Station electric equipment transient feature extraction system based on event awareness

Abstract

The invention relates to the technical field of station electric equipment, in particular to a station electric equipment transient feature extraction system based on event perception, which comprises a current and voltage analysis module, an event detection and classification module, an emergency response optimization module and a monitoring feedback adjustment module. According to the invention, by collecting and analyzing the current waveform data in real time and identifying the abnormal events related to the voltage and the current, the identification process not only improves the early warning capability of potential problems in the power system, but also enhances the quick response to the events, and real-time frequency analysis enables the system to refine the type of the voltage events and improve the accuracy of fault diagnosis. By analyzing the potential influence of the voltage abnormity type on the equipment, the emergency response process is formulated, the response measures can effectively cope with various conditions faced by the power equipment, the operation state of the power equipment is kept at the optimal level through the continuous monitoring and adjusting function, and the stability and safety of the power system are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of station power equipment, and in particular to a transient feature extraction system for station power equipment based on event perception. Background Art

[0002] Station power equipment technology mainly involves all electrical equipment inside the power station used to support power generation, transformation or distribution operations. The equipment includes but is not limited to transformers, circuit breakers, control systems and auxiliary service equipment. It is essential to ensure the stable supply, efficient conversion and distribution of electricity. The key lies in maintaining and optimizing the performance of the equipment to adapt to the ever-changing power demand and conditions.

[0003] Among them, the transient feature extraction system of power station electrical equipment is used to detect and analyze the transient changes in the electrical performance of power station electrical equipment during specific events (such as faults and load changes). Its purpose is to identify potential problems in advance through an in-depth understanding of the response of electrical equipment, thereby improving the reliability and efficiency of the equipment. The extraction of transient features helps to accurately adjust maintenance strategies, prevent equipment failures, and optimize the operating performance of the power station.

[0004] Traditional systems rely on predetermined data analysis and response mechanisms and cannot flexibly respond to dynamic changes in the power system. This static processing method leads to a lag in response to emergencies and increases the risk of failures. For example, voltage drops are not identified and handled in a timely manner, causing wider power supply problems. This shortcoming of existing technologies is particularly evident during peak power demand or extreme weather conditions, which can easily lead to equipment overload or even damage. The lack of real-time monitoring and intelligent analysis also makes it difficult for the power station's operation and maintenance team to achieve accurate control of the equipment status, making it impossible to adjust maintenance strategies in a timely manner, affecting the power station's operating efficiency and power output stability. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and to propose a transient feature extraction system for station power equipment based on event perception.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a transient feature extraction system for station power equipment based on event perception, the system comprising: The current and voltage analysis module collects current waveform data in real time based on the circuit breaker status and voltage level, analyzes current and voltage changes through the ARMA model, identifies transient voltage fluctuations and current anomalies in the sequence, and obtains abnormal current and voltage events; The event detection and classification module uses complex event processing based on the abnormal current and voltage events to identify voltage sags and abnormal voltage events of the equipment through frequency analysis, records key voltage waveform features and event parameters, refines the voltage event type, and obtains abnormal event features; The emergency response optimization module analyzes the potential impact of the differential voltage abnormality type on the station power equipment based on the abnormal event characteristics, determines the emergency response process for each event type, and adjusts the response process according to real-time data to obtain the emergency response configuration; The monitoring feedback adjustment module monitors the circuit breaker status and current changes based on the emergency response configuration, implements the response process, records the equipment operation status and the execution effect of the response process, and adjusts the sensor configuration and response parameters according to the monitoring data to obtain the operation status adjustment result.

[0007] The present invention is improved in that the analysis steps of the current and voltage changes are specifically as follows: Based on the circuit breaker status and voltage level, the current waveform data is collected and the voltage readings are recorded simultaneously to obtain the current and voltage data set; Based on the current and voltage data set, using the ARMA model, the dynamic relationship between current and voltage is estimated to obtain current and voltage relationship information; Using the current-voltage relationship information, the formula is adopted: ; Analyze the dynamic changes of current and voltage to obtain the analysis results of current and voltage changes ,in, Representative A measured current or voltage value, is the average value, Indicates the rate of change of current or voltage. and is the weight coefficient, is the total number of data points.

[0008] The present invention is improved in that the steps of acquiring the abnormal current and voltage events are specifically as follows: According to the current and voltage changes, abnormal thresholds are adjusted to match the current electrical system state, abnormal fluctuations in current and voltage are identified, and a preliminary abnormal signal list is generated; The preliminary abnormal signal list is analyzed using the formula: ; Analyze the criticality of each abnormal signal and obtain abnormal current and voltage events ,in, is the current or voltage value at the target time point, is the average current or voltage value within the sliding window, is the standard deviation within the sliding window, For each data point The weight factor of is the total number of data points.

[0009] The present invention is improved in that the steps of identifying the voltage sag and voltage abnormality events are specifically as follows: Based on the abnormal current and voltage events, voltage and current data are collected to determine potential voltage sags or anomalies, and a preliminary screening list is generated; Perform frequency analysis on the preliminary screening list to identify frequency anomalies that differ from normal operating patterns using the formula: ; Calculate the frequency content of the signal and identify voltage sags and voltage anomalies, where: Indicates frequency The power spectral density at Representative time The voltage value, represents the analysis frequency, is the total sampling time of the signal.

[0010] The present invention is improved in that the step of acquiring the abnormal event characteristics is specifically as follows: Recording key parameters of each identified abnormal event, including event occurrence time, duration period, voltage peak value, and abnormal waveform change, to obtain an abnormal data set; The abnormal data set is analyzed using the formula: ; Refine voltage event type , get the abnormal event characteristics, where is the average voltage value, Indicates the maximum difference between normal voltage and abnormal voltage. is the duration of the abnormal voltage event.

[0011] The present invention is improved in that the analysis steps of the potential impact on the station electrical equipment are specifically as follows: Based on the abnormal event characteristics, including short-term voltage drop and continuous low voltage, mark the key characteristics of each type of event and generate a classified event list; The classified event list is analyzed to evaluate the potential impact of each type of voltage anomaly on the station's electrical equipment using the formula: ; Calculate the impact index for each voltage anomaly type ,in, The average voltage change indicating voltage anomaly, is the baseline voltage value, represents the average duration of an event, is the weight parameter.

[0012] The present invention is improved in that the step of obtaining the emergency response configuration is specifically as follows: Determine the emergency response process for each type of voltage abnormality event, including defining response actions, required resources, staffing, and emergency communication processes, and obtain a list of emergency response processes; Based on the emergency response process list, real-time monitoring is performed using the formula: ; Dynamically adjust the emergency process to match real-time data changes to obtain emergency response configuration, where: represents the response adjustment value, is the real-time voltage change, is the normal voltage value, is the response strength, is the sensitivity coefficient.

[0013] The present invention is improved in that the step of obtaining the operation status adjustment result is specifically as follows: Based on the emergency response configuration, regularly obtain the real-time status and current change data of the circuit breaker, determine the current working condition of the device, and generate initial status information; According to the initial state information, the risk assessment value of the equipment is calculated using the formula: ; Quantify the correlation between current fluctuations and state changes to obtain risk assessment results ,in, Indicates the current variation amplitude, is the average current value, is the number of state changes; The risk assessment result is used to adjust the sensor configuration and circuit breaker response parameters to obtain an operation status adjustment result.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, abnormal events related to voltage and current are identified by real-time acquisition and analysis of current waveform data. The identification process not only improves the early warning capability of potential problems in the power system, but also enhances the rapid response to events. Real-time frequency analysis enables the system to refine the type of voltage events and improve the accuracy of fault diagnosis. By analyzing the potential impact of abnormal voltage types on equipment, the formulation of emergency response processes is also realized to ensure that response measures can effectively cope with various situations faced by power equipment. Through continuous monitoring and adjustment functions, the operating status of power equipment is maintained at an optimal level, ensuring the stability and safety of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a system flow chart of the present invention; Figure 2 It is a flow chart for analyzing the changes of current and voltage in the present invention; Figure 3 is a flow chart for obtaining abnormal current and voltage events in the present invention; Figure 4 This is a flow chart for identifying voltage sag and voltage anomaly events in the present invention; Figure 5 It is a flow chart of obtaining abnormal event characteristics in the present invention; Figure 6 This is a flow chart of the analysis of the potential impact on the station's electrical equipment in the present invention; Figure 7 A flowchart for obtaining the emergency response configuration in the present invention; Figure 8 The figure is a flow chart for obtaining the operation status adjustment result in the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0018] Example: See Figure 1 The present invention provides a technical solution: a transient feature extraction system for station power equipment based on event perception includes: The current and voltage analysis module collects current waveform data in real time based on the circuit breaker status and voltage level, analyzes current and voltage changes through the ARMA model, identifies transient voltage fluctuations and current anomalies in the sequence, and obtains abnormal current and voltage events; The event detection and classification module is based on abnormal current and voltage events. It uses complex event processing to identify voltage sags and abnormal voltage events of equipment through frequency analysis, records key voltage waveform features and event parameters, refines voltage event types, and obtains abnormal event features. The emergency response optimization module analyzes the potential impact of different voltage anomaly types on station power equipment based on the characteristics of abnormal events, determines the emergency response process for each event type, and adjusts the response process according to real-time data to obtain the emergency response configuration; the emergency response process is as follows: in the event of a voltage sag, the voltage level is automatically detected through real-time monitoring, and an alarm is issued when the voltage drops beyond the standard threshold. Subsequently, the automatic control mechanism adjusts the transformer tap or starts the voltage regulating equipment to try to restore the normal voltage level. If the voltage fails to recover, the system automatically starts the backup power supply, such as the generator, to ensure the power supply of key facilities. At the same time, the data during the event will be recorded for subsequent analysis of the cause and impact of the voltage sag; For current anomalies (such as overload or short circuit), the system continuously monitors the current intensity and immediately issues an alarm if an anomaly is detected. It automatically or manually isolates the overload circuit to prevent further equipment damage or safety accidents. It locates the source of the problem through fault location to facilitate rapid processing and repair. After the fault is processed, the load distribution is reconfigured as needed to optimize the operating status of the station's electrical equipment. When faced with high-frequency voltage or current fluctuations, the system continuously tracks the volatility of voltage and current. Once the fluctuation exceeds the safe range, the automatic adjustment mechanism will intervene, such as frequency response or power regulation, to stabilize the status of the station's power equipment. The system will analyze the impact of the fluctuation on the entire power equipment and connected equipment, and evaluate the long-term impact. Finally, it will adjust the power consumption strategy or perform equipment maintenance based on the cause and characteristics of the fluctuation.

[0019] The monitoring feedback adjustment module monitors the circuit breaker status and current changes based on the emergency response configuration, implements the response process, records the equipment operation status and the execution effect of the response process, and adjusts the sensor configuration and response parameters according to the monitoring data to obtain the operation status adjustment result.

[0020] Abnormal current and voltage events include voltage fluctuation type, current peak classification, and abnormal persistence identification. Abnormal event characteristics include key waveform identification, frequency response range, and event persistence classification information. Emergency response configuration includes process detail information, response speed level, and response scheduled process. Operation status adjustment results include sensor adjustment type, parameter optimization results, and effect record details.

[0021] See also Figure 2 , the analysis steps of current and voltage changes are as follows: Based on the circuit breaker status and voltage level, the current waveform data is collected and the voltage readings are recorded simultaneously to obtain the current and voltage data set; Based on the real-time monitoring of the circuit breaker status and voltage level, the current waveform data is collected and the voltage readings are recorded synchronously. In this process, the current and voltage data are continuously recorded to construct a current and voltage time series data set. The data set includes the current and voltage values ​​of each monitoring point. The generation of the data set relies on time synchronization and data acquisition technology to ensure the integrity and reliability of the data, so that subsequent analysis can be carried out based on complete data.

[0022] Based on the current and voltage data set, the ARMA model is used to estimate the dynamic relationship between current and voltage and obtain the current-voltage relationship information; The current and voltage time series data set is input into the ARMA model. Based on the maximum likelihood estimation method or other statistical methods, the dynamic relationship between current and voltage can be accurately captured. The key lies in selecting the matching model order and parameter initialization to obtain a model that accurately reflects the interdependence between current and voltage.

[0023] Using the current-voltage relationship information, the formula is used: ; Analyze the dynamic changes of current and voltage to obtain the analysis results of current and voltage changes ,in, Representative A measured current or voltage value, is the average value, Indicates the rate of change of current or voltage. and is the weight coefficient, To adjust for deviations from the mean The impact of To adjust the rate of change The impact of is the total number of data points; If there are 4 data points, , is the difference between the data points, if and , through specific data and , calculated: ; ; The results show that the fluctuations of current and voltage deviate by a total of 4.5 within a given time window, reflecting the activeness of the current and voltage changes and their instability to a certain extent, which is helpful for further analysis and formulation of control strategies.

[0024] See also Figure 3 , the specific steps for obtaining abnormal current and voltage events are: According to the changes in current and voltage, the abnormal threshold is adjusted to match the current electrical system status, identify unusual fluctuations in current and voltage, and generate a preliminary abnormal signal list; When rapid changes in voltage and current are detected, the threshold is automatically adjusted to identify abnormal electrical activities. The data is recorded as preliminary abnormal signals. Each signal represents an electrical fault point, ensuring the response speed and sensitivity of electrical safety monitoring. By automatically adjusting the threshold, the system can more effectively cope with rapid fluctuations in voltage and current. The recorded abnormal signals will be transmitted to the next analysis stage for further verification.

[0025] Analyze the preliminary list of abnormal signals using the formula: ; Analyze the criticality of each abnormal signal and obtain abnormal current and voltage events ,in, is the current or voltage value at the target time point, is the average current or voltage value within the sliding window, is the standard deviation within the sliding window, For each data point The weight factor of is the total number of data points; There are N=10 data points in the target time window, ,average value , standard deviation , set the weight factor , then the formula is calculated as: ; ; ; The results show that within the reference time window, the current value has a significant deviation of 8.33 relative to the average current, indicating that the instability of the current may lead to abnormal operation or failure of the equipment.

[0026] See also Figure 4 , the specific steps for identifying voltage sag and voltage abnormality events are: Based on abnormal current and voltage events, voltage and current data are collected to identify potential voltage sags or anomalies and generate a preliminary screening list; Performing preliminary screening for abnormal voltage and current involves analyzing the continuous data stream received from the sensor, and determining abnormal points in the voltage and current readings through thresholds. The thresholds are preset based on the normal operating parameters of the equipment. By comparing real-time data with the thresholds, readings that are outside the normal range can be automatically marked. Screening methods include statistical comparison and deviation detection, which can identify short-term large fluctuations or continuous small changes. This not only helps the operation and maintenance team respond quickly to potential electrical problems, but also provides a screened and marked data set for subsequent analysis.

[0027] Perform frequency analysis on the initial screening list to identify frequency anomalies that differ from normal operating patterns using the formula: ; Calculate the frequency content of the signal and identify voltage sags and voltage anomalies, where: Indicates frequency The power spectral density at Representative time The voltage value, represents the analysis frequency, is the total sampling time of the signal, is the complex exponential function in Fourier transform; Set the total sampling time milliseconds, referring to the voltage values ​​at three time points , , , the frequency of attention is Hz, the calculation process is as follows: ; ; ; ; The results show that the obtained value It indicates that at a frequency of 50 Hz, the energy distribution of the voltage waveform is very high, indicating that there is a suspected significant voltage anomaly at this frequency.

[0028] See also Figure 5 ,The specific steps for obtaining abnormal event features are: Record the key parameters of each identified abnormal event, including the event occurrence time, duration period, voltage peak value and abnormal waveform change, to obtain an abnormal data set; The key voltage waveform characteristics and event parameters of abnormal voltage events are recorded, including timestamps, duration of events, and changes in voltage peaks and abnormal waveforms. Once the monitored voltage exceeds the preset threshold, the system will automatically record the relevant data to ensure the integrity and accuracy of the data. The collected data is then used for further analysis to refine and classify abnormal voltage events and generate a preliminary screened abnormal data list, which records key parameters such as the start time, duration, and peak voltage of each event.

[0029] To analyze the abnormal data set, the formula is used: ; Refine voltage event type , get the abnormal event characteristics, where is the average voltage value, Indicates the maximum difference between normal voltage and abnormal voltage. is the duration of the abnormal voltage event; The following parameters are included: , , Seconds, substitute into the formula to calculate: ; The calculated result represents the relative impact of the voltage anomaly. This value provides a quantified cumulative effect of the impact and duration of the voltage anomaly event relative to the average voltage change, which helps to analyze the impact of the event and provide a basis for taking appropriate response measures.

[0030] See also Figure 6 , the specific steps for analyzing the potential impact on station electrical equipment are: Based on the abnormal event characteristics, including short-term voltage sag and sustained low voltage, the key features of each type of event are marked to generate a classified event list; Identify and classify abnormal voltage events, including short-term voltage drops and continuous low voltage. Through continuous monitoring and real-time analysis of each voltage reading, determine whether the voltage has dropped significantly or is below the normal operating threshold. In this process, the average value and maximum deviation of the voltage are recorded every minute. The collected voltage waveform is subjected to fast Fourier transform (FFT) to accurately identify abnormal patterns in the voltage waveform, so that the key features of each event, such as the amplitude and duration of the change, are accurately marked. The data is then aggregated into a classified event list, which records the specific features and frequency of occurrence of each type of event to generate a classified event list.

[0031] The classified event list is analyzed to evaluate the potential impact of each type of voltage anomaly on the station's electrical equipment using the formula: ; Calculate the impact index for each voltage anomaly type ,in, The average voltage change indicating voltage anomaly, is the baseline voltage value, represents the average duration of an event, is a weight parameter, which is adjusted according to the sensitivity of the device to voltage fluctuations; The average voltage change of a voltage abnormality event type The baseline voltage is 30V. For 230V, the event duration 90 seconds, device sensitivity weight Set to 1.5, the calculation process is as follows: ; The results show that the potential impact index calculated by It is 17.58, indicating that the impact of abnormal voltage events on station power equipment under specific conditions is significant. The results can be used for further decision-making, such as strengthening equipment protection or optimizing response strategies to reduce the potential negative impact of abnormal voltage.

[0032] See also Figure 7 , the specific steps for obtaining the emergency response configuration are: Determine the emergency response process for each type of voltage abnormality event, including defining response actions, required resources, staffing, and emergency communication processes, and obtain a list of emergency response processes; Determine an emergency response process for each identified voltage anomaly event type. By analyzing the impact of each voltage anomaly type, the event types are prioritized based on the potential damage to key equipment, the frequency of occurrence of the event, and the impact on normal operation. In this process, historical data and equipment failure records need to be called up to ensure that each abnormal event type can be addressed in a targeted manner when formulating a response strategy. Next, according to the priority list, prepare detailed response steps for each voltage anomaly type. The steps include operational instructions, such as shutting down power, adjusting loads, and switching backup systems, so that they can be quickly executed when voltage anomalies occur.

[0033] Based on the emergency response process list, real-time monitoring is carried out using the formula: ; Dynamically adjust the emergency process to match real-time data changes to obtain emergency response configuration, where: Indicates the response adjustment value, which is used to indicate the extent to which the emergency response plan needs to be adjusted. is the real-time voltage change, is the normal voltage value, is the response strength, is the sensitivity coefficient, which is used to adjust the sensitivity to real-time voltage changes; If the real-time voltage change 40V, normal voltage value 230V, response intensity is 2.0, Set to 1.2, the calculation process is as follows: ; ; The results show that emergency response measures can be dynamically optimized according to real-time data changes, thereby reducing the impact on power plant operations.

[0034] See also Figure 8 , the specific steps for obtaining the running status adjustment result are: Based on the emergency response configuration, regularly obtain the real-time status and current change data of the circuit breaker, determine the current working conditions of the equipment, and generate initial status information; Based on the emergency response configuration, real-time status and current change data are regularly collected through sensors installed on the circuit breaker. The data collection process involves real-time monitoring of the current size and the opening and closing status of the circuit breaker to ensure that the real-time data reflects the current working conditions of the circuit breaker. The collected data includes the peak value, average value and any abnormal changes of the current. The data is used by the system to generate the initial status information of the circuit breaker to ensure the accuracy and timeliness of subsequent response measures.

[0035] Based on the initial status information, the risk assessment value of the equipment is calculated using the formula: ; Quantify the correlation between current fluctuations and state changes to obtain risk assessment results ,in, Indicates the current variation amplitude, is the average current value, is the number of state changes; The monitored current data are as follows: the maximum current The minimum current is 120A If the current is 100A, then the current variation is , if the average current , and the number of state changes within a monitoring cycle ,but: ; The result shows that the risk assessment value is 0.3256, which means that under the current current fluctuation and state change frequency, the operational risk faced by the equipment is at a medium level, and the monitoring and response strategies need to be appropriately adjusted to ensure the safety of the equipment.

[0036] Using the risk assessment results, adjust the sensor configuration and circuit breaker response parameters to obtain the operation status adjustment results; Using the risk assessment results, the sensor configuration and the response parameters of the circuit breaker are adjusted according to the real-time working conditions and environmental factors of the circuit breaker. The adjustment process refers to various risk factors, such as current anomalies, short circuit probability and environmental impact. By comprehensively analyzing the risk assessment data, the sensitivity of the sensor and the threshold setting of the circuit breaker are intelligently modified to obtain the operating status adjustment results aimed at optimizing the performance of the circuit breaker.

[0037] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. The transient feature extraction system of power equipment based on event perception is characterized by: The system comprises: The current and voltage analysis module collects current waveform data in real time based on the circuit breaker status and voltage level, analyzes current and voltage changes through the ARMA model, identifies transient voltage fluctuations and current anomalies in the sequence, and obtains abnormal current and voltage events; The event detection and classification module uses complex event processing based on the abnormal current and voltage events to identify voltage sags and abnormal voltage events of the equipment through frequency analysis, records key voltage waveform features and event parameters, refines the voltage event type, and obtains abnormal event features; The emergency response optimization module analyzes the potential impact of the differential voltage abnormality type on the station power equipment based on the abnormal event characteristics, determines the emergency response process for each event type, and adjusts the response process according to real-time data to obtain the emergency response configuration; The monitoring feedback adjustment module monitors the circuit breaker status and current changes based on the emergency response configuration, implements the response process, records the equipment operation status and the execution effect of the response process, and adjusts the sensor configuration and response parameters according to the monitoring data to obtain the operation status adjustment result.

2. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The analysis steps of the current and voltage changes are specifically as follows: Based on the circuit breaker status and voltage level, the current waveform data is collected and the voltage readings are recorded simultaneously to obtain the current and voltage data set; Based on the current and voltage data set, using the ARMA model, the dynamic relationship between current and voltage is estimated to obtain current and voltage relationship information; Using the current-voltage relationship information, the formula is adopted: ； Analyze the dynamic changes of current and voltage to obtain the analysis results of current and voltage changes ,in, Representative A measured current or voltage value, is the average value, Indicates the rate of change of current or voltage. and is the weight coefficient, is the total number of data points.

3. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The steps for obtaining the abnormal current and voltage events are specifically as follows: According to the current and voltage changes, abnormal thresholds are adjusted to match the current electrical system state, abnormal fluctuations in current and voltage are identified, and a preliminary abnormal signal list is generated; The preliminary abnormal signal list is analyzed using the formula: ； Analyze the criticality of each abnormal signal and obtain abnormal current and voltage events ,in, is the current or voltage value at the target time point, is the average current or voltage value within the sliding window, is the standard deviation within the sliding window, For each data point The weight factor of is the total number of data points.

4. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The steps for identifying voltage sag and voltage abnormality events are specifically as follows: Based on the abnormal current and voltage events, voltage and current data are collected to determine potential voltage sags or anomalies, and a preliminary screening list is generated; Perform frequency analysis on the preliminary screening list to identify frequency anomalies that differ from normal operating patterns using the formula: ； Calculate the frequency content of the signal and identify voltage sags and voltage anomalies, where: Indicates frequency The power spectral density at Representative time The voltage value, represents the analysis frequency, is the total sampling duration of the signal.

5. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The steps for obtaining the abnormal event characteristics are specifically as follows: Recording key parameters of each identified abnormal event, including event occurrence time, duration period, voltage peak value, and abnormal waveform change, to obtain an abnormal data set; The abnormal data set is analyzed using the formula: ； Refine voltage event type , get the abnormal event characteristics, where is the average voltage value, Indicates the maximum difference between normal voltage and abnormal voltage. is the duration of the abnormal voltage event.

6. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The analysis steps of the potential impact on the station's electrical equipment are specifically as follows: Based on the abnormal event characteristics, including short-term voltage drop and continuous low voltage, mark the key characteristics of each type of event and generate a classified event list; The classified event list is analyzed to evaluate the potential impact of each type of voltage anomaly on the station's electrical equipment using the formula: ； Calculate the impact index for each voltage anomaly type ,in, The average voltage change indicating voltage anomaly, is the baseline voltage value, represents the average duration of an event, is the weight parameter.

7. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The steps for obtaining the emergency response configuration are specifically as follows: Determine the emergency response process for each type of voltage abnormality event, including defining response actions, required resources, staffing, and emergency communication processes, and obtain a list of emergency response processes; Based on the emergency response process list, real-time monitoring is performed using the formula: ； Dynamically adjust the emergency process to match real-time data changes to obtain emergency response configuration, where: represents the response adjustment value, is the real-time voltage change, is the normal voltage value, is the response strength, is the sensitivity coefficient.

8. The transient feature extraction system for station power equipment based on event perception according to claim 1 is characterized in that: The steps for obtaining the operation status adjustment result are specifically as follows: Based on the emergency response configuration, regularly obtain the real-time status and current change data of the circuit breaker, determine the current working condition of the device, and generate initial status information; According to the initial state information, the risk assessment value of the equipment is calculated using the formula: ； Quantify the correlation between current fluctuations and state changes to obtain risk assessment results ,in, Indicates the current variation amplitude, is the average current value, is the number of state changes; The risk assessment result is used to adjust the sensor configuration and circuit breaker response parameters to obtain an operation status adjustment result.

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