An intelligent data optimization management system for high-voltage resonant reactance experiments

Abstract

The present invention discloses an intelligent data optimization management system for high-voltage resonant reactance experiments. The present invention relates to the technical field of data analysis and includes a data management center, which is communicatively connected to a data acquisition module, a data preprocessing module, a resonant state analysis module, an environmental interference analysis module, an accuracy evaluation module, and an experimental optimization suggestion module. This intelligent data optimization management system for high-voltage resonant reactance experiments calculates a resonant state evaluation index through the resonant state analysis module to quantify the resonant state of the circuit, combines with the environmental interference evaluation module to evaluate the interference degree of external environmental factors on the experiment, and conducts comprehensive analysis through the accuracy evaluation module to predict the accuracy and reliability of the experimental results, enabling experimenters to identify potential problems in advance and take measures to avoid or reduce the occurrence of related problems, thereby enhancing the predictability and stability of the experimental results.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and specifically to an intelligent data optimization management system for high-voltage resonance reactance experiments. Background Art

[0002] High-voltage tests are indispensable for the entire power system and are crucial for ensuring the quality of power system operation. With the development of economic construction, the demand for electricity has increased unprecedentedly, and the power system is facing great pressure. To ensure the quality of power supply, the power system must operate safely and reliably. The principle of high-voltage tests is to use the method of test simulation and, with the help of relevant detection equipment, conduct safety test detections on electrical equipment. The basis is whether the insulation system of the electrical equipment is safe and reliable. In high-voltage tests, resonance tests are a commonly used method. Resonance tests utilize the series or parallel relationship of resistance, inductance, and capacitance elements in a circuit. When the circuit current is in phase with the power supply voltage, resonance occurs.

[0003] In the prior art, since high-voltage resonance reactance experiments involve multiple variables and parameters, and the interaction between parameters increases the complexity of experimental results. Moreover, the experimental process is also affected by temperature changes and electromagnetic interference in the external environment, further increasing the uncertainty of experimental results. Therefore, how to optimize and manage the data of high-voltage resonance reactance experiments and evaluate the impact of experimental interference factors on the accuracy of experimental results is the problem we need to solve. For this reason, an intelligent data optimization management system for high-voltage resonance reactance experiments is proposed. Summary of the Invention

[0004] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent data optimization management system for high-voltage resonance reactance experiments, including a data management center, which is communicatively connected to a data acquisition module, a data preprocessing module, a resonance state analysis module, an environmental interference analysis module, an accuracy evaluation module, and an experimental optimization suggestion module. Among them, the modules are electrically connected to each other;

[0005] The data acquisition module is used to collect the original data of various parameters during the high-voltage resonance reactance experiment, including the inductance value, capacitance value, test frequency, and test voltage of the reactor, and monitor the experimental environment to obtain external environmental factor data such as temperature, humidity, and electromagnetic interference, ensuring the accuracy and integrity of the data and providing a reliable basis for subsequent data processing and analysis;

[0006] The data preprocessing module is used to preprocess the collected raw data and external environmental factor data, including cleaning, filtering, and calibration steps, to remove noise and outliers, improve the quality of the data, standardize the data to make it comparable and consistent, and extract the high-voltage resonance reactance experiment features and environmental factor features;

[0007] The resonance state analysis module uses data analysis techniques to analyze the preprocessed high-voltage resonance reactance experiment data and high-voltage resonance reactance experiment features, identify data trends, and analyze the resonance state of the circuit;

[0008] The environmental interference analysis module combines the preprocessed external environmental factor data and environmental factor features, calculates the environmental interference assessment index, compares it with the reference value of the external environmental factors, and evaluates the interference degree of the external environmental factors on the high-voltage resonance reactance experiment;

[0009] The accuracy evaluation module combines the analysis results of the circuit resonance state and the interference evaluation results of the external environmental factors to perform accuracy analysis, evaluate the data change law of the high-voltage resonance reactance experiment, predict the accuracy of the experimental results, and provide a more comprehensive perspective for the accurate evaluation and prediction of the experimental results;

[0010] The experimental optimization suggestion module determines the accuracy level of the high-voltage resonance reactance experiment based on the accuracy evaluation results of the high-voltage resonance reactance experiment, provides suggestions for experimental design and optimization, adjusts experimental parameters and conditions, and optimizes the experimental scheme to improve the accuracy and reliability of the experimental results.

[0011] Preferably, in the data acquisition module, the process of obtaining the raw data of the high-voltage resonance reactance experiment parameters and the external environmental factor data includes:

[0012] Deploy the measuring instruments for the high-voltage resonance reactance experiment, and arrange temperature sensors, humidity sensors, and electromagnetic interference detectors in the experimental environment to monitor the experimental environment;

[0013] Use the deployed measuring instruments to collect the raw data of the inductance value, capacitance value, test frequency, and test voltage of the reactor during the high-voltage resonance reactance experiment;

[0014] Use the arranged temperature sensors, humidity sensors, and electromagnetic interference detectors to collect the external environmental factor data of the experimental environment. Use the temperature sensor to measure and record the temperature of the experimental environment during the experiment, use the humidity sensor to measure and record the humidity of the experimental environment during the experiment, and use the electromagnetic interference measuring instrument to measure and record the electromagnetic interference level in real time during the experiment;

[0015] Summarize the original data of the high-voltage resonant reactance experiment and the data of external environmental factors collected, mark the data, record the experimental conditions and timestamps, and store them in the data warehouse for subsequent analysis.

[0016] Preferably, in the data preprocessing module, the extraction process of the high-voltage resonant reactance experiment characteristics and environmental factor characteristics includes:

[0017] Extract the collected original data and external environmental factor data from the data warehouse and preprocess them. The preprocessing operations include data cleaning, data filtering, and data calibration steps;

[0018] Perform standardization processing on the preprocessed original data and external environmental factor data to eliminate the influence of dimensional differences between different data, and extract characteristics from the preprocessed and standardized original data and external environmental factor data;

[0019] For the original data during the high-voltage resonant reactance experiment process, extract the high-voltage resonant reactance experiment characteristics of the reactor inductance value, capacitance value, test frequency, and test voltage. Among them, for the reactor inductance value, extract the change trend of the inductance value over time, average value, and standard deviation statistical characteristics. For the capacitance value, extract the change trend of the capacitance value over time, average value, and standard deviation statistical characteristics. For the test frequency, extract the stability and fluctuation range characteristics of the frequency. For the test voltage, extract the peak value, average value, and waveform characteristics of the voltage;

[0020] For the external environmental factor data, extract the environmental factor characteristics of temperature, humidity, and electromagnetic interference. Among them, for temperature, extract the change trend, maximum value, minimum value, and average value characteristics of temperature. For humidity characteristics, extract the change trend, maximum value, minimum value, and average value characteristics of humidity. For electromagnetic interference characteristics, extract the intensity, frequency distribution, and duration characteristics of electromagnetic interference;

[0021] Integrate the relevant data of the extracted high-voltage resonant reactance experiment characteristics and environmental factor characteristics to obtain a comprehensive feature set.

[0022] Preferably, in the resonance state analysis module, the process of identifying data trends and analyzing the circuit resonance state includes:

[0023] Traverse the preprocessed high-voltage resonant reactance experiment data, extract the high-voltage resonant reactance experiment characteristics from the comprehensive feature set, and perform time series analysis on the inductance value, capacitance value, test frequency, and test voltage characteristics to identify the change trend over time, and apply the sliding window technique to analyze the local trends and patterns of the data;

[0024] Perform fast Fourier transform analysis on the voltage and current signals to determine the resonance peak in the frequency domain, calculate the power spectral density of the signal, and identify the frequency range where the energy is concentrated;

[0025] Calculate the theoretical resonance frequency of the circuit based on the values of the inductance and capacitance, analyze the phase difference between the voltage and current signals, combine with the experimental characteristics of the high-voltage resonance reactance, calculate the resonance state evaluation index, and quantitatively analyze the resonance state of the circuit;

[0026] Use the circuit theory model to fit the experimental data, calculate the circuit behavior evaluation index, verify the behavior of the circuit, identify and analyze the abnormal data points related to the resonance state, and determine whether the circuit is in the resonance state.

[0027] Preferably, the expression of the resonance state evaluation index is:

[0028]

[0029] where R is the resonance state evaluation index, n is the total number of frequency points measured in the experiment, f i is the frequency of the i-th measurement point in the experiment, f0 is the theoretical resonance frequency, L is the inductance measured in the experiment, C is the capacitance measured in the experiment, σ i is the standard deviation of the frequency of the i-th measurement point in the experiment, V φ is the phase difference between the voltage and the current, φ max is the maximum allowable phase difference, P peak is the peak value in the power spectral density, P ref is the peak value of the reference power spectral density, and the value range of R is from 0 to 1;

[0030] The expression of the circuit behavior evaluation index is:

[0031]

[0032] Δf = f i - f0;

[0033] where S is the circuit behavior evaluation index, n is the total number of frequency points measured in the experiment, G i is the power value of the i-th measurement point in the experiment, G0 is the power value predicted according to the circuit theory model, G ref is the reference power value, Z i is the impedance value of the i-th measurement point in the experiment, Z0 is the impedance value predicted according to the circuit theory model, Z ref is the reference impedance value, Δf is the deviation between the measured frequency and the theoretical resonance frequency, f ref is the reference frequency, and the value range of S is from 0 to 1.

[0034] Preferably, in the environmental interference analysis module, the process of obtaining the environmental interference evaluation index includes:

[0035] Extract the environmental factor characteristics related to the high-voltage resonant reactance experiment from the preprocessed external environmental factor data, and analyze the temperature change trend, humidity change trend, and electromagnetic interference intensity;

[0036] Set the reference values of the external environmental factors, compare the current environmental factor data with the reference values, calculate the environmental interference evaluation index, and quantify the interference degree of the external environmental factors on the experiment;

[0037] Preset the interference evaluation threshold, compare the environmental interference evaluation index with the interference evaluation threshold, comprehensively analyze the interference degree of the environmental factors on the experiment, and judge the severity of the interference degree.

[0038] Preferably, the expression of the environmental interference evaluation index is:

[0039]

[0040] where E is the environmental interference evaluation index, m is the total number of environmental factor measurement points in the experiment, T j is the temperature value of the j-th environmental factor measurement point in the experiment, T ref is the reference value of the temperature, T max is the maximum allowable temperature deviation, H j is the humidity value of the j-th environmental factor measurement point in the experiment, H ref is the reference value of the humidity, H max is the maximum allowable humidity deviation, I peak is the peak intensity of the electromagnetic interference, I ref is the reference value of the electromagnetic interference, and the value range of E is from 0 to 1.

[0041] Preferably, in the accuracy evaluation module, the process of accuracy analysis includes:

[0042] Combining the analysis results of the circuit resonance state and the interference evaluation results of the external environmental factors, obtain the resonance state evaluation index and the environmental interference evaluation index;

[0043] Draw the curve of the resonance state evaluation index changing with time, analyze its stability, volatility, and change trend in different time periods, and draw the curve of the environmental interference evaluation index changing with time, analyze the dynamic changes of the environmental factors and their potential impact on the circuit resonance state;

[0044] According to the experimental environmental conditions and the requirements of the high-voltage resonant reactance experiment, assign weights to the resonance state evaluation index and the environmental interference evaluation index, combine the circuit resonance state evaluation index, the environmental interference evaluation index and their weights, calculate the accuracy evaluation coefficient, and analyze the accuracy of the experimental results. A high accuracy evaluation coefficient indicates that the experimental data is stable and the results are reliable, while a low accuracy evaluation coefficient indicates that there may be uncertainties;

[0045] Based on the precision evaluation coefficient and its analysis results, different precision levels are set, namely the first-level precision level, the second-level precision level, the third-level precision level, and the fourth-level precision level. Among them, the precision level increases gradually in accuracy from the first level to the fourth level, and corresponding precision evaluation thresholds are set for each precision level.

[0046] Preferably, the expression of the precision evaluation coefficient is:

[0047]

[0048] where AP is the precision evaluation coefficient, R is the resonance state evaluation index, R ref is the reference value of the resonance state evaluation index, R max is the maximum allowable resonance state deviation, E is the environmental interference evaluation index, E ref is the reference value of the environmental interference evaluation index, E max is the maximum allowable environmental interference deviation, w1 and w2 are the weights of the resonance state evaluation index and the environmental interference evaluation index respectively, and the value range of AP is from 0 to 1;

[0049] Multiple said precision levels correspond to multiple said precision evaluation thresholds, where the precision evaluation thresholds include an upper threshold and a lower threshold;

[0050] Multiple said precision levels and multiple said precision evaluation thresholds satisfy the following relationship:

[0051] For the first-level precision level, AP H ≤AP<1;

[0052] For the second-level precision level, AP M ≤AP<AP H ;

[0053] For the third-level precision level, AP L ≤AP<AP M ;

[0054] For the fourth-level precision level, 0<AP<AP L ;

[0055] where AP is the precision evaluation coefficient, AP H is the lower threshold corresponding to the first-level precision level and the upper threshold corresponding to the second-level precision level, AP M is the lower threshold corresponding to the second-level precision level and the upper threshold corresponding to the third-level precision level, AP L is the lower threshold corresponding to the third-level precision level and the upper threshold corresponding to the fourth-level precision level, AP H =0.9, AP M =0.75, AP L =0.5.

[0056] Preferably, in the experimental optimization suggestion module, the process of providing suggestions for experimental design and optimization includes:

[0057] According to the calculated precision evaluation coefficient, analyze the precision level of the current experiment, and compare the precision evaluation coefficient with the preset precision level threshold to determine the precision level of the current experiment;

[0058] According to the precision evaluation result, analyze the experimental parameters and environmental factors that cause deviations in the experimental results, check the experimental parameters and experimental environmental factors, and put forward optimization suggestions for adjusting the experimental parameters and environmental factors to ensure matching with the experimental requirements;

[0059] According to the optimization suggestions, iteratively optimize the experimental scheme, adjust the experimental parameters and experimental environmental factors, and improve the accuracy and precision of the experimental results by implementing the optimization suggestions;

[0060] Conduct experimental verification under the optimized experimental conditions, collect data and re-evaluate the precision level of the experiment. According to the verification results, continuously adjust and optimize the experimental scheme until the expected precision requirements are met, and record the optimization suggestions and implementation results to generate an experimental report containing the optimization suggestions and expected effects.

[0061] The present invention provides an intelligent data optimization management system for high-voltage resonant reactance experiments. It has the following beneficial effects:

[0062] First, the intelligent data optimization management system for high-voltage resonant reactance experiments calculates the resonant state evaluation index through the resonant state analysis module to quantify the resonant state of the circuit, combines with the environmental interference evaluation module to evaluate the interference degree of external environmental factors on the experiment, and conducts comprehensive analysis through the precision evaluation module to predict the precision and accuracy of the experimental results, enabling experimenters to identify potential problems in advance and take measures to avoid or reduce the occurrence of related problems, thereby enhancing the predictability and stability of the experimental results.

[0063] Second, the intelligent data optimization management system for high-voltage resonant reactance experiments monitors various key parameters during the experiment by integrating sensor and data processing technologies, calculates the resonant state evaluation index and the environmental interference evaluation index, and then determines the precision level of the experiment. Through real-time monitoring and data analysis, it can promptly discover and correct deviations and errors in the experiment, significantly improving the precision and reliability of the experiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a module composition diagram of an intelligent data optimization management system for high-voltage resonant reactance experiments of the present invention;

[0065] Figure 2Flow chart for the present invention to identify data trends and analyze the resonant state of the circuit;

[0066] Figure 3 Flow chart for obtaining the environmental interference evaluation index of the present invention;

[0067] Figure 4 Flow chart for the accuracy analysis of the present invention. Detailed implementation manners

[0068] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners. The embodiments of the present invention are given for purposes of illustration and description, and are not exhaustive or limit the present invention to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are selected and described to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and design various embodiments with various modifications suitable for specific purposes.

[0069] The first embodiment is as Figures 1 to 3 shown. The present invention provides a technical solution: an intelligent data optimization management system for high-voltage resonant reactance experiments, including a data management center, which is communicatively connected to a data acquisition module, a data preprocessing module, a resonant state analysis module, an environmental interference analysis module, an accuracy evaluation module, and an experimental optimization suggestion module. Among them, the modules are electrically connected to each other;

[0070] The data acquisition module is used to collect the original data of various parameters during the high-voltage resonant reactance experiment, including the inductance value, capacitance value, test frequency, and test voltage of the reactor, and monitor the experimental environment to obtain the external environmental factor data of temperature, humidity, and electromagnetic interference, ensuring the accuracy and integrity of the data, providing a reliable basis for subsequent data processing and analysis. Deploy the measuring instruments for the high-voltage resonant reactance experiment, and install temperature sensors, humidity sensors, and electromagnetic interference detectors in the experimental environment to monitor the experimental environment. Use the deployed measuring instruments to collect the original data of the inductance value, capacitance value, test frequency, and test voltage of the reactor during the high-voltage resonant reactance experiment. Among them, the inductance value of the reactor is obtained through an inductance measuring instrument, and the inductance value of the reactor is measured and recorded in real time during the experiment. The capacitance value is measured and recorded in real time during the experiment using a capacitance measuring instrument. The test frequency during the experiment is recorded in real time through a frequency measuring instrument. The test voltage is measured and recorded in real time during the experiment using a high-voltage voltage measuring instrument. Use the installed temperature sensors, humidity sensors, and electromagnetic interference detectors to collect the external environmental factor data of the experimental environment. Use the temperature sensor to measure and record the temperature of the experimental environment during the experiment. Use the humidity sensor to measure and record the humidity of the experimental environment during the experiment. Use the electromagnetic interference measuring instrument to measure and record the electromagnetic interference level in real time during the experiment. Summarize the collected original data of the high-voltage resonant reactance experiment and the external environmental factor data, and perform data marking, record the experimental conditions and timestamps, and store them in the data warehouse for subsequent analysis;

[0071] A data preprocessing module for preprocessing the collected raw data and external environmental factor data, including cleaning, filtering, and calibration steps to remove noise and outliers, improve the quality of the data, standardize the data to make it comparable and consistent, extract high-voltage resonance reactance experiment features and environmental factor features, extract the collected raw data and external environmental factor data from the data warehouse, and perform preprocessing on them. The preprocessing operations include data cleaning, data filtering, and data calibration steps. Among them, through data cleaning, statistical methods (Z-score) are used to identify outliers and remove them from the dataset. For missing data points, interpolation methods are used to fill in the missing values according to the data distribution and experimental conditions. Digital filtering techniques are used to remove high-frequency noise in the data and retain useful signals, smooth the data to reduce fluctuations and uncertainties in the data, and improve the stability and reliability of the data. Through data calibration, consistency processing is performed on the data to ensure that data from different sensors and measurement devices are consistent in range, unit, and accuracy. Standardize the preprocessed raw data and external environmental factor data to eliminate the influence of dimensional differences between different data, and perform feature extraction on the preprocessed and standardized raw data and external environmental factor data. For the raw data during the high-voltage resonance reactance experiment process, extract high-voltage resonance reactance experiment features such as the inductor inductance value, capacitor value, test frequency, and test voltage. Among them, for the inductor inductance value, extract statistical features such as the change trend of the inductance value over time, average value, and standard deviation. For the capacitor value, extract statistical features such as the change trend of the capacitor value over time, average value, and standard deviation. For the test frequency, extract features such as frequency stability and fluctuation range. For the test voltage, extract features such as voltage peak value, average value, and waveform. For the external environmental factor data, extract environmental factor features such as temperature, humidity, and electromagnetic interference. Among them, for temperature, extract features such as the change trend of temperature, maximum value, minimum value, and average value. For humidity features, extract features such as the change trend of humidity, maximum value, minimum value, and average value. For electromagnetic interference features, extract features such as the intensity, frequency distribution, and duration of electromagnetic interference. Integrate the relevant data of the extracted high-voltage resonance reactance experiment features and environmental factor features to obtain a comprehensive feature set;

[0072] The resonance state analysis module uses data analysis techniques to analyze the preprocessed high-voltage resonance reactance experimental data and high-voltage resonance reactance experimental characteristics, identify data trends and analyze the resonance state of the circuit. It traverses the preprocessed high-voltage resonance reactance experimental data, extracts high-voltage resonance reactance experimental characteristics from the comprehensive feature set, and performs time series analysis on the inductance value, capacitance value, test frequency, and test voltage characteristics to identify the change trends over time. The sliding window technique is applied to analyze the local trends and patterns of the data. Fast Fourier transform analysis is performed on the voltage and current signals to determine the resonance peaks in the frequency domain, and the power spectral density of the signals is calculated to identify the frequency range where the energy is concentrated. The theoretical resonance frequency of the circuit is calculated based on the values of the inductance and capacitance, and the phase difference between the voltage and current signals is analyzed. Combining with the high-voltage resonance reactance experimental characteristics, a resonance state evaluation index is calculated to quantitatively analyze the resonance state of the circuit. A circuit theory model is used to fit the experimental data, and a circuit behavior evaluation index is calculated to verify the behavior of the circuit. Abnormal data points related to the resonance state are identified and analyzed to determine whether the circuit is in a resonance state;

[0073] Furthermore, the expression of the resonance state evaluation index is:

[0074]

[0075] where R is the resonance state evaluation index, n is the total number of frequency points measured in the experiment, f i is the frequency of the i-th measurement point in the experiment, f0 is the theoretical resonance frequency, L is the inductance measured in the experiment, C is the capacitance measured in the experiment, σ i is the standard deviation of the frequency of the i-th measurement point in the experiment, V φ is the phase difference between the voltage and current, φ max is the maximum allowable phase difference, P peak is the peak value in the power spectral density, P ref is the reference power spectral density peak value. The value range of R is from 0 to 1. When all measured values meet the ideal conditions, the value of R is 1, indicating that the circuit is in a perfect resonance state. As the measured values deviate from the ideal conditions, the value of R will decrease. When approaching 0, it indicates that the circuit is far from the resonance state. When f i approaches f0, |ln(f i -f0)| decreases, making the entire denominator decrease, thus R increases. When |V φ | is small, decreases, making the entire denominator decrease, thus R increases. When P peak approaches P ref , decreases, making the entire denominator decrease, thus R increases. The resonance state of the circuit is evaluated by comprehensively considering the deviations of the resonance frequency, phase difference, and power spectral density peak value;

[0076] The expression for the circuit behavior evaluation index is:

[0077]

[0078] Δf = f i - f0;

[0079] where S is the circuit behavior evaluation index, n is the total number of frequency points measured in the experiment, G i is the power value at the i-th measurement point in the experiment, G0 is the power value predicted according to the circuit theory model, G ref is the reference power value, Z i is the impedance value at the i-th measurement point in the experiment, Z0 is the impedance value predicted according to the circuit theory model, Z ref is the reference impedance value, Δf is the deviation between the measured frequency and the theoretical resonance frequency, f ref is the reference frequency. The value range of S is from 0 to 1. When all measured values conform to the theoretical prediction, the value of S is 1, indicating that the circuit behavior is completely consistent with the theoretical model. As the measured values deviate from the theoretical prediction, the value of S will decrease. When it is close to 0, it indicates that there is a significant deviation between the circuit behavior and the theoretical model. When |G i - G0| is small, the summation term decreases, making the entire denominator decrease, and thus S increases. When is small, the radical term decreases, making the entire denominator decrease, and thus S increases. When |Δf| is small, the exponential term decreases, making the entire denominator decrease, and thus S increases;

[0080] The environmental interference analysis module combines the preprocessed external environmental factor data and environmental factor characteristics to calculate the environmental interference evaluation index, compares it with the reference value of the external environmental factors, evaluates the interference degree of the external environmental factors on the high-voltage resonant reactance experiment, extracts the environmental factor characteristics related to the high-voltage resonant reactance experiment from the preprocessed external environmental factor data, analyzes the temperature change trend, humidity change trend and electromagnetic interference intensity, sets the reference value of the external environmental factors, compares the current environmental factor data with the reference value, calculates the environmental interference evaluation index, quantifies the interference degree of the external environmental factors on the experiment. Among them, according to the ideal experimental conditions, the optimal temperature range in the experiment is set as the reference value of the temperature, the optimal humidity level in the experiment is set as the reference value of the humidity, and the electromagnetic interference reference value is the allowable value of the ideal experimental conditions. A preset interference evaluation threshold is set, the environmental interference evaluation index is compared with the interference evaluation threshold, and the interference degree of the environmental factors on the experiment is comprehensively analyzed to judge the severity of the interference degree;

[0081] Furthermore, the expression for the environmental interference evaluation index is:

[0082]

[0083] Among them, E is the environmental interference evaluation index, m is the total number of environmental factor measurement points in the experiment, T j is the temperature value of the j-th environmental factor measurement point in the experiment, T ref is the reference value of the temperature, T max is the maximum allowable temperature deviation, H j is the humidity value of the j-th environmental factor measurement point in the experiment, H ref is the reference value of the humidity, H max is the maximum allowable humidity deviation, I peak is the peak intensity of the electromagnetic interference, I ref is the reference value of the electromagnetic interference. The value range of E is from 0 to 1. When all measured values meet the reference value, the value of E is 1, indicating that the environmental factors have no interference on the experiment. As the measured values deviate from the reference value, the value of E will decrease. When it is close to 0, it indicates that the environmental factors have significant interference on the experiment;

[0084] The precision evaluation module combines the analysis results of the circuit resonance state and the interference evaluation results of external environmental factors to conduct precision analysis, evaluate the data change law of the high-voltage resonance reactance experiment, predict the accuracy of the experimental results, and provide a more comprehensive perspective for the accurate evaluation and prediction of the experimental results;

[0085] The experimental optimization suggestion module determines the precision level of the high-voltage resonance reactance experiment based on the precision evaluation results of the high-voltage resonance reactance experiment, and provides suggestions for experimental design and optimization, adjusts experimental parameters and conditions, and optimizes the experimental scheme to improve the accuracy and reliability of the experimental results.

[0086] The second embodiment, on the basis of the first embodiment, please refer to Figure 4 As shown, in the precision evaluation module, the process of precision analysis includes:

[0087] Combining the analysis results of the circuit resonance state and the interference evaluation results of external environmental factors, obtain the resonance state evaluation index and the environmental interference evaluation index, draw the curve of the resonance state evaluation index changing with time, analyze its stability, volatility and change trend in different time periods, and draw the curve of the environmental interference evaluation index changing with time, analyze the dynamic changes of environmental factors and their potential impact on the circuit resonance state, assign weights to the resonance state evaluation index and the environmental interference evaluation index according to the experimental environmental conditions and the requirements of the high-voltage resonance reactance experiment, combine the circuit resonance state evaluation index, the environmental interference evaluation index and their weights, calculate the precision evaluation coefficient, analyze the precision of the experimental results. A high precision evaluation coefficient indicates that the experimental data is stable and the results are reliable, while a low precision evaluation coefficient indicates that there may be uncertainties. Based on the precision evaluation coefficient and its analysis results, set different precision levels, namely the first-level precision level, the second-level precision level, the third-level precision level and the fourth-level precision level. Among them, the accuracy increases gradually from the first level to the fourth level, and set corresponding precision evaluation thresholds for each precision level;

[0088] Furthermore, the expression of the precision evaluation coefficient is:

[0089]

[0090] where, AP is the precision evaluation coefficient, R is the resonance state evaluation index, R ref is the reference value of the resonance state evaluation index, R max is the maximum allowable resonance state deviation, E is the environmental interference evaluation index, E ref is the reference value of the environmental interference evaluation index, E max is the maximum allowable environmental interference deviation, w1 and w2 are the weights of the resonance state evaluation index and the environmental interference evaluation index respectively. The value range of AP is from 0 to 1. When both R and E are equal to their reference values, the value of AP is 1, indicating that the experimental results are very accurate. As R and E deviate from their reference values, the value of AP will decrease. Approaching 0 indicates that the experimental results are inaccurate. When |R - R ref | is small, the radical term decreases, making the whole denominator decrease, thus AP increases. When |E - E ref | is small, the exponential term decreases, making the whole denominator decrease, thus AP increases;

[0091] Multiple precision levels correspond to multiple precision evaluation thresholds. Among them, the precision evaluation thresholds include upper thresholds and lower thresholds;

[0092] The multiple precision levels and the multiple precision evaluation thresholds satisfy the following relationship:

[0093] The first-level precision level AP H≤AP < 1; Highest accuracy, the experimental results are very precise, and both the resonance state and environmental interference are within the optimal range;

[0094] Secondary accuracy level AP M ≤AP < AP H ; High accuracy, the experimental results are relatively precise, and there may be minor deviations;

[0095] Tertiary accuracy level AP L ≤AP < AP M ; Medium accuracy, the experimental results are average, and there may be some deviations, but the results are still usable;

[0096] Quaternary accuracy level 0 < AP < AP L ; Low accuracy, there may be large deviations in the experimental results, and further verification or adjustment is required;

[0097] where AP is the accuracy evaluation coefficient, AP H is the lower threshold corresponding to the primary accuracy level and the upper threshold corresponding to the secondary accuracy level, AP M is the lower threshold corresponding to the secondary accuracy level and the upper threshold corresponding to the tertiary accuracy level, AP L is the lower threshold corresponding to the tertiary accuracy level and the upper threshold corresponding to the quaternary accuracy level, AP H = 0.9, AP M = 0.75, AP L = 0.5;

[0098] In the experimental optimization suggestion module, the process of providing suggestions for experimental design and optimization includes:

[0099] According to the calculated accuracy evaluation coefficient, analyze the accuracy level of the current experiment, compare the accuracy evaluation coefficient with the preset accuracy level thresholds to determine the accuracy level of the current experiment, based on the accuracy evaluation results, analyze the experimental parameters and environmental factors that cause deviations in the experimental results, check the experimental parameters and experimental environmental factors, propose optimization suggestions for adjusting the experimental parameters and environmental factors to ensure matching with the experimental requirements, according to the optimization suggestions, iteratively optimize the experimental scheme, adjust the experimental parameters and experimental environmental factors, and by implementing the optimization suggestions, improve the accuracy and precision of the experimental results, conduct experimental verification under the optimized experimental conditions, collect data and re-evaluate the accuracy level of the experiment, according to the verification results, continuously adjust and optimize the experimental scheme until the expected accuracy requirements are met, and record the optimization suggestions and implementation results, generate an experimental report containing the optimization suggestions and expected effects.

[0100] Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art and related fields based on the embodiments in the present invention without creative efforts shall fall within the scope of protection of the present invention. Structures, devices, and operation methods not specifically described and explained in the present invention shall be implemented by conventional means in the art unless otherwise specified and limited.

Claims

1. An intelligent data optimization management system for high-voltage resonant reactance experiments, comprising a data management center, characterized in that: The data management center is communicatively connected with a data acquisition module, a data preprocessing module, a resonance state analysis module, an environmental interference analysis module, an accuracy assessment module and an experiment optimization suggestion module, wherein electrical signals are connected between the modules; The data acquisition module is used to collect the original data of various parameters during the high-voltage resonant reactance experiment, monitor the experimental environment, and obtain external environmental factor data; The data preprocessing module is used to preprocess the collected raw data and external environmental factor data, extract the high-voltage resonant reactance experimental characteristics and environmental factor characteristics, and integrate the relevant data of the extracted high-voltage resonant reactance experimental characteristics and environmental factor characteristics to obtain a comprehensive feature set; The resonant state analysis module analyzes the preprocessed high-voltage resonant reactance experimental data and the high-voltage resonant reactance experimental characteristics, identifies the data trend and analyzes the resonant state of the circuit. In the resonant state analysis module, the process of identifying the data trend and analyzing the resonant state of the circuit includes: Traverse the preprocessed high-voltage resonant reactance test data, extract the high-voltage resonant reactance test features from the comprehensive feature set, and perform time series analysis on the inductance value, capacitance value, test frequency and test voltage features to identify the change trend over time; Perform fast Fourier transform analysis on voltage and current signals to determine the resonance peak in the frequency domain, and calculate the power spectrum density of the signal to identify the frequency range where the energy is concentrated; The theoretical resonant frequency of the circuit is calculated based on the values ​​of inductance and capacitance, and the phase difference between the voltage and current signals is analyzed. Combined with the experimental characteristics of high-voltage resonant reactance, the resonance state evaluation index is calculated to quantitatively analyze the resonant state of the circuit. Use circuit theory models to fit experimental data, calculate circuit behavior evaluation indexes, verify circuit behavior, identify and analyze abnormal data points related to the resonant state, and determine whether the circuit is in a resonant state; The environmental interference analysis module calculates the environmental interference evaluation index by combining the pre-processed external environmental factor data and the environmental factor characteristics, compares the baseline value of the external environmental factor, and evaluates the interference degree of the external environmental factor on the high-voltage resonant reactance experiment; The accuracy assessment module combines the analysis results of the circuit resonance state and the interference assessment results of external environmental factors to perform accuracy analysis and assess the data change law of the high-voltage resonance reactance experiment; The experiment optimization suggestion module determines the accuracy level of the high-voltage resonant reactance experiment based on the accuracy evaluation result of the high-voltage resonant reactance experiment, and provides suggestions for experimental design and optimization.

2. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 1, characterized in that: In the data acquisition module, the process of acquiring the original data of the high-voltage resonant reactance experimental parameters and the external environmental factor data includes: Deploy measurement instruments for high-voltage resonant reactance experiments, and place temperature sensors, humidity sensors, and electromagnetic interference detectors in the experimental environment to monitor the experimental environment; Use the deployed measuring instruments to collect the original data of the inductance, capacitance, test frequency and test voltage of the reactor during the high-voltage resonant reactance experiment; The temperature sensors, humidity sensors and electromagnetic interference detectors are used to collect data on external environmental factors of the experimental environment. The temperature sensors are used to measure and record the temperature of the experimental environment during the experiment. The humidity sensors are used to measure and record the humidity of the experimental environment during the experiment. The electromagnetic interference measuring instruments are used to measure and record the electromagnetic interference level in real time during the experiment. The collected raw data of high-voltage resonant reactance experiments and external environmental factor data are summarized, and the data are marked, and the experimental conditions and timestamps are recorded and stored in the data warehouse.

3. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 2, characterized in that: In the data preprocessing module, the process of extracting the high-voltage resonant reactance experimental characteristics and environmental factor characteristics includes: Extract the collected raw data and external environmental factor data from the data warehouse and preprocess them. The preprocessing operation includes data cleaning, data filtering and data calibration steps; Standardize the preprocessed raw data and external environmental factor data to eliminate the impact of dimensional differences between different data, and extract features from the preprocessed and standardized raw data and external environmental factor data; For the raw data of the high-voltage resonant reactance test process, extract the high-voltage resonant reactance test characteristics of the reactor inductance value, capacitance value, test frequency and test voltage. For the reactor inductance value, extract the change trend, average value and standard deviation statistical characteristics of the inductance value over time; for the capacitance value, extract the change trend, average value and standard deviation statistical characteristics of the capacitance value over time; for the test frequency, extract the frequency stability and fluctuation range characteristics; for the test voltage, extract the voltage peak value, average value and waveform characteristics; For external environmental factor data, the environmental factor characteristics of temperature, humidity and electromagnetic interference are extracted. For temperature, the temperature change trend, maximum value, minimum value and average value characteristics are extracted. For humidity characteristics, the humidity change trend, maximum value, minimum value and average value characteristics are extracted. For electromagnetic interference characteristics, the intensity, frequency distribution and duration characteristics of electromagnetic interference are extracted.

4. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 1, characterized in that: The expression of the resonance state evaluation index is: ； ； in, is the resonance state evaluation index, is the total number of frequency points measured in the experiment, For the experiment The frequency of the measurement points, is the theoretical resonant frequency, is the inductance measured in the experiment, is the capacitance measured in the experiment, For the experiment The standard deviation of the frequencies of the measurement points, is the phase difference between voltage and current, is the maximum allowed phase difference, is the peak value in the power spectral density, is the reference power spectral density peak, The value range is from 0 to 1; The expression of the circuit behavior evaluation index is: ； ； in, is the circuit behavior evaluation index, is the total number of frequency points measured in the experiment, For the experiment The power value of each measurement point, is the power value predicted by the circuit theory model, is the reference power value, For the experiment The impedance value of each measuring point is is the impedance value predicted by the circuit theory model, is the reference impedance value, To measure the deviation of the frequency from the theoretical resonant frequency, is the reference frequency, The value range is 0 to 1.

5. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 4 is characterized in that: In the environmental interference analysis module, the process of obtaining the environmental interference assessment index includes: Extract the environmental factor characteristics related to the high-voltage resonant reactance experiment from the pre-processed external environmental factor data, and analyze the temperature change trend, humidity change trend and electromagnetic interference intensity; Set the baseline value of external environmental factors, compare the current environmental factor data with the baseline value, calculate the environmental interference assessment index, and quantify the degree of interference of external environmental factors on the experiment; Preset the interference assessment threshold, compare the environmental interference assessment index with the interference assessment threshold, comprehensively analyze the degree of interference of environmental factors on the experiment, and judge the severity of the interference.

6. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 5, characterized in that: The expression of the environmental interference assessment index is: ； in, is the environmental disturbance assessment index, is the total number of environmental factor measurement points in the experiment, For the experiment The temperature value of each environmental factor measurement point, is the reference value of temperature, is the maximum allowable temperature deviation, For the experiment The humidity value of each environmental factor measurement point, is the reference value of humidity, is the maximum allowable humidity deviation, is the peak intensity of electromagnetic interference, is the reference value of electromagnetic interference, The value range is 0 to 1.

7. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 6, characterized in that: In the accuracy assessment module, the accuracy analysis process includes: Combining the analysis results of the circuit resonance state and the interference evaluation results of the external environmental factors, a resonance state evaluation index and an environmental interference evaluation index are obtained; Draw a curve of the resonance state evaluation index changing over time, analyze its stability, volatility and change trend in different time periods, and draw a curve of the environmental interference evaluation index changing over time, analyze the dynamic changes of environmental factors and their potential impact on the circuit resonance state; According to the experimental environment conditions and the requirements of the high-voltage resonant reactance experiment, weights are assigned to the resonance state evaluation index and the environmental interference evaluation index. The accuracy evaluation coefficient is calculated by combining the circuit resonance state evaluation index and the environmental interference evaluation index and their weights, and the accuracy of the experimental results is analyzed. Based on the accuracy assessment coefficient and its analysis results, different accuracy levels are set, namely, level one accuracy level, level two accuracy level, level three accuracy level and level four accuracy level. The accuracy of the accuracy level increases step by step from level one to level four, and a corresponding accuracy assessment threshold is set for each accuracy level.

8. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 7, characterized in that: The expression of the accuracy evaluation coefficient is: ； in, is the accuracy evaluation coefficient, is the resonance state evaluation index, is the reference value of the resonance state evaluation index, is the maximum allowable resonant state deviation, is the environmental disturbance assessment index, is the benchmark value of the environmental interference assessment index, is the maximum permissible environmental disturbance deviation, and are the weights of the resonance state assessment index and the environmental interference assessment index, The value range is from 0 to 1; The plurality of accuracy levels correspond to the plurality of accuracy assessment thresholds, wherein the accuracy assessment thresholds include an upper threshold and a lower threshold; The multiple accuracy levels and the multiple accuracy assessment thresholds satisfy the following relationship: First level accuracy ; Second level accuracy ; Three levels of accuracy ; Four levels of accuracy ; in, is the accuracy evaluation coefficient, is the lower threshold corresponding to the first level of accuracy and the upper threshold corresponding to the second level of accuracy. is the lower threshold corresponding to the second level precision level and the upper threshold corresponding to the third level precision level. is the lower threshold corresponding to the third level of accuracy and the upper threshold corresponding to the fourth level of accuracy, , , .

9. The intelligent data optimization management system for high-voltage resonant reactance experiment according to claim 8, characterized in that: In the experiment optimization suggestion module, the process of providing suggestions for experiment design and optimization includes: Analyze the accuracy level of the current experiment based on the calculated accuracy evaluation coefficient, and compare the accuracy evaluation coefficient with the preset accuracy level threshold to determine the accuracy level of the current experiment; According to the accuracy evaluation results, analyze the experimental parameters and environmental factors that cause the experimental results to deviate, check the experimental parameters and environmental factors, and put forward optimization suggestions for adjusting the experimental parameters and environmental factors; According to the optimization suggestions, iteratively optimize the experimental plan and adjust the experimental parameters and experimental environment factors; Conduct experimental verification under optimized experimental conditions, collect data and re-evaluate the accuracy level of the experiment. Based on the verification results, continuously adjust and optimize the experimental plan until the expected accuracy requirements are met. Record the optimization suggestions and implementation results, and generate an experimental report containing optimization suggestions and expected effects.

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