SF6 gas monitoring data analysis system and method for sealed container

Abstract

The invention discloses an SF6 gas monitoring data analysis system and method for a sealed container, and belongs to the technical field of intelligent gas analysis, and the method specifically comprises the following steps: extracting an SF6 gas sample from the sealed container, introducing the SF6 gas sample into a gas decomposition product analyzer for concentration detection, and converting a detection result into a digital signal for display; the decomposition condition of the SF6 gas is analyzed by comparing the detection concentration with a standard value; based on a decomposition result, using an intelligent diagnosis strategy to identify an abnormal mode, and combining historical data and container operation conditions to construct a comprehensive performance evaluation model to judge the SF6 gas performance; if the performance is abnormal and the concentration of a decomposition product is higher than a threshold value, analyzing the SF6 gas quality by adopting an isotope tracking and chemometrics method; maintenance measures are formulated according to performance and quality analysis results, and the accuracy and efficiency of SF6 gas monitoring are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent gas analysis, and in particular to a SF6 gas monitoring data analysis system and method for sealed containers. Background Art

[0002] SF6 gas, or sulfur hexafluoride, is a colorless, odorless, non-toxic, non-flammable stable gas. SF6 gas has been widely used in power systems due to its excellent insulation and arc-extinguishing properties. However, with the increasing use of SF6 gas in electrical equipment, its safety and stability issues have become increasingly prominent. In order to ensure the normal operation of SF6 gas in sealed containers, real-time monitoring and data analysis are required. At present, most of the SF6 gas monitoring methods available on the market use sensor technology for data acquisition, but there are still deficiencies in data processing and analysis, and accurate early warning and fault diagnosis cannot be achieved.

[0003] For example, a Chinese patent with the authorization announcement number CN118152408B discloses a remote monitoring method and system based on digital intelligent gas analysis, including: based on the target position to be monitored, obtaining gas analysis data and storing it in the first storage space; when the gas analysis data to be stored in the first storage space changes, generating event information, and storing the gas analysis data and event information in the second storage space; according to the first timestamp corresponding to the remote monitoring instruction, calling the gas analysis data in the first storage space, performing data analysis according to the preset analysis conditions, and obtaining the first gas monitoring result; at the same time, based on the first timestamp, calling the gas analysis data in the second storage space, according to the same preset analysis conditions, obtaining the second gas monitoring result of the target position to be monitored, and verifying the first gas monitoring result. This technical solution provides a guarantee for the safe operation of the air separation unit.

[0004] The above existing technologies all have the following problems: the remote monitoring method is easily affected by fluctuations in network and communication technology, and there is a risk of attack in the transmission link; the data analysis capability is low. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention proposes a SF6 gas monitoring data analysis system and method for a sealed container, wherein an SF6 gas sample is extracted from the sealed container, introduced into a gas decomposition product analyzer for concentration detection, and the detection result is converted into a digital signal for display; the decomposition of the SF6 gas is analyzed by comparing the detected concentration with the standard value; based on the decomposition result, an intelligent diagnosis strategy is used to identify abnormal patterns, and a comprehensive performance evaluation model is constructed in combination with historical data and container operating conditions to judge the SF6 gas performance; if the performance is abnormal and the decomposition product concentration is higher than a threshold, the isotope tracking and chemometric methods are used to analyze the SF6 gas quality; maintenance measures are formulated based on the performance and quality analysis results, thereby improving the accuracy and efficiency of SF6 gas monitoring.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for analyzing SF6 gas monitoring data for a sealed container, comprising: Step S1: extracting a quantitative SF6 gas sample from a sealed container using a sampling tool; Step S2: introducing the SF6 gas sample into the gas decomposition product analyzer, the gas decomposition product analyzer automatically converts the decomposition product concentration into an analog electrical signal, converts the analog electrical signal into a digital signal through an integrated microprocessor and an A / D converter, and displays the actual value of the detected decomposition product concentration on an LCD; Step S3: Record the actual value of the decomposition product concentration displayed on the LCD, perform pretreatment, compare the detected concentration after pretreatment with the standard value, and analyze the decomposition of SF6 gas; Step S4: Based on the SF6 gas decomposition results, an intelligent diagnosis strategy is used to automatically identify abnormal patterns, and a comprehensive performance evaluation model is constructed based on the intelligent diagnosis results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; Step S5: If the comprehensive performance evaluation model determines that the SF6 gas performance is abnormal, and the concentration of the decomposition product is higher than the preset concentration abnormality threshold, the isotope tracking and chemometric method is used to analyze the SF6 gas quality; Step S6: Formulate maintenance measures based on the judgment results of SF6 gas performance and quality analysis results.

[0007] Specifically, the specific steps of analyzing the decomposition of SF6 gas in step S3 include: S3.1: By comparing the detected concentration after pretreatment With standard value , obtain the concentration ratio of each decomposition product after SF6 gas decomposition ,in, , , , Respectively represent the actual concentration values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, , , , Respectively represent the concentration standard values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, represents the actual value of the concentration of the i-th gas decomposition product, represents the correction factor for the i-th gas decomposition product, represents the concentration proportion of the i-th gas decomposition product; S3.2: Combine historical gas decomposition product concentration data and use a time series analysis model to analyze the changing trends of different decomposition product concentrations; S3.3: Set threshold values ​​for decomposition product concentrations , by analyzing the concentration proportion and change trend of decomposition products, it can be judged whether the decomposition of SF6 gas is complete; like , it means that the decomposition process is not thorough enough and there is incompletely decomposed SF6 gas or new decomposition products.

[0008] Specifically, the specific steps of step S4 include: S4.1: Acquisition and ; S4.2: Extract the characteristics of SF6 gas performance based on the concentration ratio of SF6 gas decomposition products and the thoroughness of the decomposition process. The characteristics of SF6 gas performance include the purity, stability and insulation performance of SF6 gas. The thoroughness index B of the decomposition process is: , It indicates the decomposition amount of SF6 gas, and Q indicates the sampling amount of SF6 gas; S4.3: Based on the detection concentration after pretreatment , using intelligent diagnostic strategies to automatically identify abnormal patterns in SF6 gas decomposition results; S4.4: Construct a comprehensive performance evaluation model based on the intelligent diagnosis results, historical data and container operating conditions, and judge the performance of the SF6 gas in the sealed container based on the comprehensive performance evaluation model.

[0009] Specifically, the specific steps of S4.3 include: S4.31: Collect sample data of SF6 gas decomposition products of known defect types, and use the sample data of SF6 gas decomposition products of known defect types to train the intelligent diagnosis strategy and establish a mapping relationship between characteristic gas concentration and defect type; S4.32: Acquisition , and Input into the trained intelligent diagnosis strategy, the trained intelligent diagnosis strategy is based on Automatically identify abnormal patterns of SF6 gas decomposition results and output the corresponding defect type or abnormality degree; S4.33: Verify the output defect type or abnormality level, and adjust and optimize the intelligent diagnosis strategy based on the verification results.

[0010] Specifically, the specific steps of S4.4 include: S4.41: Obtain the intelligent diagnosis results output by the intelligent diagnosis strategy in S4.3, and at the same time, collect historical SF6 gas data and container operating condition data, and integrate them to form comprehensive SF6 gas monitoring data; S4.42: Arrange and combine the SF6 gas comprehensive monitoring data to form a feature matrix, wherein rows in the feature matrix represent samples and columns represent features; S4.43: Calculate the covariance matrix from the feature matrix , and Perform eigenvalue decomposition , get the eigenvalues ​​and corresponding eigenvectors, where represents the eigenvalue diagonal matrix, and P represents the eigenvector matrix; S4.44: According to the size of the eigenvalue, select the eigenvectors corresponding to the first k eigenvalues ​​with higher cumulative contribution rates as the main features; S4.45: Project the SF6 gas comprehensive monitoring data onto the main features to obtain SF6 gas low-dimensional data; S4.46: Based on the SF6 gas low-dimensional data, the similarity between the SF6 gas low-dimensional data and the SF6 gas performance characteristics is calculated using the correlation analysis method; S4.47: Screen the SF6 gas low-dimensional data according to the similarity calculation result to obtain the SF6 gas performance characteristics; S4.48: Load a pre-built support vector machine model, train the pre-built support vector machine model using the extracted SF6 gas performance characteristics, and generate a comprehensive performance evaluation model; S4.49: Input the data of the SF6 gas in the sealed container to be evaluated into the comprehensive performance evaluation model, obtain the prediction results of the comprehensive performance evaluation model, and judge the performance of the SF6 gas based on the prediction results.

[0011] Specifically, the specific steps of step S5 include: S5.1: Obtain the judgment result Z of the comprehensive performance evaluation model and set the concentration abnormality threshold ; like , it is judged that the performance of SF6 gas is normal; like , it is judged that the SF6 gas performance is abnormal; S5.2: When judging that the performance of SF6 gas is abnormal; like , it is judged that the performance of SF6 gas is normal; like , perform the following steps: A1: Heavy oxygen water Inject into the SF6 gas sample and mix evenly to obtain an isotope-traced gas sample; A2: Chemical analysis of isotope-traced gas samples to determine their purity, water content, and degree of oxidation. Electrochemical sensors are used to detect the decomposition products of SF6 gas and calculate their concentrations. A3: Organize and process the data obtained from chemical analysis and electrochemical sensors, calculate the mass loss and performance change of SF6 gas, and evaluate the performance and quality of SF6 gas based on the mass loss and performance change results.

[0012] Specifically, the gas decomposition products in step S2 include SO2, H2S, SOF2, and SO2F2.

[0013] A SF6 gas monitoring data analysis system for sealed containers, comprising: a sampling module, an analysis module, a data processing module, a performance evaluation module, and a maintenance measure formulation module; The sampling module is used to extract a quantitative SF6 gas sample from the sealed container; The analysis module is used to introduce the SF6 gas sample into the gas decomposition product analyzer to detect and analyze the concentration of the decomposition products; The data processing module is used to record the actual value of the decomposition product concentration displayed by the LCD, and perform preprocessing and comparative analysis; The performance evaluation module is used to construct a comprehensive performance evaluation model based on the SF6 gas decomposition results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; The maintenance measure formulation module formulates corresponding maintenance measures based on the judgment results of SF6 gas performance and the quality analysis results.

[0014] Specifically, the data processing module includes: a recording unit, a preprocessing unit, and a comparison and analysis unit; The recording unit is used to record the actual value of the detected decomposition product concentration; The preprocessing unit is used to preprocess the recorded actual value of the decomposition product concentration; The comparison and analysis unit is used to compare the actual value of the detected concentration after pretreatment with the standard value to analyze the decomposition of SF6 gas.

[0015] Specifically, the performance evaluation module includes: a model building unit, a performance judgment unit, and a quality analysis unit; The model building unit is used to build a comprehensive performance evaluation model using historical data and container operating conditions; The performance judgment unit is used to judge the performance of SF6 gas according to the model; The mass analysis unit is used to determine the concentration of decomposition products and, based on the determination result, analyze the quality of SF6 gas using isotope tracking and chemometric methods.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a SF6 gas monitoring data analysis method for a sealed container. By integrating advanced sampling, detection and intelligent diagnosis technologies, the method realizes accurate monitoring of the SF6 gas state in the sealed container. It can not only acquire and process the data of the concentration of SF6 gas decomposition products in real time, but also automatically identify abnormal modes using intelligent diagnosis strategies, and build a comprehensive performance evaluation model in combination with historical data and operating conditions, so that operators can discover potential problems in time, ensure the safe and stable operation of power equipment, and effectively prevent failures caused by gas quality degradation.

[0017] The present invention proposes a SF6 gas monitoring data analysis method for sealed containers. When abnormal SF6 gas performance is detected, isotope tracking and chemometric methods are used to deeply analyze the gas quality, further enhancing the accuracy and depth of fault diagnosis, which not only helps to extend the service life of the equipment, but also improves maintenance efficiency and reduces unnecessary downtime, thereby improving the safety of the overall operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of a SF6 gas monitoring data analysis method for a sealed container according to the present invention; Figure 2 This is a principle flow chart of a method for analyzing SF6 gas monitoring data for a sealed container according to the present invention; Figure 3 This is an architecture diagram of an SF6 gas monitoring data analysis system for a sealed container according to the present invention. DETAILED DESCRIPTION

[0019] See also Figure 1 and Figure 2 The present invention provides an embodiment: a method for analyzing SF6 gas monitoring data for a sealed container, comprising the following steps: Step S1: extracting a quantitative SF6 gas sample from a sealed container using a sampling tool; The sampling volume calculation formula is: , Q represents the sampling volume of SF6 gas, v represents the extraction speed of the sampling tool, and t represents the sampling time.

[0020] Furthermore, the specific steps of step S1 include: (1) Prepare sampling tools and check the sealing of the sampling tools to ensure that there will be no gas leakage during the sampling process. The sampling tools include air pumps, sampling needles, and sampling bottles; (2) Connect the sampling tool to the sealed container and ensure that the connection is tight and leak-free; (3) According to the amount of SF6 gas sample to be extracted, set the extraction speed and extraction time parameters of the sampling tool to ensure that the sampling parameters meet safety specifications and standards; (4) Start the sampling tool and begin to extract SF6 gas samples from the sealed container. During the sampling process, pay close attention to the working status of the sampling tool and the pressure changes in the sealed container; (5) When the preset sampling volume or time is reached, stop the sampling tool, remove the sampling bottle from the sampling tool, and seal it to prevent gas leakage; (6) Record the sampling time, sampling volume, and sealed container number.

[0021] Step S2: introducing the SF6 gas sample into the gas decomposition product analyzer, the gas decomposition product analyzer automatically converts the decomposition product concentration into an analog electrical signal, converts the analog electrical signal into a digital signal through an integrated microprocessor and an A / D converter, and displays the actual value of the detected decomposition product concentration on an LCD; Furthermore, the specific steps of step S2 include: (1) Ensure that the gas decomposition product analyzer is in normal working condition and has been preheated to a stable state. Connect the SF6 gas sample to the gas inlet of the gas decomposition product analyzer through the gas duct; (2) Open the gas inlet valve of the analyzer to allow the SF6 gas sample to slowly enter the analyzer. At the same time, ensure that the gas flow rate is moderate to avoid damage to the analyzer or affect the detection accuracy; (3) The sensors inside the gas decomposition product analyzer automatically detect the concentration of decomposition products in SF6 gas, such as SO2, H2S, SOF2, and SO2F2, and convert the detected decomposition product concentrations into corresponding analog electrical signals. These analog electrical signals are then preliminarily processed by an integrated microprocessor and converted into digital signals by an A / D converter; (4) The converted digital signal is sent to the LCD display to show the actual value of the detected decomposition product concentration. The operator can observe the readings on the LCD display and record these data for subsequent analysis.

[0022] Step S3: Record the actual value of the decomposition product concentration displayed on the LCD, perform pretreatment, compare the detected concentration after pretreatment with the standard value, and analyze the decomposition of SF6 gas; Furthermore, the specific steps of step S3 include: (1) Observe the LCD display and record the actual concentration of SF6 gas decomposition products; (2) Verify the recorded concentration data and eliminate abnormal values ​​or erroneous data; (3) Set the concentration standard value according to the normal decomposition product concentration range of SF6 gas or the standard value provided by the equipment manufacturer; (4) Compare the actual value of the detected concentration after pretreatment with the set standard value, analyze the concentration difference, and determine whether it exceeds the normal range or exists abnormality; (5) Based on the comparison results, analyze the decomposition of SF6 gas. If abnormal decomposition product concentration is found, further investigation is required to find the cause, such as equipment failure or improper operation.

[0023] Step S4: Based on the SF6 gas decomposition results, an intelligent diagnosis strategy is used to automatically identify abnormal patterns, and a comprehensive performance evaluation model is constructed based on the intelligent diagnosis results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; Step S5: If the comprehensive performance evaluation model determines that the SF6 gas performance is abnormal, and the concentration of the decomposition product is higher than the preset concentration abnormality threshold, the isotope tracking and chemometric method is used to analyze the SF6 gas quality; Step S6: Formulate maintenance measures based on the judgment results of SF6 gas performance and quality analysis results.

[0024] Among them, maintenance measures include: 1) Gas replacement or supplementation: If the performance or quality of SF6 gas does not meet the requirements, it is necessary to replace new SF6 gas or supplement an appropriate amount of SF6 gas to maintain the gas performance and stability in the sealed container; 2) Sealed container maintenance: If the abnormal performance of SF6 gas is caused by the decline in the sealing performance of the sealed container or the existence of leakage and other problems, it is necessary to inspect the sealed container, repair the leakage point, and improve the sealing performance; 3) Adjust the operating conditions: According to the performance and quality analysis results of SF6 gas, it is necessary to adjust the operating conditions of the sealed container, such as temperature, pressure, etc., to optimize the performance and service life of SF6 gas; 4) Strengthen monitoring and data analysis: For abnormal conditions in the performance or quality of SF6 gas, it is necessary to strengthen its monitoring and data analysis, timely discover potential problems and take corresponding measures to solve them.

[0025] The specific steps of analyzing the decomposition of SF6 gas in step S3 include: S3.1: By comparing the detected concentration after pretreatment With standard value , obtain the concentration ratio of each decomposition product after SF6 gas decomposition ,in, , , , Respectively represent the actual concentration values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, , , , Respectively represent the concentration standard values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, represents the actual value of the concentration of the i-th gas decomposition product, represents the correction factor for the i-th gas decomposition product, represents the concentration proportion of the i-th gas decomposition product; S3.2: Combine historical gas decomposition product concentration data and use a time series analysis model to analyze the changing trends of different decomposition product concentrations; Furthermore, the specific steps of S3.2 include: (1) Collect and organize the historical concentration data of SF6 gas decomposition products, and pre-process and clean the historical concentration data; (2) loading a pre-built time series analysis model, and using the pre-processed historical concentration data to estimate the parameters of the pre-built time series analysis model according to data characteristics and analysis requirements, to obtain a trained time series analysis model, wherein the time series analysis model is a prior art content in the art and is not an inventive solution of the present application, and is not described in detail herein; (3) Use Perform trend analysis on the trained time series analysis model to predict the changing trends of the concentrations of different decomposition products.

[0026] S3.3: Set threshold values ​​for decomposition product concentrations , by analyzing the concentration proportion and change trend of decomposition products, it can be judged whether the decomposition of SF6 gas is complete; like , it means that the decomposition process is not thorough enough and there is incompletely decomposed SF6 gas or new decomposition products.

[0027] The specific steps of step S4 include: S4.1: Acquisition and ; S4.2: Extract the characteristics of SF6 gas performance based on the concentration ratio of SF6 gas decomposition products and the thoroughness of the decomposition process. The characteristics of SF6 gas performance include the purity, stability and insulation performance of SF6 gas. The thoroughness index B of the decomposition process is: , It indicates the decomposition amount of SF6 gas, and Q indicates the sampling amount of SF6 gas; Furthermore, the performance characteristics of SF6 gas are extracted including: (1) Purity characteristics: The purity of SF6 gas is evaluated based on the content of impurities in the decomposition products, such as oxygen, moisture, and other fluorides. The higher the purity, the less impurities in the SF6 gas and the more stable the performance. (2) Stability characteristics: Analyze whether the gas decomposition products contain unstable compounds and the concentration change trend of these compounds. If the content of unstable compounds in the gas decomposition products is low and the change trend is stable, it indicates that SF6 gas has good stability; (3) Insulation performance characteristics: The insulation performance of SF6 gas is evaluated by combining the compounds in the gas decomposition products that may affect the insulation performance, such as the concentration of SO2. The lower the concentration of the compound, the better the insulation performance of SF6 gas.

[0028] S4.3: Based on the detection concentration after pretreatment , using intelligent diagnostic strategies to automatically identify abnormal patterns in SF6 gas decomposition results; S4.4: Construct a comprehensive performance evaluation model based on the intelligent diagnosis results, historical data and container operating conditions, and judge the performance of the SF6 gas in the sealed container based on the comprehensive performance evaluation model.

[0029] The specific steps of S4.3 include: S4.31: Collect sample data of SF6 gas decomposition products of known defect types, and use the sample data of SF6 gas decomposition products of known defect types to train the intelligent diagnosis strategy and establish a mapping relationship between characteristic gas concentration and defect type; In the present invention, the intelligent diagnosis strategy uses a support vector machine model. The support vector machine model is a prior art in this field and is not an inventive solution of the present application, so it will not be described in detail here.

[0030] Among them, the sample data of SF6 gas decomposition products of known defect types refer to the data of SF6 gas decomposition products collected in the laboratory or actual operating environment, where the corresponding electrical equipment defect types are clearly known. These data usually include information such as the type and concentration of characteristic gases, and are the basis for training intelligent diagnostic strategies and identifying abnormal patterns.

[0031] In the prior art, known defect types and their corresponding SF6 gas decomposition product characteristics include: (1) Partial discharge defect: Partial discharge may cause SF6 gas to decompose and produce SO2, HF, H2S and other gases. The concentration changes of these gases can reflect the severity and trend of partial discharge; (2) Overheating defect: When overheating occurs inside electrical equipment, SF6 gas may decompose to produce CO, CO2 and other gases. The concentration changes of these gases can reflect the existence and degree of overheating. (3) Aging or moisture of insulating materials: Aging or moisture of insulating materials may cause SF6 gas to decompose and produce gases such as CF4. The concentration changes of these gases can reflect the health status of the insulating materials; (4) Internal pollution of equipment: Pollution inside the equipment may cause SF6 gas to decompose and produce various impurity gases, such as moisture and oxygen. The changes in the content of these impurities can reflect the cleanliness of the equipment. (5) Arc discharge defects: Arc discharge may cause SF6 gas to decompose and produce a large amount of low-fluorine sulfides such as SF4 and SF2. These compounds may recombine into SF6 under the action of the arc, but may also produce other toxic and harmful decomposition products, such as SO2F2 and SOF2.

[0032] S4.32: Acquisition , and Input into the trained intelligent diagnosis strategy, the trained intelligent diagnosis strategy is based on Automatically identify abnormal patterns of SF6 gas decomposition results and output the corresponding defect type or abnormality degree; S4.33: Verify the output defect type or abnormality level, and adjust and optimize the intelligent diagnosis strategy based on the verification results.

[0033] The specific steps of S4.4 include: S4.41: Obtain the intelligent diagnosis results output by the intelligent diagnosis strategy in S4.3, and at the same time, collect historical SF6 gas data and container operating condition data, and integrate them to form comprehensive SF6 gas monitoring data; S4.42: Arrange and combine the SF6 gas comprehensive monitoring data to form a feature matrix, wherein rows in the feature matrix represent samples and columns represent features; S4.43: Calculate the covariance matrix from the feature matrix , and Perform eigenvalue decomposition , get the eigenvalues ​​and corresponding eigenvectors, where represents the eigenvalue diagonal matrix, and P represents the eigenvector matrix; S4.44: According to the size of the eigenvalue, select the eigenvectors corresponding to the first k eigenvalues ​​with higher cumulative contribution rates as the main features; S4.45: Project the SF6 gas comprehensive monitoring data onto the main features to obtain SF6 gas low-dimensional data; S4.46: Based on the SF6 gas low-dimensional data, a correlation analysis method is used to calculate the similarity between the SF6 gas low-dimensional data and the SF6 gas performance characteristics, wherein the correlation analysis method or the similarity calculation formula is the prior art content in this field, and is not an inventive solution of the present application, and is not described in detail here; S4.47: Screen the SF6 gas low-dimensional data according to the similarity calculation result to obtain the SF6 gas performance characteristics; S4.48: Load a pre-built support vector machine model, and use the extracted SF6 gas performance characteristics to train the pre-built support vector machine model to generate a comprehensive performance evaluation model, wherein the support vector machine model is a prior art content in this field, is not an inventive solution of the present application, and is not described in detail here; S4.49: Input the data of the SF6 gas in the sealed container to be evaluated into the comprehensive performance evaluation model, obtain the prediction results of the comprehensive performance evaluation model, and judge the performance of the SF6 gas based on the prediction results.

[0034] The specific steps of step S5 include: S5.1: Obtain the judgment result Z of the comprehensive performance evaluation model and set the concentration abnormality threshold ; like , it is judged that the performance of SF6 gas is normal; like , it is judged that the SF6 gas performance is abnormal; S5.2: When judging that the performance of SF6 gas is abnormal; like , it is judged that the performance of SF6 gas is normal; like , perform the following steps: A1: Heavy oxygen water Inject into the SF6 gas sample and mix evenly to obtain an isotope-traced gas sample; A2: Chemical analysis of isotope-traced gas samples to determine their purity, water content, and degree of oxidation. Electrochemical sensors are used to detect the decomposition products of SF6 gas and calculate their concentrations. Furthermore, the specific implementation steps of A2 include: (1) Inject heavy oxygen water into the SF6 gas sample and mix it evenly to obtain a gas sample that has been traced by isotopes; (2) Using chromatography to measure the purity, water content and oxidation degree of the isotope-traced gas sample, and using an electrochemical gas sensor to detect the decomposition products of SF6 gas, such as SO2, H2S, SOF2, and SO2F2. The chromatography is a prior art in this field and is not an inventive solution of the present application, so it will not be described in detail here. (3) Calculate the concentration of decomposition products based on the output signal of the electrochemical sensor.

[0035] A3: Organize and process the data obtained from chemical analysis and electrochemical sensors, calculate the mass loss and performance change of SF6 gas, and evaluate the performance and quality of SF6 gas based on the mass loss and performance change results.

[0036] Furthermore, the specific implementation steps of A3 include: Collect and record the concentration data of decomposition products obtained by chemical analysis and electrochemical sensors, including information such as the purity, water content, degree of oxidation of SF6 gas, and concentration of decomposition products; Arrange and process the collected concentration data of decomposition products, remove outliers and noise, ensure the accuracy and reliability of the data, and obtain processed data; Based on the processed data, the mass loss of SF6 gas is calculated by comparing the initial mass with the current mass; Evaluate the performance changes of SF6 gas, including changes in insulation performance and stability, based on the concentration and type of decomposition products; Based on the results of mass loss and performance change, the performance and quality of SF6 gas are comprehensively evaluated.

[0037] The gas decomposition products in step S2 include SO2, H2S, SOF2, and SO2F2.

[0038] See also Figure 3 Another embodiment provided by the present invention is a SF6 gas monitoring data analysis system for a sealed container, comprising: Sampling module, analysis module, data processing module, performance evaluation module, maintenance measures formulation module; Sampling module, used to extract quantitative SF6 gas samples from the sealed container; An analysis module is used to introduce SF6 gas samples into a gas decomposition product analyzer to detect and analyze the concentration of decomposition products; The data processing module is used to record the actual value of the decomposition product concentration displayed on the LCD and perform preprocessing and comparative analysis; The performance evaluation module is used to build a comprehensive performance evaluation model based on the SF6 gas decomposition results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; The maintenance measures formulation module formulates corresponding maintenance measures based on the judgment results of SF6 gas performance and quality analysis results.

[0039] The sampling module includes: a sampling tool unit and a quantitative control unit; Sampling tool unit, a tool used to actually extract the gas, including a gas pump, valves, and piping components to ensure that the required amount of SF6 gas can be extracted from a sealed container; The quantitative control unit is used to control the sampling volume to ensure that the amount of SF6 gas sample extracted each time is consistent.

[0040] The analysis module includes: an import unit, a signal conversion unit, and a display unit; An introduction unit, used to introduce SF6 gas samples into the analyzer, including connecting pipes and interfaces; a signal conversion unit for converting the concentration of decomposition products into analog electrical signals using a gas decomposition product analyzer and converting these signals into digital signals through an integrated microprocessor and an A / D converter; The display unit comprises an LCD display screen for displaying the actual value of the detected decomposition product concentration.

[0041] The data processing module includes: a recording unit, a preprocessing unit, and a comparison and analysis unit; A recording unit for recording the actual value of the detected decomposition product concentration; A preprocessing unit, used for preprocessing the actual values ​​of the recorded decomposition product concentrations, such as data cleaning and formatting; The comparison and analysis unit is used to compare the actual value of the detected concentration after pretreatment with the standard value and analyze the decomposition of SF6 gas.

[0042] The performance evaluation module includes: model building unit, performance judgment unit, and quality analysis unit; A model building unit, used to build a comprehensive performance evaluation model using historical data and container operating conditions; A performance judgment unit, used to judge the performance of SF6 gas according to the model; The mass analysis unit is used to determine the concentration of decomposition products and, based on the determination results, uses isotope tracking and chemometric methods to analyze the quality of SF6 gas, including its purity, water content, and degree of oxidation.

[0043] The maintenance measure formulation module includes: a measure formulation unit and an execution tracking unit; A measures formulation unit is used to formulate maintenance measures, such as changing gas and adjusting the operating conditions of the container, based on the results of performance evaluation and quality analysis; The execution tracking unit is used to track the execution of maintenance measures, ensure that the measures are effectively implemented, and record the data.

[0044] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0045] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0046] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in the field may also change, modify, replace and modify the above-mentioned embodiments without departing from the purpose and scope of protection of the present invention, and all of these are within the protection of the present invention.

Claims

1. A method for analyzing SF6 gas monitoring data for a sealed container, characterized in that: include: Step S1: extracting a quantitative SF6 gas sample from a sealed container using a sampling tool; Step S2: introducing the SF6 gas sample into the gas decomposition product analyzer, the gas decomposition product analyzer automatically converts the decomposition product concentration into an analog electrical signal, converts the analog electrical signal into a digital signal through an integrated microprocessor and an A / D converter, and displays the actual value of the detected decomposition product concentration on an LCD; Step S3: Record the actual value of the decomposition product concentration displayed on the LCD, perform pretreatment, compare the detected concentration after pretreatment with the standard value, and analyze the decomposition of SF6 gas; Step S4: Based on the SF6 gas decomposition results, an intelligent diagnosis strategy is used to automatically identify abnormal patterns, and a comprehensive performance evaluation model is constructed based on the intelligent diagnosis results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; Step S5: If the comprehensive performance evaluation model determines that the SF6 gas performance is abnormal, and the concentration of the decomposition product is higher than the preset concentration abnormality threshold, the isotope tracking and chemometric method is used to analyze the SF6 gas quality; Step S6: Formulate maintenance measures based on the judgment results of SF6 gas performance and quality analysis results.

2. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 1, characterized in that: The specific steps of analyzing the decomposition of SF6 gas in step S3 include: S3.1: By comparing the detected concentration after pretreatment With standard value , obtain the concentration ratio of each decomposition product after SF6 gas decomposition ,in, , , , Respectively represent the actual concentration values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, , , , Respectively represent the concentration standard values ​​of gas decomposition products SO2, H2S, SOF2, SO2F2, represents the actual value of the concentration of the i-th gas decomposition product, represents the correction factor for the i-th gas decomposition product, represents the concentration proportion of the i-th gas decomposition product; S3.2: Combine historical gas decomposition product concentration data and use a time series analysis model to analyze the changing trends of different decomposition product concentrations; S3.3: Set threshold values ​​for decomposition product concentrations , by analyzing the concentration proportion and change trend of decomposition products, it can be judged whether the decomposition of SF6 gas is complete; like , it means that the decomposition process is not thorough enough and there is incompletely decomposed SF6 gas or new decomposition products.

3. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 2, characterized in that: The specific steps of step S4 include: S4.1: Acquisition and ; S4.2: Extract the characteristics of SF6 gas performance based on the concentration ratio of SF6 gas decomposition products and the thoroughness of the decomposition process. The characteristics of SF6 gas performance include the purity, stability and insulation performance of SF6 gas. The thoroughness index B of the decomposition process is: , It indicates the decomposition amount of SF6 gas, and Q indicates the sampling amount of SF6 gas; S4.3: Based on the detection concentration after pretreatment , using intelligent diagnostic strategies to automatically identify abnormal patterns in SF6 gas decomposition results; S4.4: Construct a comprehensive performance evaluation model based on the intelligent diagnosis results, historical data and container operating conditions, and judge the performance of the SF6 gas in the sealed container based on the comprehensive performance evaluation model.

4. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 3, characterized in that: The specific steps of S4.3 include: S4.31: Collect sample data of SF6 gas decomposition products of known defect types, and use the sample data of SF6 gas decomposition products of known defect types to train the intelligent diagnosis strategy and establish a mapping relationship between characteristic gas concentration and defect type; S4.32: Acquisition , and Input into the trained intelligent diagnosis strategy, the trained intelligent diagnosis strategy is based on Automatically identify abnormal patterns of SF6 gas decomposition results and output the corresponding defect type or abnormality degree; S4.33: Verify the output defect type or abnormality level, and adjust and optimize the intelligent diagnosis strategy based on the verification results.

5. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 4, characterized in that: The specific steps of S4.4 include: S4.41: Obtain the intelligent diagnosis results output by the intelligent diagnosis strategy in S4.3, and at the same time, collect historical SF6 gas data and container operating condition data, and integrate them to form comprehensive SF6 gas monitoring data; S4.42: Arrange and combine the SF6 gas comprehensive monitoring data to form a feature matrix, wherein rows in the feature matrix represent samples and columns represent features; S4.43: Calculate the covariance matrix from the feature matrix , and Perform eigenvalue decomposition , get the eigenvalues ​​and corresponding eigenvectors, where represents the eigenvalue diagonal matrix, and P represents the eigenvector matrix; S4.44: According to the size of the eigenvalue, select the eigenvectors corresponding to the first k eigenvalues ​​with higher cumulative contribution rates as the main features; S4.45: Project the SF6 gas comprehensive monitoring data onto the main features to obtain SF6 gas low-dimensional data; S4.46: Based on the SF6 gas low-dimensional data, the similarity between the SF6 gas low-dimensional data and the SF6 gas performance characteristics is calculated using the correlation analysis method; S4.47: Screen the SF6 gas low-dimensional data according to the similarity calculation result to obtain the SF6 gas performance characteristics; S4.48: Load a pre-built support vector machine model, train the pre-built support vector machine model using the extracted SF6 gas performance characteristics, and generate a comprehensive performance evaluation model; S4.49: Input the data of the SF6 gas in the sealed container to be evaluated into the comprehensive performance evaluation model, obtain the prediction results of the comprehensive performance evaluation model, and judge the performance of the SF6 gas based on the prediction results.

6. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 5, characterized in that: The specific steps of step S5 include: S5.1: Obtain the judgment result Z of the comprehensive performance evaluation model and set the concentration abnormality threshold ; like , it is judged that the performance of SF6 gas is normal; like , it is judged that the SF6 gas performance is abnormal; S5.2: When judging that the performance of SF6 gas is abnormal; like , it is judged that the performance of SF6 gas is normal; like , perform the following steps: A1: Heavy oxygen water Inject into the SF6 gas sample and mix evenly to obtain an isotope-traced gas sample; A2: Chemical analysis of isotope-traced gas samples to determine their purity, water content, and degree of oxidation. Electrochemical sensors are used to detect the decomposition products of SF6 gas and calculate their concentrations. A3: Organize and process the data obtained from chemical analysis and electrochemical sensors, calculate the mass loss and performance change of SF6 gas, and evaluate the performance and quality of SF6 gas based on the mass loss and performance change results.

7. A method for analyzing SF6 gas monitoring data for a sealed container according to claim 6, characterized in that: The gas decomposition products in step S2 include SO2, H2S, SOF2, and SO2F2.

8. A SF6 gas monitoring data analysis system for a sealed container, which is used to implement a SF6 gas monitoring data analysis method for a sealed container as claimed in any one of claims 1 to 7, characterized in that: include: Sampling module, analysis module, data processing module, performance evaluation module, maintenance measures formulation module; The sampling module is used to extract a quantitative SF6 gas sample from the sealed container; The analysis module is used to introduce the SF6 gas sample into the gas decomposition product analyzer to detect and analyze the concentration of the decomposition products; The data processing module is used to record the actual value of the decomposition product concentration displayed by the LCD, and perform preprocessing and comparative analysis; The performance evaluation module is used to construct a comprehensive performance evaluation model based on the SF6 gas decomposition results, combined with historical data and container operating conditions, to determine the performance of the SF6 gas in the sealed container; The maintenance measure formulation module formulates corresponding maintenance measures based on the judgment results of SF6 gas performance and the quality analysis results.

9. A SF6 gas monitoring data analysis system for a sealed container as claimed in claim 8, characterized in that: The data processing module includes: a recording unit, a preprocessing unit, and a comparison and analysis unit; The recording unit is used to record the actual value of the detected decomposition product concentration; The preprocessing unit is used to preprocess the recorded actual value of the decomposition product concentration; The comparison and analysis unit is used to compare the actual value of the detected concentration after pretreatment with the standard value to analyze the decomposition of SF6 gas.

10. The SF6 gas monitoring data analysis system for a sealed container according to claim 9, characterized in that: The performance evaluation module includes: a model building unit, a performance judgment unit, and a quality analysis unit; The model building unit is used to build a comprehensive performance evaluation model using historical data and container operating conditions; The performance judgment unit is used to judge the performance of SF6 gas according to the model; The mass analysis unit is used to determine the concentration of decomposition products and, based on the determination result, analyze the quality of SF6 gas using isotope tracking and chemometric methods.

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