation command after a successful rehearsal; executing the operation command to bring the relay protection device back to a normal state. Therefore, this active anti-malfunction method for relay protection in intelligent substations suffers from problems such as relying on raw status data for anomaly judgment, the complexity of the substation environment leading to high-frequency interference, data transmission distortion and fluctuation, and high noise levels, resulting in insufficient stability in the operation and maintenance management of the relay protection pressure plate. Summary of the Invention

[0004] Therefore, this invention provides an intelligent operation and maintenance management system for substation relay protection circuit boards, which overcomes the problems in the prior art where the original state data is used as the basis for anomaly judgment, the substation environment is complex and prone to high-frequency interference, and the data transmission is prone to distortion and fluctuation with a lot of noise, resulting in insufficient stability of the operation and maintenance management of relay protection circuit boards.

[0005] To achieve the above objectives, the present invention provides an intelligent operation and maintenance management system for substation relay protection circuit boards, comprising:

[0006] The data acquisition module is used to collect the operating status data of substations equipped with relay protection pressure plates;

[0007] The data processing module, which is connected to the data acquisition module, includes a preprocessing unit for preprocessing the running status data to output standardized status data and a feature extraction unit connected to the preprocessing unit for extracting features from the standardized status data to output status features.

[0008] The status assessment module, which is connected to the data processing module, includes a model training unit for training an initial model based on the status characteristics to obtain an intelligent assessment model, and an assessment unit connected to the model training unit for assessing the operating status of the relay protection pressure plate based on the intelligent assessment model to obtain an assessment result.

[0009] A filtering adjustment module, which is connected to the data processing module, is used to determine the multi-dimensional feature differentiation filtering coefficients based on the matching accuracy of state features.

[0010] The identifier adjustment module is connected to the data acquisition module and the filter adjustment module respectively, and is used to determine the key status identifier weight based on the fluctuation value of the running status data transmission per unit time.

[0011] The compensation adjustment module is connected to the data processing module and the identification adjustment module respectively, and is used to determine the dynamic compensation gain of the running status data quality based on the reference drift error rate of the state characteristics within a single cycle.

[0012] Furthermore, if the accuracy of the matching of the protection pressure plate state characteristics is less than the preset second accuracy rate, the filtering adjustment module determines that the stability of the operation and maintenance management of the relay protection pressure plate does not meet the requirements.

[0013] Furthermore, in response to the fact that the accuracy of the matching of the protection pressure plate status features is greater than the preset first accuracy and less than the preset second accuracy, the filtering adjustment module initially determines that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements, and determines whether the real-time performance of the protection pressure plate status data acquisition meets the requirements based on the fluctuation value of the data transmission of the operating status data per unit time.

[0014] Furthermore, the filtering adjustment module increases the multi-dimensional feature differentiation filtering coefficient in response to the protection pressure plate state feature matching accuracy being less than or equal to the preset first accuracy.

[0015] The increase in the multi-dimensional feature discrimination filtering coefficient is determined by the difference between the preset first accuracy rate and the protection pressure plate state feature matching accuracy rate.

[0016] Furthermore, the identification adjustment module responds to the fluctuation value of the operating status data transmission per unit time being greater than the preset first fluctuation value, and determines that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements.

[0017] Furthermore, the identifier adjustment module increases the weight of the key status identifier in response to the fluctuation value of the running status data transmission within the unit time being greater than the preset first fluctuation value and less than the preset second fluctuation value.

[0018] Furthermore, in response to the fluctuation value of the operating status data transmission within the unit time being greater than or equal to the preset second fluctuation value, the identification adjustment module initially determines that the consistency of the protection pressure plate status data does not meet the requirements, and determines whether the consistency of the protection pressure plate status data meets the requirements based on the reference drift error rate of the status characteristics within a single cycle.

[0019] Furthermore, the increase in the weight of the key status identifier is determined by the difference between the fluctuation value of the running status data transmission per unit time and the preset first fluctuation value.

[0020] Furthermore, the compensation adjustment module responds to the fact that the reference drift error rate of the state characteristics within a single cycle is greater than the preset error rate, determines that the consistency of the protection pressure plate state data does not meet the requirements, and increases the dynamic compensation gain for the operating state data quality.

[0021] Furthermore, the increase in the dynamic compensation gain for the operational status data quality is determined by the difference between the reference drift error rate of the status characteristics within a single cycle and the preset error rate.

[0022] Compared with existing technologies, the beneficial effects of this invention are as follows: The system of this invention, by setting up a data acquisition module, a data processing module, a state assessment module, a filtering adjustment module, an identification adjustment module, and a compensation adjustment module, adjusts the multi-dimensional feature differentiation filtering coefficients according to the accuracy of the protection pressure plate state feature matching. Since substations are located in outdoor or semi-outdoor environments, composite pollution layers cover the identification and state feature areas of the pressure plates, leading to noise interference during feature extraction. By adjusting the multi-dimensional feature differentiation filtering coefficients, the extraction capabilities of the grayscale features, edge contour features, and identification texture features of the pressure plates at different scales can be simultaneously assessed, effectively separating pollution noise from real state features and improving feature extraction accuracy. Furthermore, the weight of key state identifications is adjusted based on the fluctuation value of the operating state data transmission per unit time. Because the operation of relay protection devices and high-voltage equipment generates high-frequency electromagnetic radiation, which superimposes with the state data transmission signal, it leads to… To mitigate signal amplitude fluctuations and transmission delays, the system prioritizes parsing and transmitting key status identifiers when data transmission fluctuates. This reduces the bandwidth consumption of non-critical data. Simultaneously, a weighted algorithm reduces the impact of fluctuating signals on the parsing results of key identifiers, ensuring real-time transmission of core status information and avoiding recognition lag caused by transmission delays. Furthermore, the system dynamically adjusts the gain for compensating for operational status data quality based on the baseline drift error rate of status characteristics within a single cycle. Fluctuations in temperature and humidity within the substation, equipment vibration causing sensor installation position shifts, and aging of electronic components leading to baseline drift in signal acquisition result in systematic deviations in the status data of the same relay protection plate collected by different sensors. Adjusting the gain for dynamic compensation of operational status data enhances the compensation for high-quality data, weakens the impact of drift data on status judgment, and improves the stability of relay protection plate operation and maintenance management.

[0023] Furthermore, the system of the present invention adjusts the multi-dimensional feature discrimination filtering coefficient by setting a preset first accuracy rate and a preset second accuracy rate. Since the substation is in an outdoor or semi-outdoor environment, the composite pollution layer covers the marking and status feature areas of the pressure plate, resulting in noise interference during feature extraction. By adjusting the multi-dimensional feature discrimination filtering coefficient, the extraction capability of grayscale features, edge contour features and marking texture features of the pressure plate at different scales can be simultaneously applied, effectively separating pollution noise from real status features, improving feature extraction accuracy, and further improving the stability of operation and maintenance management of relay protection pressure plates.

[0024] Furthermore, the system of the present invention adjusts the weight of key status identifiers by setting preset first fluctuation values ​​and preset second fluctuation values. Since the operation of relay protection devices and high-voltage equipment generates high-frequency electromagnetic radiation, which is superimposed on the status data transmission signal, it causes signal amplitude fluctuations and transmission delays. By adjusting the weight of key status identifiers, the system will prioritize parsing and transmitting key identifier information when data transmission fluctuates, reducing the occupation of transmission bandwidth by non-critical data. At the same time, the weighted algorithm reduces the impact of fluctuation signals on the key identifier parsing results, ensuring the real-time transmission of core status information and avoiding recognition lag problems caused by transmission delays, thereby further improving the stability of operation and maintenance management of relay protection pressure plates.

[0025] Furthermore, the system described in this invention adjusts the dynamic compensation gain for the quality of operating status data by setting a preset error rate. Due to temperature and humidity fluctuations and equipment vibrations in the substation causing sensor installation position shifts, and aging of electronic components causing signal acquisition reference drift, systematic deviations occur in the status data of the same pressure plate collected by different sensors. By adjusting the dynamic compensation gain for the quality of operating status data, the compensation for high-quality data can be enhanced, the impact of drift data on status judgment can be weakened, and the stability of operation and maintenance management of relay protection pressure plates can be further improved. Attached Figure Description

[0026] Figure 1 This is an overall structural block diagram of the intelligent operation and maintenance management system for substation relay protection pressure plates according to an embodiment of the present invention;

[0027] Figure 2 This is a flowchart illustrating the logic of determining the multi-dimensional feature differentiation filtering coefficients for an intelligent operation and maintenance management system for substation relay protection pressure plates, as described in an embodiment of the present invention.

[0028] Figure 3 This is a flowchart illustrating the determination of key status identifier weights in an intelligent operation and maintenance management system for substation relay protection circuit boards according to an embodiment of the present invention.

[0029] Figure 4 This is a flowchart illustrating the dynamic compensation gain for determining the operating status data quality of an intelligent operation and maintenance management system for substation relay protection circuit boards, as described in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0031] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0032] Please see Figure 1 As shown, it is an overall structural block diagram of the intelligent operation and maintenance management system for substation relay protection pressure plates according to an embodiment of the present invention.

[0033] This invention provides an intelligent operation and maintenance management system for substation relay protection circuit boards, comprising:

[0034] The data acquisition module is used to collect the operating status data of substations equipped with relay protection pressure plates;

[0035] The data processing module, which is connected to the data acquisition module, includes a preprocessing unit for preprocessing the running status data to output standardized status data and a feature extraction unit connected to the preprocessing unit for extracting features from the standardized status data to output status features.

[0036] The status assessment module, which is connected to the data processing module, includes a model training unit for training an initial model based on the status characteristics to obtain an intelligent assessment model, and an assessment unit connected to the model training unit for assessing the operating status of the relay protection pressure plate based on the intelligent assessment model to obtain an assessment result.

[0037] A filtering adjustment module, which is connected to the data processing module, is used to determine the multi-dimensional feature differentiation filtering coefficients based on the matching accuracy of the protection pressure plate state characteristics.

[0038] The identifier adjustment module is connected to the data acquisition module and the filter adjustment module respectively, and is used to determine the key status identifier weight based on the fluctuation value of the running status data transmission per unit time.

[0039] The compensation adjustment module is connected to the data processing module and the identification adjustment module respectively, and is used to determine the dynamic compensation gain of the running status data quality based on the reference drift error rate of the state characteristics within a single cycle.

[0040] Specifically, the operational status data includes high-frequency electromagnetic radiation intensity, real-time temperature inside the protection cabinet, and power supply ripple voltage.

[0041] Specifically, preprocessing includes data denoising, data completion, and data standardization.

[0042] Specifically, the standardized status data includes the high-frequency electromagnetic radiation intensity after data noise reduction, the real-time temperature inside the protection cabinet after data completion, and the power supply ripple voltage after data standardization.

[0043] Specifically, the state characteristics include the variance of high-frequency electromagnetic radiation intensity fluctuation, the slope of temperature change inside the cabinet, and the power supply ripple voltage fluctuation coefficient.

[0044] Specifically, the initial model is an initial algorithm framework with basic time-series feature learning capabilities and designed specifically for the relay protection pressure plate state classification task.

[0045] Specifically, the intelligent evaluation model includes the support vector machine model, the isolation forest model, and the long short-term memory network model, with the preferred embodiment being the long short-term memory network model.

[0046] Specifically, the process of training the initial model based on state characteristics to obtain the intelligent evaluation model involves dividing the state characteristics into a training set, a validation set, and a test set. The initial model is trained using the training set to learn the inherent laws of the relay protection pressure plate's operating state. The parameters are optimized and adjusted using the validation set. Finally, the quality of the generated model is evaluated using the test set to obtain the intelligent evaluation model.

[0047] Specifically, the evaluation results include normal closing status, abnormal electrical signal amplitude distortion, and data transmission real-time performance meeting the standards.

[0048] Specifically, the process of evaluating the operating status of the relay protection pressure plate according to the intelligent evaluation model to obtain the evaluation result involves matching multi-dimensional status characteristics with a standard feature library, combining data quality verification, determining the switching status and anomaly type, classifying risk levels, generating operation and maintenance suggestions, and forming the evaluation result.

[0049] Specifically, the matching accuracy of state features is the ratio of the number of correctly matched state features to the total number of matched state features.

[0050] Specifically, a correct match is defined as a state feature that perfectly matches the preset standard state feature without any deviation.

[0051] Specifically, the multi-dimensional feature discrimination filter coefficient is the core indicator for quantifying the ability to effectively extract features from multi-dimensional state features and filter interference signals.

[0052] Specifically, the fluctuation value of the operation status data transmission per unit time is the difference between the maximum and minimum data transmission amounts of the operation status data per unit time.

[0053] Specifically, the weight of key status indicators is a parameter that quantifies the importance of various key status indicators of the pressure plate in judging the operating status of the pressure plate and assessing the operational and maintenance risks.

[0054] Specifically, the reference drift error rate of the state feature within a single period is the ratio of the total deviation of the measured value of the state feature from the reference value to the total reference value within a single period.

[0055] Specifically, the benchmark value is a preset threshold or standard parameter used to measure the normal / standard working condition of the pressure plate.

[0056] Specifically, the dynamic compensation gain for operational status data quality is an adaptive adjustment parameter used to dynamically correct deviations in the operational status data of the relay protection pressure plate and improve data quality.

[0057] In practice, the beneficial effects of this invention are as follows: The system of this invention, by setting up a data acquisition module, a data processing module, a state assessment module, a filtering adjustment module, an identification adjustment module, and a compensation adjustment module, adjusts the multi-dimensional feature differentiation filtering coefficient according to the accuracy of the protection pressure plate state feature matching. Since substations are located in outdoor or semi-outdoor environments, composite pollution layers cover the identification and state feature areas of the pressure plate, leading to noise interference during feature extraction. By adjusting the multi-dimensional feature differentiation filtering coefficient, the extraction capabilities of the grayscale features, edge contour features, and identification texture features of the pressure plate at different scales can be simultaneously assessed, effectively separating pollution noise from real state features and improving feature extraction accuracy. Furthermore, the weight of key state identification is adjusted based on the fluctuation value of the operating state data transmission per unit time. Because the operation of relay protection devices and high-voltage equipment generates high-frequency electromagnetic radiation, which superimposes with the state data transmission signal, it causes signal amplitude fluctuations and transmission... To mitigate latency, by adjusting the weights of key status identifiers, the system prioritizes parsing and transmitting key identifier information during data transmission fluctuations, reducing the bandwidth consumption of non-critical data. Simultaneously, a weighted algorithm reduces the impact of fluctuating signals on the key identifier parsing results, ensuring real-time transmission of core status information and avoiding recognition lag issues caused by transmission delays. Furthermore, the system dynamically adjusts the gain for compensating for operational status data quality based on the baseline drift error rate of status characteristics within a single cycle. Fluctuations in temperature and humidity within the substation, equipment vibration causing sensor installation position shifts, and aging of electronic components leading to baseline drift in signal acquisition result in systematic deviations in the status data of the same relay protection plate collected by different sensors. By adjusting the gain for dynamic compensation of operational status data quality, differentiated deviation compensation can be performed on the data collected by different sensors. The redundant information from multiple data sources offsets the drift effect of a single sensor, improving the reliability of the data source and enhancing the stability of relay protection plate operation and maintenance management.

[0058] Please continue reading. Figure 2 As shown, it is a logic flowchart of determining the adaptive filter step size factor in the intelligent operation and maintenance management system for substation relay protection pressure plates according to an embodiment of the present invention.

[0059] Specifically, the filtering adjustment module determines that the operation and maintenance management stability of the relay protection plate meets the requirements when the matching accuracy of the protection plate state characteristics is greater than or equal to a preset second accuracy.

[0060] The filtering adjustment module determines that the stability of the operation and maintenance management of the relay protection plate does not meet the requirements when the matching accuracy of the protection plate state characteristics is less than the preset second accuracy.

[0061] Specifically, the filtering adjustment module responds to the fact that the accuracy of the matching of the protection pressure plate status features is greater than the preset first accuracy and less than the preset second accuracy, initially determining that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements, and determines whether the real-time performance of the protection pressure plate status data acquisition meets the requirements based on the fluctuation value of the data transmission of the operating status within a unit time.

[0062] Understandably, the preset first accuracy rate is lower than the preset second accuracy rate. The preset first accuracy rate and the preset second accuracy rate are divided into three intervals, each corresponding to one of the three scenarios:

[0063] The first interval is when the accuracy of matching the status features of the protection pressure plate is less than or equal to the preset first accuracy. The corresponding situation is: because the substation is in an outdoor or semi-outdoor environment, the composite pollution layer covers the marking and status feature area of ​​the pressure plate, resulting in noise interference during feature extraction.

[0064] The second interval is when the accuracy of the protection pressure plate status feature matching is greater than the preset first accuracy and less than the preset second accuracy. The corresponding situation is: due to the high frequency electromagnetic radiation generated by the operation of the relay protection device and high voltage equipment, which is superimposed on the status data transmission signal, the signal amplitude fluctuates and the transmission delay occurs.

[0065] The third interval is when the confidence level of the protection pressure plate status feature identification is greater than or equal to the preset second accuracy rate, which corresponds to the situation that the stability of the operation and maintenance management of the relay protection pressure plate meets the requirements.

[0066] Understandably, this system uses preset first and second accuracy rates to characterize the accuracy of state feature extraction. The core principle is to utilize accuracy thresholds to quantitatively classify the quality of feature extraction, accurately distinguishing between three states: qualified extraction, data acquisition requiring real-time diagnostics, and urgent adjustment of filter parameters. This avoids the one-sidedness of a single threshold judgment and adapts to the needs of substation relay protection circuit boards for graded control of state identification accuracy. The preset first accuracy rate can be set as the system's inherent fluctuation threshold to ensure that minor environmental interference or data fluctuations are not over-responded to, reducing unnecessary parameter adjustments. The preset second accuracy rate is set as the system's stable operation threshold to ensure that feature extraction quality meets standards and avoids misjudgments due to the loss of core features. This setting balances the stability of equipment operation under normal conditions while accurately identifying extraction quality deviations caused by pollution interference and transmission fluctuations, avoiding interference from short-term feature fluctuations in the overall stability assessment. The preset first and second accuracy rates can be set according to actual operating conditions, aiming to ensure the stability and practicality of relay protection circuit board operation and maintenance management. Optionally, the preset first accuracy rate and preset second accuracy rate are determined by evaluating the effect of different feature matching accuracy rates on the operation and maintenance management of the relay protection circuit board through a limited number of tests. The preset first accuracy rate and preset second accuracy rate should be neither too small nor cause excessive interference to the operation and maintenance management process of the relay protection circuit board. For example, the preset first accuracy rate is generally selected in the range of [94%, 96%], and the preset second accuracy rate is generally selected in the range of [97%, 99%].

[0067] Preferably, the first accuracy rate is 95% in the preferred embodiment, and the second accuracy rate is 98% in the preferred embodiment.

[0068] Specifically, the filtering adjustment module increases the multi-dimensional feature differentiation filtering coefficient in response to the protection pressure plate state feature matching accuracy being less than or equal to the preset first accuracy.

[0069] The increase in the multi-dimensional feature discrimination filtering coefficient is determined by the difference between the preset first accuracy rate and the protection pressure plate state feature matching accuracy rate.

[0070] Specifically, when the difference between the preset first accuracy rate and the matching accuracy rate of the protection pressure plate status features is within 2%, the multi-dimensional feature discrimination filter coefficient is increased to 1.1 times its original value. When the difference between the preset first accuracy rate and the matching accuracy rate of the protection pressure plate status features exceeds 2%, in addition to increasing to 1.1 times its original value, for every additional 1% exceeding 2%, the multi-dimensional feature discrimination filter coefficient is further increased by 0.1. For example, if the difference between the preset first accuracy rate and the matching accuracy rate of the protection pressure plate status features is 3%, and the current multi-dimensional feature discrimination filter coefficient is 1.0, the increased multi-dimensional feature discrimination filter coefficient will be 1.0 × 1.1 + 0.1 × 1 = 1.2.

[0071] In practice, the system of the present invention adjusts the multi-dimensional feature discrimination filtering coefficient by setting a preset first accuracy rate and a preset second accuracy rate. Since the substation is in an outdoor or semi-outdoor environment, the composite pollution layer covers the marking and status feature areas of the pressure plate, resulting in noise interference during feature extraction. By adjusting the multi-dimensional feature discrimination filtering coefficient, the extraction capability of grayscale features, edge contour features and marking texture features of the pressure plate at different scales can be simultaneously applied, effectively separating pollution noise from real status features, improving feature extraction accuracy, and further improving the stability of operation and maintenance management of relay protection pressure plates.

[0072] Please continue reading. Figure 3 As shown, it is a logical flowchart of determining the weight of key status identifiers in the intelligent operation and maintenance management system for substation relay protection pressure plates according to an embodiment of the present invention.

[0073] Specifically, the identification adjustment module responds to the fluctuation value of the operating status data transmission per unit time being less than or equal to a preset first fluctuation value, thus determining that the real-time performance of the protection pressure plate status data acquisition meets the requirements.

[0074] The identification adjustment module responds to the fact that the fluctuation value of the operating status data transmission per unit time is greater than the preset first fluctuation value, and determines that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements.

[0075] Specifically, the identifier adjustment module increases the weight of key status identifiers in response to the fluctuation value of the operation status data transmission within the unit time being greater than the preset first fluctuation value and less than the preset second fluctuation value.

[0076] Specifically, the identification adjustment module responds to the fluctuation value of the operating status data transmission within the unit time being greater than or equal to the preset second fluctuation value, initially determines that the consistency of the protection pressure plate status data does not meet the requirements, and determines whether the consistency of the protection pressure plate status data meets the requirements based on the benchmark drift error rate of the status characteristics within a single cycle.

[0077] It is understandable that the preset first fluctuation value is less than the preset second fluctuation value, and the three intervals divided by the preset first fluctuation value and the preset second fluctuation value correspond to three different situations:

[0078] The first interval is when the fluctuation value of the data transmission of the operating status within a unit of time is less than or equal to the preset first fluctuation value. The corresponding situation is: the real-time performance of the protection pressure plate status data acquisition meets the requirements.

[0079] The second interval is where the fluctuation value of the operating status data transmission per unit time is greater than the preset first fluctuation value and less than the preset second fluctuation value. The corresponding situation is: due to the high-frequency electromagnetic radiation generated by the operation of the relay protection device and high-voltage equipment, which is superimposed on the status data transmission signal, the signal amplitude fluctuates and the transmission delay occurs.

[0080] The third interval is when the fluctuation value of the data transmission of the operating status within a unit of time is greater than or equal to the preset second fluctuation value. The corresponding situation is: due to the temperature and humidity fluctuations in the substation, equipment vibration causing the sensor installation position to shift, and the aging of electronic components causing the signal acquisition reference to drift, the same pressure plate status data collected by different sensors will show systematic deviation.

[0081] Understandably, using preset first and second fluctuation values ​​to characterize the real-time performance of the protection circuit board status data acquisition avoids the limitations of a single threshold judgment and adapts to the data transmission characteristics of the complex electromagnetic environment in substations through a gradient control strategy. The preset first fluctuation value corresponds to the critical point between normal transmission and minor interference, ensuring that frequent weight adjustments are unnecessary under normal operating conditions, reducing system computational resource consumption. The preset second fluctuation value corresponds to the critical point between minor fluctuations and severe interference, ensuring that the consistency judgment process is triggered promptly when transmission anomalies occur, avoiding the accumulation of data deviations. This setting ensures system stability when real-time performance meets the standards and accurately responds to different levels of electromagnetic interference, avoiding identification errors caused by transmission problems. The preset first and second fluctuation values ​​can be set according to actual operating conditions. The setting of the preset first and second fluctuation values ​​aims to ensure the stability and practicality of the operation and maintenance management of the relay protection circuit board. Optionally, the preset first fluctuation value and the preset second fluctuation value are determined through a limited number of tests by evaluating the effect of different feature matching accuracy rates on the operation and maintenance management of the relay protection circuit board. The determined preset first fluctuation value and preset second fluctuation value should meet the requirement that they are neither too small nor cause excessive interference to the operation and maintenance management process of the relay protection circuit board. For example, the preset first fluctuation value is generally selected in the range of [10ms, 15ms], and the preset second fluctuation value is generally selected in the range of [16ms, 20ms].

[0082] Preferably, the first fluctuation value is preset to 13ms in a preferred embodiment, and the second fluctuation value is preset to 17ms in a preferred embodiment.

[0083] Specifically, the increase in the weight of the key status identifier is determined by the difference between the fluctuation value of the running status data transmission per unit time and the preset first fluctuation value.

[0084] Specifically, when the difference between the fluctuation value of the operation status data transmission per unit time and the preset first fluctuation value is within 2ms, the weight of the key status identifier increases to 1.15 times its original value. When the difference exceeds 2ms, in addition to increasing to 1.15 times its original value, the weight of the key status identifier increases by an additional 0.02 for every 1ms exceeding the preset first fluctuation value. For example, if the difference between the fluctuation value of the operation status data transmission per unit time and the preset first fluctuation value is 4ms, and the current weight of the key status identifier is 0.6, then the increased weight of the key status identifier will be 0.6 × 1.15 + 0.02 × 2 = 0.73.

[0085] In implementation, the system of the present invention adjusts the weight of key status identifiers by setting preset first fluctuation values ​​and preset second fluctuation values. Since the operation of relay protection devices and high-voltage equipment generates high-frequency electromagnetic radiation, which is superimposed on the status data transmission signal, it causes signal amplitude fluctuations and transmission delays. By adjusting the weight of key status identifiers, the system will prioritize parsing and transmitting key identifier information when data transmission fluctuates, reducing the occupation of transmission bandwidth by non-critical data. At the same time, the weighted algorithm reduces the impact of fluctuation signals on the key identifier parsing results, ensuring the real-time transmission of core status information and avoiding recognition lag problems caused by transmission delays, thereby further improving the stability of operation and maintenance management of relay protection pressure plates.

[0086] Please continue reading. Figure 4 As shown, it is a logic flowchart of the intelligent operation and maintenance management system for substation relay protection pressure plates in an embodiment of the present invention for determining the dynamic compensation gain of operating status data quality.

[0087] Specifically, the compensation adjustment module responds to the reference drift error rate of the state characteristics within a single cycle being less than or equal to a preset error rate, thus determining that the consistency of the protection pressure plate state data meets the requirements.

[0088] The compensation adjustment module responds when the reference drift error rate of the state characteristics within a single cycle is greater than the preset error rate, determines that the consistency of the protection pressure plate state data does not meet the requirements, and increases the dynamic compensation gain for the operating state data quality.

[0089] It is understandable that the two intervals defined by the preset error rate correspond to two different scenarios:

[0090] The first interval is where the baseline drift error rate of the state characteristics within a single cycle is less than or equal to the preset error rate. The corresponding situation is: the long-term consistency of the protection pressure plate state data meets the requirements.

[0091] The second interval is where the reference drift error rate of the state characteristics within a single cycle is greater than the preset error rate. The corresponding situation is: due to temperature and humidity fluctuations in the substation, equipment vibration causing sensor installation position shifts, and aging of electronic components causing signal acquisition reference drift, resulting in systematic deviations in the same pressure plate state data collected by different sensors.

[0092] It is understandable that using a preset error rate to characterize the stability of sensor measurement data is primarily based on its core properties: quantifying the degree of measurement accuracy attenuation, accurately defining the compensation trigger threshold, and achieving adaptive data quality optimization. The preset error rate is a threshold determined during the system design phase by analyzing the impact of sensor drift on state judgment under different operating environments, the statistical characteristics of the substation electromagnetic environment, and the accuracy requirements of relay protection for data consistency. Its core function is to define the acceptable normal measurement fluctuations and the critical point where quality compensation is necessary; enabling the system to accurately judge the reliability of operating status data and dynamically adjust the compensation strategy. By improving the dynamic compensation gain of data quality, it corrects systematic measurement deviations, ultimately ensuring the accuracy and stability of the protection circuit board state assessment results. The preset error rate can be set according to actual operating conditions. The setting of the preset error rate aims to ensure the stability and practicality of the operation and maintenance management of the relay protection circuit board. Optionally, the preset error rate is determined through a limited number of tests by evaluating the effect of different feature matching accuracy rates on the operation and maintenance management of the relay protection circuit board. The determined preset error rate should be neither too small nor cause excessive interference to the operation and maintenance management process of the relay protection circuit board.

[0093] For example, the preset error rate is typically selected in the range of [1%, 3%].

[0094] Preferably, the preset error rate is 2% in the preferred embodiment.

[0095] Specifically, the increase in the dynamic compensation gain for the operational status data quality is determined by the difference between the baseline drift error rate of the status characteristics within a single cycle and the preset error rate.

[0096] Specifically, when the difference between the baseline drift error rate and the preset error rate of the state characteristics within a single cycle is within 0.5%, the dynamic compensation gain for operational status data quality increases to 1.2 times the original value. When the difference exceeds 0.5%, in addition to increasing to 1.2 times the original value, the dynamic compensation gain for operational status data quality increases by an additional 0.1 for every 0.5% exceeding the original value. For example, if the difference between the baseline drift error rate and the preset error rate of the state characteristics within a single cycle is 1.5%, and the current dynamic compensation gain for operational status data quality is 1.0, then the increased dynamic compensation gain for operational status data quality is 1.0 × 1.2 + 0.1 × 2 = 1.4.

[0097] In practice, the system described in this invention adjusts the dynamic compensation gain for the quality of operating status data by setting a preset error rate. Due to temperature and humidity fluctuations and equipment vibrations in the substation causing sensor installation position shifts, and aging of electronic components causing signal acquisition reference drift, systematic deviations occur in the status data of the same pressure plate collected by different sensors. By adjusting the dynamic compensation gain for the quality of operating status data, the compensation for high-quality data can be enhanced, the impact of drift data on status judgment can be weakened, and the stability of operation and maintenance management of relay protection pressure plates can be further improved.

[0098] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. An intelligent operation and maintenance management system for substation relay protection circuit boards, characterized in that, include: The data acquisition module is used to collect the operating status data of substations equipped with relay protection pressure plates; The data processing module, which is connected to the data acquisition module, includes a preprocessing unit for preprocessing the running status data to output standardized status data and a feature extraction unit connected to the preprocessing unit for extracting features from the standardized status data to output status features. The status assessment module, which is connected to the data processing module, includes a model training unit for training an initial model based on the status characteristics to obtain an intelligent assessment model, and an assessment unit connected to the model training unit for assessing the operating status of the relay protection pressure plate based on the intelligent assessment model to obtain an assessment result. A filtering adjustment module, which is connected to the data processing module, is used to determine the multi-dimensional feature differentiation filtering coefficients based on the matching accuracy of state features. The identifier adjustment module is connected to the data acquisition module and the filter adjustment module respectively, and is used to determine the key status identifier weight based on the fluctuation value of the running status data transmission per unit time. The compensation adjustment module is connected to the data processing module and the identification adjustment module respectively, and is used to determine the dynamic compensation gain of the running status data quality based on the reference drift error rate of the state characteristics within a single cycle.

2. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 1, characterized in that, The filter adjustment module responds to the fact that the accuracy of the protection pressure plate state feature matching is less than the preset second accuracy rate, and determines that the stability of the operation and maintenance management of the relay protection pressure plate does not meet the requirements.

3. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 2, characterized in that, The filtering adjustment module responds to the fact that the accuracy of the matching of the protection pressure plate status features is greater than the preset first accuracy and less than the preset second accuracy. It initially determines that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements, and determines whether the real-time performance of the protection pressure plate status data acquisition meets the requirements based on the fluctuation value of the data transmission of the operating status within a unit time.

4. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 3, characterized in that, The filtering adjustment module increases the multi-dimensional feature differentiation filtering coefficient in response to the fact that the accuracy of the matching of the protective pressure plate state feature is less than or equal to the preset first accuracy. The increase in the multi-dimensional feature discrimination filtering coefficient is determined by the difference between the preset first accuracy rate and the protection pressure plate state feature matching accuracy rate.

5. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 4, characterized in that, The identification adjustment module responds to the fact that the fluctuation value of the operating status data transmission per unit time is greater than the preset first fluctuation value, and determines that the real-time performance of the protection pressure plate status data acquisition does not meet the requirements.

6. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 5, characterized in that, The identifier adjustment module increases the weight of the key status identifier in response to the fluctuation value of the operation status data transmission within the unit time being greater than the preset first fluctuation value and less than the preset second fluctuation value.

7. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 6, characterized in that, The identification adjustment module responds to the fluctuation value of the operating status data transmission within the unit time being greater than or equal to the preset second fluctuation value, and initially determines that the consistency of the protection pressure plate status data does not meet the requirements. It then determines whether the consistency of the protection pressure plate status data meets the requirements based on the benchmark drift error rate of the status characteristics within a single cycle.

8. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 7, characterized in that, The increase in the weight of the key status identifier is determined by the difference between the fluctuation value of the running status data transmission per unit time and the preset first fluctuation value.

9. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 8, characterized in that, The compensation adjustment module responds to the fact that the reference drift error rate of the state characteristics within a single cycle is greater than the preset error rate, determines that the consistency of the protection pressure plate state data does not meet the requirements, and increases the dynamic compensation gain for the quality of the operating state data.

10. The intelligent operation and maintenance management system for substation relay protection circuit boards according to claim 9, characterized in that, The increase in the dynamic compensation gain for the operational status data quality is determined by the difference between the baseline drift error rate of the status characteristics within a single cycle and the preset error rate.

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