Grounding grid full-life management method fusing Lasso and improved grey wolf algorithm

Abstract

The invention discloses a grounding grid full-life management method fusing Lasso and an improved grey wolf algorithm, and the method comprises the steps: carrying out the corrosion diagnosis of a grounding grid through employing a preset corrosion diagnosis algorithm when the abnormal fluctuation of the operation of the grounding grid is detected, or the operation of the grounding grid is carried out for an inspection period time after the completion of the previous rectification; and generating a corrosion diagnosis report of the grounding grid according to the real-time detection data and the historical detection data so as to rectify the grounding grid, and according to the real-time detection data and the historical detection data, adjusting the next inspection period time of the grounding grid and predicting the residual life of the grounding grid. Based on a preset corrosion diagnosis algorithm, integration and closed-loop management can be carried out on whole-process data of design, detection, diagnosis, rectification, operation and maintenance of the grounding grid, an underdetermined equation set in grounding grid corrosion diagnosis is solved, the positioning precision is improved, non-excavation type accurate corrosion fault positioning is achieved, the diagnosis efficiency and the intelligent management level are improved, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of grounding grids, and in particular to a grounding grid full-life management method integrating Lasso and improved grey wolf algorithms. Background Art

[0002] Grounding grids are critical infrastructure for the safe operation of power system equipment. Corrosion can degrade grounding performance, threatening both personnel and equipment safety. Therefore, grounding grid corrosion diagnosis and management are essential. Existing grounding grid corrosion diagnosis technologies primarily include electromagnetic, electrochemical, and power grid methods. However, electromagnetic methods are susceptible to electromagnetic interference from high-voltage equipment and have low diagnostic accuracy. Electrochemical methods require excavation and sensor installation, making implementation complex and disruptive. Power grid methods have limited accessible nodes, resulting in underdetermined equations. Traditional algorithms (such as the least squares method) are prone to overfitting and lack diagnostic accuracy. Furthermore, existing grounding grid management technologies suffer from the following issues: scattered data silos for detection, diagnosis, rectification, and maintenance data; reliance on manual inspection records, which is inefficient and prone to errors; a lack of health monitoring and early warning, resulting in passive fault response; and a lack of digital tracking of rectification plans and construction quality. Summary of the Invention

[0003] The present invention provides a full-life cycle management method for a grounding grid that integrates the Lasso and improved grey wolf algorithms. Based on a corrosion diagnosis algorithm based on pure resistance network theory that integrates the Lasso and improved grey wolf algorithms, the method integrates and implements closed-loop management of data from the entire process of grounding grid design, detection, diagnosis, rectification, and operation and maintenance. The method can solve underdetermined equations in grounding grid corrosion diagnosis, suppress noise interference, improve positioning accuracy, achieve trenchless and precise positioning of corrosion faults, improve diagnostic efficiency and intelligent management, and reduce operation and maintenance costs.

[0004] To achieve the above objectives, an embodiment of the present invention provides a grounding grid lifecycle management method that integrates the Lasso and improved grey wolf algorithms, including:

[0005] Establishing topological structure data of the grounding grid according to a design drawing of the grounding grid; and detecting the grounding grid according to the topological structure data;

[0006] When abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has been running for an inspection cycle after the previous rectification is completed, real-time detection data and historical detection data are obtained; wherein the real-time detection data includes electrical parameters, appearance inspection data, and environmental parameters of the grounding grid;

[0007] Based on the electrical parameters, a preset corrosion diagnosis algorithm is used to perform corrosion diagnosis on the grounding grid, and a corrosion diagnosis report for the grounding grid is generated; wherein the preset corrosion diagnosis algorithm is obtained by improving the corrosion diagnosis algorithm of pure resistance network theory by combining Lasso and improved grey wolf algorithms;

[0008] generating an inspection work order for the grounding grid at a current moment according to the corrosion diagnosis report and the real-time detection data, and rectifying the grounding grid according to the inspection work order to update the topology data;

[0009] According to the real-time detection data and the historical detection data, the next inspection cycle time of the grounding grid is adjusted, and the remaining life of the grounding grid is predicted.

[0010] As an improvement to the above solution, the method of performing corrosion diagnosis on the grounding grid using a preset corrosion diagnosis algorithm based on the electrical parameters to generate a corrosion diagnosis report for the grounding grid includes:

[0011] establishing a grounding grid model according to the electrical parameters;

[0012] Adaptive weighted Lasso is used to solve the grounding grid model, branches corresponding to non-zero coefficients of the grounding grid are screened out, and a candidate set of high-probability corrosion branches and corresponding first branch resistance changes are obtained;

[0013] Using an improved grey wolf algorithm to optimize the branches in the candidate set, and obtaining an optimized resistance change of the second branch;

[0014] The first branch resistance variation and the second branch resistance variation are weightedly fused to obtain a comprehensive branch resistance variation, so as to generate a corrosion diagnosis report of the grounding grid.

[0015] As an improvement to the above solution, the improved grey wolf algorithm is used to optimize the branches in the candidate set to obtain the optimized resistance change of the second branch, including:

[0016] The candidate set and the corresponding first branch resistance change are used as the solution space constraints and initial positions of the improved grey wolf algorithm;

[0017] A hybrid objective function of the improved grey wolf algorithm is defined, and solution space constraints and initial positions are iteratively optimized according to the hybrid objective function to obtain an optimized second branch resistance change.

[0018] As an improvement to the above solution, generating a current inspection work order for the grounding grid based on the corrosion diagnosis report and the real-time detection data, and rectifying the grounding grid according to the inspection work order to update the topology data includes:

[0019] Matching a rectification plan for the grounding grid based on the corrosion diagnosis report and the real-time detection data; wherein the rectification plan includes construction drawings, a material list, and process standards;

[0020] Generate an inspection work order for the grounding grid at the current moment based on the rectification plan and role permissions;

[0021] The grounding grid is rectified and the execution progress is tracked according to the inspection work order to update the topology data.

[0022] As an improvement to the above solution, adjusting the next inspection cycle time of the grounding grid and predicting the remaining life of the grounding grid based on the real-time detection data and historical detection data includes:

[0023] Adjusting the next inspection cycle time of the grounding grid according to the real-time detection data;

[0024] The health status of the grounding grid is judged based on the real-time detection data and the historical corrosion diagnosis report in the historical detection data to predict the remaining life of the grounding grid.

[0025] As an improvement to the above solution, after updating the topology data, the method further includes:

[0026] Obtain rectification data, and upload the topology data, the rectification data, the real-time detection data, and the corrosion diagnosis report to update historical detection data.

[0027] Compared with the prior art, the present invention discloses a method for managing the lifecycle of a grounding grid that integrates the Lasso algorithm and the improved Grey Wolf algorithm. The method establishes topological structure data of the grounding grid based on the design drawings of the grounding grid, inspects the grounding grid based on the topological structure data, and acquires real-time and historical detection data when abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has run its inspection cycle after the previous rectification is completed. The real-time detection data includes electrical parameters, visual inspection data, and environmental parameters of the grounding grid. Based on the electrical parameters, the grounding grid is subjected to corrosion diagnosis using a preset corrosion diagnosis algorithm to generate a corrosion diagnosis report for the grounding grid. The preset corrosion diagnosis algorithm is obtained by improving the corrosion diagnosis algorithm based on pure resistance network theory by combining the Lasso algorithm and the improved Grey Wolf algorithm. Based on the corrosion diagnosis report and the real-time detection data, an inspection work order for the grounding grid at the current moment is generated, and the grounding grid is rectified according to the inspection work order to update the topological structure data. Based on the real-time and historical detection data, the time for the next inspection cycle of the grounding grid is adjusted, and the remaining life of the grounding grid is predicted. Based on the corrosion diagnosis algorithm of pure resistance network theory that integrates Lasso and improved grey wolf algorithms, it can integrate and close-loop manage the entire process data of grounding grid design, detection, diagnosis, rectification, and operation and maintenance, solve the underdetermined equations in grounding grid corrosion diagnosis, suppress noise interference, improve positioning accuracy, realize trenchless precise positioning of corrosion faults, improve diagnostic efficiency and intelligent management level, and reduce operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a grounding grid lifecycle management method that integrates the Lasso and improved grey wolf algorithms, provided by an embodiment of the present invention;

[0029] Figure 2 This is a functional diagram of the grounding network diagnostic management platform provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "comprises" and "specifically" and any variations thereof in the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, products or apparatuses.

[0032] See also Figure 1 , Figure 1 This is a flow chart of a grounding grid lifecycle management method that integrates the Lasso and improved gray wolf algorithms, provided by an embodiment of the present invention. The grounding grid lifecycle management method that integrates the Lasso and improved gray wolf algorithms includes:

[0033] S1, establishing topological structure data of the grounding grid according to a design drawing of the grounding grid; and detecting the grounding grid according to the topological structure data;

[0034] S2, when abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has been running for an inspection cycle after the previous rectification is completed, obtaining real-time detection data and historical detection data; wherein the real-time detection data includes electrical parameters, appearance inspection data, and environmental parameters of the grounding grid;

[0035] S3, performing corrosion diagnosis on the grounding grid based on the electrical parameters using a preset corrosion diagnosis algorithm to generate a corrosion diagnosis report for the grounding grid; wherein the preset corrosion diagnosis algorithm is obtained by improving a corrosion diagnosis algorithm based on pure resistance network theory by combining a Lasso algorithm and an improved Grey Wolf algorithm;

[0036] S4, generating a current inspection work order for the grounding grid based on the corrosion diagnosis report and the real-time detection data, and rectifying the grounding grid according to the inspection work order to update the topology data;

[0037] S5, adjusting the next inspection cycle time of the grounding grid according to the real-time detection data and the historical detection data, and predicting the remaining life of the grounding grid.

[0038] For example, the grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms described in the embodiment of the present invention is implemented by a grounding grid diagnosis and management platform server, which can exchange information with target users. Figure 2 , Figure 2This is a functional diagram of the grounding grid diagnostic management platform provided by an embodiment of the present invention, including a data management module: storing full-cycle data of the grounding grid (such as design drawings, inspection records, rectification reports, operation and maintenance logs, etc.), supporting historical data comparison and analysis, and generating trend charts; a business management module: automatically generating inspection work orders, assigning tasks to designated personnel, tracking execution progress, associating rectification plans with construction records, and ensuring process compliance; a health management module: predicting the remaining life of the grounding grid based on historical corrosion diagnosis results, triggering early warning notifications, and visually displaying key indicators such as corrosion hotspots and grounding resistance distribution; and an authority management module: multi-role hierarchical authority control (such as administrators, technicians, construction teams, etc.), and operation log auditing to ensure data security and traceability. The grounding grid diagnosis management platform server establishes topological structure data of the grounding grid based on the design drawings of the grounding grid; detects the grounding grid based on the topological structure data; obtains real-time detection data and historical detection data when abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has been running for the inspection cycle after the previous rectification is completed; wherein the real-time detection data includes the electrical parameters, appearance inspection data and environmental parameters of the grounding grid; based on the electrical parameters, the grounding grid is subjected to corrosion diagnosis using a preset corrosion diagnosis algorithm to generate a corrosion diagnosis report for the grounding grid; wherein the preset corrosion diagnosis algorithm is obtained by improving the corrosion diagnosis algorithm of pure resistance network theory by combining the Lasso algorithm and the improved gray wolf algorithm; based on the corrosion diagnosis report and the real-time detection data, an inspection work order for the grounding grid at the current moment is generated, and the grounding grid is rectified according to the inspection work order to update the topological structure data; based on the real-time detection data and the historical detection data, the next inspection cycle time of the grounding grid is adjusted, and the remaining life of the grounding grid is predicted. The embodiment of the present invention is based on a corrosion diagnosis algorithm based on pure resistance network theory that integrates the Lasso and improved grey wolf algorithms. It integrates and performs closed-loop management on the entire process data of grounding grid design, detection, diagnosis, rectification, and operation and maintenance. It can solve the underdetermined equations in grounding grid corrosion diagnosis, suppress noise interference, improve positioning accuracy, realize trenchless and precise positioning of corrosion faults, improve diagnostic efficiency and intelligent management level, and reduce operation and maintenance costs.

[0039] Specifically, step S3 includes:

[0040] S31, establishing a grounding grid model according to the electrical parameters;

[0041] S32, using an adaptive weighted Lasso to solve the grounding grid model, screening out branches corresponding to non-zero coefficients of the grounding grid, and obtaining a candidate set of high-probability corrosion branches and corresponding first branch resistance changes;

[0042] S33, optimizing the branches in the candidate set using an improved grey wolf algorithm to obtain an optimized resistance change of the second branch;

[0043] S34, performing weighted fusion on the first branch resistance change and the second branch resistance change to obtain a comprehensive branch resistance change, so as to generate a corrosion diagnosis report of the grounding grid.

[0044] More specifically, the S33 includes:

[0045] S331, using the candidate set and the corresponding first branch resistance change as the solution space constraint and initial position of the improved grey wolf algorithm;

[0046] S332, defining a hybrid objective function of the improved grey wolf algorithm, and iteratively optimizing the solution space constraints and the initial position according to the hybrid objective function to obtain an optimized second branch resistance change.

[0047] For example, the power grid method is used to establish a grounding grid model, and the Lasso and improved grey wolf algorithms (GWO) are integrated in stages. Through dynamic collaboration and the introduction of L1 regularization penalty terms, a physical constraint-guided intelligent search is formed to achieve a "coarse screening + fine refinement" two-stage optimization, suppress the influence of branches with less corrosion, reduce the underdetermination of the equation, achieve high-precision sparse solutions, and improve diagnostic efficiency and accuracy. For example, in the coarse screening stage, the electrical parameters are median filtered to remove outliers, and after normalization (parameters such as voltage and resistance are scaled to the [0,1] interval to avoid dimensional effects on algorithm convergence), a grounding grid model is established, and dynamic weights are introduced to reflect the prior corrosion risk of branches. The objective function is determined, and the grounding grid model is solved by minimizing the objective function. The branches corresponding to the non-zero coefficients of the grounding grid are screened out, and a candidate set of high-probability corrosion branches and the corresponding first branch resistance changes (Lasso results) are obtained; in the fine refinement stage, the candidate set and the corresponding first branch resistance changes are used as the solution space constraints and initial positions of the improved grey wolf algorithm, and only the branches in the candidate set are selected. The branches are optimized, the variable dimension is reduced, and dynamic upper and lower bounds are set; a hybrid objective function of the improved gray wolf algorithm is defined, and the Lasso result is used as the initial position of the gray wolf according to the hybrid objective function to accelerate convergence. The step probability is associated with the residual, and when the residual is large, the random search intensity is increased to perform iterative optimization to obtain the optimized second branch resistance change; the first branch resistance change and the second branch resistance change are weightedly fused to obtain the comprehensive branch resistance change, and a corrosion index is defined according to the comprehensive branch resistance change. Combined with the inversion results and the prior risk, a graded alarm (normal / mild / severe) is output to generate a corrosion diagnosis report for the grounding grid.

[0048] The grounding grid model can be expressed as a set of linear equations:

[0049] Y=JΔR+∈,

[0050] Where Y is the node voltage change, J is the sensitivity matrix, ΔR is the branch resistance change (sparse vector), and ∈ is the noise.

[0051] The objective function is:

[0052]

[0053] Where, dynamic weight Risk j Score the branch corrosion risk (based on prior data such as material and specifications).

[0054] The high probability corrosion branch candidate set S = {j | ΔR j ≠0}, compressing the solution space from p dimensions to |S| dimensions (|S|<<p).

[0055] Dynamic upper and lower bounds: ( is the Lasso result)

[0056] The hybrid objective function is:

[0057]

[0058] Among them, for non-candidate branches Apply L1 penalty (η>>λ) to ensure that GWO searches only within S. As the initial position of the gray wolf α, it accelerates convergence, and the step probability q is associated with the residual, q = 1-Fitness / Fitness max , increase the random search intensity when the residual is large;

[0059] The change in comprehensive branch resistance is:

[0060]

[0061] In the formula, the weight ω is adaptively adjusted according to the residual, ω = ‖Y-JΔR Lasso ‖2 / (‖·‖ Lasso +‖·‖ GWO ).

[0062] The corrosion index is:

[0063]

[0064] Specifically, step S4 includes:

[0065] S41, matching a rectification plan for the grounding grid based on the corrosion diagnosis report and the real-time detection data; wherein the rectification plan includes construction drawings, a material list, and process standards;

[0066] S42, generating an inspection work order for the grounding grid at the current moment according to the rectification plan and role permissions;

[0067] S43: rectify the grounding grid according to the inspection work order and track the execution progress to update the topology data.

[0068] Specifically, step S5 includes:

[0069] S51, adjusting the next inspection cycle time of the grounding grid according to the real-time detection data;

[0070] S52: judging the health status of the grounding grid based on the real-time detection data and the historical corrosion diagnosis report in the historical detection data, so as to predict the remaining life of the grounding grid.

[0071] Furthermore, after updating the topology data, the method further includes:

[0072] Obtain rectification data, and upload the topology data, the rectification data, the real-time detection data, and the corrosion diagnosis report to update historical detection data.

[0073] Exemplarily, the grounding grid includes full-process management, including: in the design phase, uploading construction CAD drawings and establishing a grounding grid topology database; in the detection phase, collecting port resistance through corrosion diagnosis equipment, using built-in algorithms to analyze data, locating corrosion fault areas, and generating diagnostic reports; in the rectification phase, automatically matching rectification plans based on diagnostic results, pushing construction drawings, material lists, and process standards; in the operation and maintenance phase, formulating periodic inspection plans, real-time monitoring of health status, and warning of remaining life; standardized service processes include: detection services, using the four-electrode method to measure port resistance, inputting port resistance changes and branch current initial values, and constructing an underdetermined set of equations; introducing L1 regularization terms, iteratively optimizing and solving branch resistance changes; outputting the location and degree of corrosion branches, and generating a visual diagnostic report; engineering services, based on the rectification plan generated by the platform, the construction team replaces corroded parts according to standard procedures, using hot-dip galvanized flat steel or copper-clad steel materials, and retesting and accepting after construction; operation and maintenance services, regularly and automatically pushing inspection tasks, and dynamically adjusting the operation and maintenance plan based on real-time monitoring data.

[0074] This embodiment of the present invention manages the entire process, from initial construction acceptance, regular corrosion testing during operation, customized engineering services for remediation plans, to post-remediation diagnosis, retesting, and acceptance. This allows users to comprehensively inspect, accurately diagnose, and efficiently rectify grounding grids, achieving complete closed-loop management of the grounding grid. It primarily provides grounding grid inspection services, diagnostic reports, remediation plan development, engineering services, and regular maintenance and operation services.

[0075] An embodiment of the present invention discloses a full-lifecycle management method for a grounding grid that integrates the Lasso algorithm and the improved Grey Wolf algorithm. The method comprises: establishing topological structure data of the grounding grid based on a design drawing of the grounding grid; inspecting the grounding grid based on the topological structure data; acquiring real-time inspection data and historical inspection data when abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has been running for an inspection cycle after a previous rectification is completed; wherein the real-time inspection data includes electrical parameters, appearance inspection data, and environmental parameters of the grounding grid; performing corrosion diagnosis on the grounding grid based on the electrical parameters using a preset corrosion diagnosis algorithm to generate a corrosion diagnosis report for the grounding grid; wherein the preset corrosion diagnosis algorithm is obtained by improving a corrosion diagnosis algorithm based on pure resistance network theory by combining the Lasso algorithm and the improved Grey Wolf algorithm; generating an inspection work order for the grounding grid at the current moment based on the corrosion diagnosis report and the real-time inspection data; and rectifying the grounding grid based on the inspection work order to update the topological structure data; adjusting the next inspection cycle of the grounding grid based on the real-time inspection data and the historical inspection data, and predicting the remaining life of the grounding grid. Based on the corrosion diagnosis algorithm of pure resistance network theory that integrates Lasso and improved grey wolf algorithms, it can integrate and close-loop manage the entire process data of grounding grid design, detection, diagnosis, rectification, and operation and maintenance, solve the underdetermined equations in grounding grid corrosion diagnosis, suppress noise interference, improve positioning accuracy, realize trenchless precise positioning of corrosion faults, improve diagnostic efficiency and intelligent management level, and reduce operation and maintenance costs.

[0076] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms, characterized in that: include: Establishing topological structure data of the grounding grid according to the design drawings of the grounding grid; Detecting the grounding grid according to the topology data; When abnormal fluctuations in the operation of the grounding grid are detected, or when the grounding grid has been running for an inspection cycle after the previous rectification is completed, real-time detection data and historical detection data are obtained; wherein the real-time detection data includes electrical parameters, appearance inspection data, and environmental parameters of the grounding grid; Based on the electrical parameters, a preset corrosion diagnosis algorithm is used to perform corrosion diagnosis on the grounding grid, and a corrosion diagnosis report for the grounding grid is generated; wherein the preset corrosion diagnosis algorithm is obtained by improving the corrosion diagnosis algorithm of pure resistance network theory by combining Lasso and improved grey wolf algorithms; generating an inspection work order for the grounding grid at a current moment according to the corrosion diagnosis report and the real-time detection data, and rectifying the grounding grid according to the inspection work order to update the topology data; According to the real-time detection data and the historical detection data, the next inspection cycle time of the grounding grid is adjusted, and the remaining life of the grounding grid is predicted.

2. The grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithm according to claim 1, characterized in that: The method of performing corrosion diagnosis on the grounding grid using a preset corrosion diagnosis algorithm based on the electrical parameters to generate a corrosion diagnosis report for the grounding grid includes: establishing a grounding grid model according to the electrical parameters; Adaptive weighted Lasso is used to solve the grounding grid model, branches corresponding to non-zero coefficients of the grounding grid are screened out, and a candidate set of high-probability corrosion branches and corresponding first branch resistance changes are obtained; Using an improved grey wolf algorithm to optimize the branches in the candidate set, and obtaining an optimized resistance change of the second branch; The first branch resistance variation and the second branch resistance variation are weightedly fused to obtain a comprehensive branch resistance variation, so as to generate a corrosion diagnosis report of the grounding grid.

3. The grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms as claimed in claim 2 is characterized in that: The improved grey wolf algorithm is used to optimize the branches in the candidate set to obtain the optimized second branch resistance change, including: The candidate set and the corresponding first branch resistance change are used as the solution space constraints and initial positions of the improved grey wolf algorithm; A hybrid objective function of the improved grey wolf algorithm is defined, and solution space constraints and initial positions are iteratively optimized according to the hybrid objective function to obtain an optimized second branch resistance change.

4. The grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms according to claim 1, characterized in that: Generating a current inspection work order for the grounding grid based on the corrosion diagnosis report and the real-time detection data, and rectifying the grounding grid according to the inspection work order to update the topology data, including: Matching a rectification plan for the grounding grid based on the corrosion diagnosis report and the real-time detection data; wherein the rectification plan includes construction drawings, a material list, and process standards; Generate an inspection work order for the grounding grid at the current moment based on the rectification plan and role permissions; The grounding grid is rectified and the execution progress is tracked according to the inspection work order to update the topology data.

5. The grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms according to claim 1, characterized in that: The adjusting the next inspection cycle time of the grounding grid according to the real-time detection data and the historical detection data, and predicting the remaining life of the grounding grid, includes: Adjusting the next inspection cycle time of the grounding grid according to the real-time detection data; The health status of the grounding grid is judged based on the real-time detection data and the historical corrosion diagnosis report in the historical detection data to predict the remaining life of the grounding grid.

6. The grounding grid lifecycle management method integrating Lasso and improved grey wolf algorithms according to claim 1, characterized in that: After updating the topology data, the method further includes: Obtain rectification data, and upload the topology data, the rectification data, the real-time detection data, and the corrosion diagnosis report to update historical detection data.

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