A method and system for quantifying accessibility for maintenance

Abstract

The application discloses a kind of maintenance accessibility quantitative mapping method and system, the method includes: first, scene feature information is collected and initial parameter set is generated;Second, the construction of virtual maintenance environment is driven using the parameter set, the generation of scene sample is completed;Then, from three dimensions of vision, operation and space, accessibility evaluation system is constructed, and sample is quantitatively scored;Finally, different grades are divided according to the scoring results.The system includes: parameter module, scene module, quantification module and grading module.By using the application, maintenance accessibility evaluation is changed from qualitative subjectivity to standardized quantification (parameter→modeling→quantification→mapping), deviation is avoided, and the evaluation has the characteristics of uniform standard, reviewable and traceable.The application can be widely applied in engineering maintenance technical field.

Description

Technical Field

[0001] This invention relates to the field of engineering maintenance technology, and in particular to a quantitative mapping method and system for maintenance accessibility. Background Technology

[0002] In existing maintainability assessments, maintainability is typically described using qualitative methods such as expert scoring, questionnaires, or "good / average / poor." For power systems with complex structures, limited space, and constrained motion paths, traditional qualitative assessments have three prominent problems: first, the evaluation is highly subjective, with significant differences in results from different personnel; second, there is a lack of reproducible quantitative evidence, making it difficult to support design optimization and scheme comparison.

[0003] Therefore, there is a need to propose a method that can transform the qualitative description of maintenance accessibility into calculable, interpretable, and verifiable quantitative results, so that the evaluation conclusions can not only serve engineering design, but also support cross-platform and cross-condition comparative analysis through a unified level expression. Summary of the Invention

[0004] In view of this, in order to solve the technical problem that most existing maintenance accessibility evaluation methods rely on subjective human judgment, resulting in subjective and unquantifiable accessibility evaluations, this invention proposes a quantitative mapping method for maintenance accessibility, which includes the following steps: S1. Collect scene feature information and generate an initial parameter set; S2. Use this parameter set to drive the construction of a virtual maintenance environment and complete the generation of scene samples; S3. Construct an accessibility assessment system from three dimensions: visual, operational, and spatial, and quantify and score the samples; S4. Divide the samples into different levels based on the scoring results.

[0005] In some embodiments, step S1 further includes: Acquire raw information such as the object to be maintained, maintenance access point, obstacles, tools, human posture, target component location, and operation type, and divide the key inputs affecting maintainability into a set of continuous variables. and discrete variable sets .

[0006] Among them, continuous variables preferably include maintenance opening size, maintenance depth, gap distance, tool length, and range of motion of human joints; discrete variables preferably include tool type, fastener specifications, maintenance position, action type, and work sequence, so as to achieve a structured expression of the actual maintenance working conditions.

[0007] Establish probability distribution models for parameters with different physical properties; for parameters constrained by closed intervals, uniform distribution or truncated normal distribution can be used; for parameters constrained by one side, Weibull distribution or other right-skewed distribution can be used to truly reflect the uncertainty of manufacturing tolerances, operating condition fluctuations and usage conditions.

[0008] Based on the probability distribution, the Monte Carlo method is used to generate multiple sets of parameter samples, thereby forming a sample set covering typical working conditions, critical working conditions and extreme working conditions, which is used to drive the subsequent batch reconstruction of virtual maintenance scenarios and accessibility statistical evaluation.

[0009] In some embodiments, it also includes: To characterize the coupling constraints between continuous and discrete variables, a conditional probability matrix can be constructed. And under the premise of satisfying known engineering constraints, the maximum entropy method or other probabilistic consistency method is used to solve the problem so that the tool selection, body position selection and movement mode are matched with the spatial scale conditions.

[0010] Based on the above embodiments, the output of step S1 is a parameterized input set, parameter constraint relationship, and benchmark condition configuration file that can be directly called for subsequent simulation calculations.

[0011] In some embodiments, step S2 specifically includes: According to the mapping function A unified model is created for the equipment geometry, target component location, ergonomic constraints, tool envelope space, and obstacle distribution to generate a 3D virtual maintenance scene corresponding to the current sample parameters.

[0012] In this step, it is preferable to further construct "completely unreachable" and "completely reachable" benchmark samples, which serve as the lower and upper limits of the quantization interval, respectively. The benchmark samples can be used for subsequent level boundary determination, as well as for model calibration, threshold comparison, and algorithm correctness verification.

[0013] In some embodiments, the visual accessibility metrics in step S3 specifically include: Visual accessibility quantification is used to characterize the feasibility of maintenance personnel observing target components during operation. It comprehensively considers factors such as field of view coverage, target posture occlusion, observation angle, and visual efficiency, and outputs a visual accessibility quantification index.

[0014] Visual accessibility metrics can be implemented using a weighted model. Where R represents the visual field factor assessment value, G represents the target posture factor assessment value, A represents the visual comfort assessment value, and F represents the visual ergonomics assessment value. The corresponding weights are given, and the sum of the weights is 1.

[0015] in: Visual Factor Evaluation Value The following formula can be used for calculation: In the formula, The total number of triangular grids divided on the surface of the observed object. for The area of ​​each grid (i.e., the denominator is the total target surface area). To account for the number of grids visible to the human eye when considering environmental occlusion factors, For the first The area of ​​each visible grid cell. For this visible grid, based on the near-boundary ratio The interpolated field coefficient values.

[0016] Object posture factor evaluation value The following formula can be used for calculation: In the formula For the first The pose coefficient values ​​corresponding to each visible triangular mesh.

[0017] In ergonomics, perspective The angle refers to the angle between the two ends of the observed object and the two lines connecting the viewpoint. The size of the angle can be calculated using the following formula: Visual efficiency Evaluation value based on visual factors Object posture factor evaluation value Perspective Factor Evaluation Value The calculation yields the following formula for quantification: This indicator can transform the empirical judgment of "visibility" into a comparable and statistically analyzable quantitative result, providing a visual dimension for subsequent comprehensive evaluation.

[0018] In some embodiments, the entity reachability metrics in step S3 specifically include: Quantitative accessibility of entities is used to assess the ease with which a tool or hand can reach a target component. It combines the operation path length D and the target feature size W in the virtual scene to construct an entity accessibility index. This reflects the operational efficiency of being "within reach".

[0019] The entity accessibility index can be modeled using Fitts's Law. ,in The reference time for the start of the action. The reciprocal of the information processing rate. This is the length of the operation path. The target size.

[0020] By uniformly quantifying different paths, target parts, and tool conditions, this quantification can provide a comparable analytical basis for the feasibility of contacting maintenance objects and operational efficiency.

[0021] In some embodiments, the spatial reachability index of step S3 specifically includes: Spatial accessibility quantification is used to assess whether the space margin meets maintenance requirements for specific work processes; this module preferably solves the posture of the tool and hand at each sampling position step by step according to the tool motion type, rotation reference axis, step size setting and local coordinate system, and performs collision detection simultaneously during the solution process.

[0022] After determining the scope of the workspace, the gravitational field of the target point can be further constructed. It is used to characterize the ease with which the tool end or arm trajectory approaches the target maintenance point.

[0023] Simultaneously construct an obstacle repulsion field. This is used to characterize the risk of obstacles interfering with the movement of tools or arms, where Let i be the coordinates of the center of the i-th obstacle. Indicates the obstacle risk coefficient. Indicates the range of influence of the obstacle.

[0024] Through the gradient of the total potential field Characterize the optimization direction of the maintenance path, and combine it with the average clearance value. With interference probability Obtain spatial accessibility score ,in, This represents the average gap value, which is the average minimum distance between the tool / limb and the environment under all step lengths in the work trajectory; and The upper and lower limits of the scale boundary are the benchmark assessment values ​​for completely inaccessible (5mm, touch interference) and completely accessible (150mm, open space).

[0025] If a collision occurs during the simulation, it can be directly determined that the current working condition does not meet the spatial accessibility requirements; if no collision occurs, the spatial margin is quantified based on the peak value of the total potential field, the smoothness of the potential field gradient, and the average gap level, thereby achieving a comprehensive evaluation of "can be done" and "whether it is done smoothly and safely".

[0026] In some embodiments, step S4 specifically includes: For each set of random parameter samples, output the corresponding visual accessibility, physical accessibility, and spatial accessibility results to construct a multidimensional index dataset. And determine the quantiles of each indicator based on the cumulative distribution function. .

[0027] Based on the above quantiles, the continuous quantization results can be divided into discrete level intervals of 1 to 8, where level 1 is preferred and represents completely unreachable, and level 8 is preferred and represents completely reachable. This grading method can be dynamically updated according to parameter distribution, manufacturing capabilities and platform differences, and has stronger adaptability.

[0028] For each indicator's quantification result, quantile points are calculated, and a corresponding quantitative mapping grading table of levels 1 to 8 is generated. In other words, the final output of this invention is not a general overall grading table, but rather includes at least a visual accessibility grading table. Physical Accessibility Classification Table and spatial accessibility classification table .

[0029] For any indicator to be evaluated , First, the set of quantitative results for this indicator under N sample working conditions is obtained through the corresponding quantitative model. Among them, visual accessibility corresponds to Entity reachability corresponds to Spatial reachability corresponds to .

[0030] Subsequently, the quantile boundaries were calculated for each set of indicator results. This allows for the division of continuous quantification results into eight level intervals. Different indicators use their own quantile boundaries to avoid directly mixing three fundamentally different dimensions: visual, physical, and spatial.

[0031] Based on the quantile boundaries, a quantitative mapping hierarchy table for visual accessibility can be generated. Quantitative Mapping Hierarchy Table of Entity Accessibility And spatial accessibility quantification mapping hierarchy table Each classification table should include at least the classification number, quantification range, typical parameter performance, and corresponding engineering guidance significance.

[0032] In a preferred embodiment, in addition to outputting the index value and level corresponding to a single sample, the system also simultaneously outputs the grading table entries, boundary sources, calibration basis, and optimization suggestions corresponding to that level, so that the evaluation results can be directly used for maintenance access size optimization, obstacle layout adjustment, tool selection, or work process improvement.

[0033] Furthermore, to improve the engineering interpretability of the grading results, expert scores can be collected simultaneously. Questionnaire scores of operators and the original quantification level The final calibration level is obtained by weighting and fusing the two types of subjective ratings. .

[0034] For samples whose scoring dispersion exceeds the threshold, the module can also trigger on-site verification, simulation recalculation, or weight rebalancing to form a closed-loop evaluation mechanism of "quantitative calculation - empirical calibration - anomaly verification".

[0035] This invention also proposes a quantitative mapping system for maintenance accessibility, which includes a parameter module, a scenario module, a quantification module, and a hierarchical module.

[0036] Based on the above scheme, the present invention provides a quantitative mapping method and system for maintenance accessibility, which transforms the traditional subjective description of maintenance accessibility as "good / average / poor" into a standardized evaluation result supported by parameter input, virtual modeling, quantitative calculation and grade mapping. This effectively reduces subjective biases between different evaluators, different evaluation batches and different user units, and improves the consistency, verifiability and traceability of evaluation conclusions. Attached Figure Description

[0037] Figure 1 This is a flowchart of the steps of a quantitative mapping method for maintenance accessibility according to the present invention; Figure 2 This is a structural block diagram of a maintenance accessibility quantitative mapping system according to the present invention. Detailed Implementation

[0038] Besides the technical issues mentioned in the background section, when dealing with complex structures, space-constrained environments, and long action chains such as power and energy systems, at least the following shortcomings still exist: 1. Fragmented evaluation dimensions. Existing solutions often only consider one dimension, such as visibility, accessibility, or disassembly / assembly time, lacking integrated modeling of the three constraints of "visible, reachable, and operable," making it difficult for evaluation conclusions to truly reflect the feasibility of the complete maintenance process. 2. Insufficient representation of dynamic operation processes. Many solutions only verify static postures or geometric interference at a single moment, making it difficult to characterize the spatial redundancy changes in continuous actions such as tool rotation, pulling, extending, and retracting, and also difficult to reflect the dynamic coupling relationship between the arm, tool, and obstacles. 3. Lack of parametric modeling mechanisms for uncertain working conditions. Existing technologies usually conduct analysis based on a single set of nominal parameters, rarely considering random factors such as fluctuations in maintenance port size, obstacle position deviations, differences in human body size, changes in tool specifications, and manufacturing tolerances, resulting in insufficient coverage of actual batch working conditions in the evaluation results. 4. Disconnect between quantitative results and engineering semantics. Even if some solutions can output continuous values, they often lack a stable mapping relationship with engineering level, risk level, and design recommendations. Designers find it difficult to quickly determine whether the current solution is "acceptable," "needs optimization," or "must be refactored" based on a single value. 5. Lack of unified benchmark intervals and cross-scenario comparability. Different products, different maintenance tasks, or different evaluators use inconsistent reference boundaries and thresholds, which can easily lead to the inability to horizontally compare evaluation results of the same type of operation on different platforms, hindering the formation of verifiable, transferable, and sustainable maintainability standards. 6. Lack of an effective integration mechanism between subjective experience and simulation data. Existing solutions either rely excessively on expert subjective judgment or only output simulation values, lacking a closed-loop process for jointly calibrating questionnaire perceptions, field experience, and quantitative results, thus making it difficult to balance statistical objectivity and engineering applicability. 7. Difficulty in directly supporting design optimization and assurance decisions. Due to the lack of structured output of key constraint parameters, risk sources, and optimization directions, existing evaluation results can usually only be used as an analytical reference, making it difficult to further transform them into direct basis for maintenance access size optimization, tool selection adjustment, layout improvement, or workflow refactoring.

[0039] For the reasons mentioned above, a new quantitative mapping method for maintenance accessibility indicators needs to be proposed, so that it can be applied to multiple source parameters and multiple operating conditions, forming a closed-loop evaluation system from parameter acquisition, virtual modeling, three-dimensional quantification, statistical classification to empirical calibration.

[0040] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] It should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0042] It should be understood that the terms "system," "apparatus," and / or "module" used in this application are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0043] Furthermore, flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Additionally, other operations can be added to these processes, or one or more steps can be removed from them.

[0044] Reference Figure 1 This is a flowchart illustrating an optional example of the quantitative mapping method for maintenance accessibility proposed in this invention. This method can be applied to computer equipment, and the mapping method proposed in this embodiment may include, but is not limited to, the following steps: Step S101: Collect the work scenario and determine the input parameters.

[0045] First, collect the structural and operational data of the target work unit, including at least: the diameter of the maintenance port. Maintenance depth Target filter element center position Location of surrounding pipes / wiring harnesses / housing and other obstacles Typical safety distance Tool length The input parameters include the tool's shape envelope, the working position, and the target action type. Among these parameters, the maintenance port diameter, obstacle spacing, and tool length can be treated as continuous variables, while the tool type, maintenance posture, and action mode can be treated as discrete variables.

[0046] S102. Establish a virtual maintenance scenario based on spatial accessibility.

[0047] A three-dimensional virtual maintenance scene is constructed based on the collected parameters, and target parts, maintenance ports, obstacles, human models, and tool models are loaded into the scene. For the filter replacement action in this embodiment, the operation process can be divided into three stages: "tool entry - loosening / rotation - extraction and retraction". If the filter element adopts a threaded connection, the tool motion type is preferably defined as rotation around the rotation axis of the maintenance component. After loosening is completed, a translational trajectory is defined along the direction of filter element extraction.

[0048] S103. Determine the scope of the work space and perform motion sampling.

[0049] First, assemble the maintenance tools and determine their motion type. Then, draw a rotational reference axis or translational reference direction at the sampling point, input the coordinates of a point on the axis, obtain the position of the origin of the local coordinate system, and set the step size. and range of motion or The system then gradually moves to the next step size position, updating the tool and hand coordinates in real time, and solving the positional problem for each step's posture. If necessary, ergonomic constraints can be further superimposed, such as using NASA single-joint range of motion data to constrain neck rotation, flexion / extension, and other upper limb postures, eliminating posture samples that exceed physiological limits.

[0050] S104. Perform collision detection and determine the feasible motion range.

[0051] At each sampling location, collision detection is performed on the tool, hand, and forearm envelopes and the obstacle set. If a rigid collision occurs, the collision location, the collision object, and the corresponding motion stage are recorded. If an unavoidable collision exists at a certain stage, it can be directly determined that the working condition does not meet the spatial accessibility requirements. If no collision occurs, the set of feasible motion positions corresponding to that stage is retained and proceeds to subsequent potential field calculations.

[0052] S105. Construct an artificial force field model for spatial accessibility.

[0053] Under conditions where no collision occurs, the target repair point Establish a gravitational field at the center ,in With maintenance port diameter Relevant, acceptable ; Preferred tool extension length Relevant, acceptable Subsequently, focusing on the center of each obstacle... Establish a repulsive field at the center ,in Obstacle hazard level Safety distance jointly determined, Can be taken as To characterize the extent of the obstacle's influence. Total potential field gradient. Used to characterize the degree of spatial movement constraints of tools and arms and to determine optimization directions.

[0054] S106, Calculate the spatial reachability quantization value.

[0055] The average gap value is obtained by statistically analyzing the entire movement trajectory / the minimum distance between the limb and the surrounding environment. Simultaneously, the real-time distance is less than the safety margin. The step size ratio is used to obtain the interference probability. Spatial accessibility scores can be further calculated as follows: In a preferred embodiment, Pick To characterize completely unreachable or touching the interference boundary, Desirable Using open space as a benchmark, safety margin Desirable Weight and The values ​​can be 0.6 and 0.4 respectively. If a collision occurs, the condition can be directly classified into the lowest level range or recorded as not meeting the spatial accessibility requirements.

[0056] S107. Generate a spatial accessibility quantitative mapping hierarchy table.

[0057] Monte Carlo sampling was performed based on the probability distribution of parameters such as access point size, obstacle spacing, tool length, and maintenance posture to obtain N sets of spatial accessibility scores. Then calculate the quantiles. This results in eight level intervals and the generation of a quantitative mapping classification table for spatial accessibility. The specific numerical boundaries in the classification table are automatically determined by the actual sample distribution, while the engineering semantics are defined by combining the smoothness of action, spatial margin, and interference risk.

[0058] Table 1 shows an example of one method for generating a quantitative mapping hierarchy table of spatial accessibility. S108. Calibration is performed by combining questionnaire surveys and expert knowledge.

[0059] For samples near the grading boundaries, maintenance engineer scores can be further collected. Questionnaire scores of operators and in accordance with The spatial accessibility classification results are calibrated in a certain way; if the scoring dispersion exceeds the preset threshold, on-site verification or re-simulation is triggered to ensure that the classification table conforms to both statistical laws and actual operational perception.

[0060] S109, Output Results.

[0061] The final output should include at least: the spatial reachability quantification value of the current job sample. The table includes the classification level, entries in the quantitative mapping grading table for spatial accessibility, key constraints leading to low levels, and corresponding optimization suggestions. Using the same process, a quantitative mapping grading table for visual accessibility and a quantitative mapping grading table for physical accessibility can also be generated separately, thus achieving the invention's objective of "quantifying and tabulating each qualitative indicator separately."

[0062] Based on the above method embodiments, the beneficial effects of the present invention also include: This invention can characterize the dynamic spatial constraints in continuous motion processes. By simulating tool motion, iteratively solving step length, collision detection, and modeling artificial force fields, this invention dynamically analyzes continuous motions such as tool rotation, pulling, extending, and retracting, rather than being limited to single postures or static moments. Therefore, it can more accurately reflect spatial redundancy, interference risks, motion continuity, and operational safety during operations, improving the realism and precision of spatial accessibility assessment.

[0063] This invention facilitates the early identification of maintainability shortcomings during the design phase and guides optimization. It not only outputs maintainability accessibility ratings but also, by combining sensitive parameters, collision locations, space-constrained areas, sources of view obstruction, and access path bottlenecks, further pinpoints key constraints leading to low ratings. This provides direct evidence for adjusting maintenance access dimensions, optimizing structural layouts, selecting tools, improving processes, optimizing work sequences, and ensuring resource allocation, significantly enhancing the value of the assessment results for design optimization and decision support.

[0064] like Figure 2 As shown, a quantitative mapping system for maintenance accessibility includes: The parameter module is used to execute S101; The scenario module is used to execute S102; The quantization module is used to execute S103-S106; The hierarchical module is used to execute S107; The calibration module is used to perform S108 and S109.

[0065] The content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0066] A quantitative mapping device for maintenance accessibility: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a maintenance accessibility quantification mapping method as described above.

[0067] The content of the above method embodiments is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0068] A storage medium storing processor-executable instructions, which, when executed by a processor, are used to implement a maintenance accessibility quantification mapping method as described above.

[0069] The content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0070] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A quantitative mapping method for maintenance accessibility, characterized in that, Includes the following steps: Acquire scene information and generate parameter samples; Based on the parameter samples, a virtual maintenance scenario is reconstructed to obtain a scenario sample; Define visual accessibility metrics, physical accessibility metrics, and spatial accessibility metrics, and evaluate the scene samples to obtain evaluation scores; The evaluation scores are used to classify the students.

2. The quantitative mapping method for maintenance accessibility according to claim 1, characterized in that, The step of acquiring scene information and generating parameter samples specifically includes: Obtain raw information by acquiring information such as the object to be repaired, the repair port, obstacles, tools, human posture, the location of the target component, and the type of operation. Based on the original information, input parameters are defined, and continuous variable sets and discrete variable sets are constructed; Establish probability distribution models for input parameters with different physical properties; Based on the probability distribution model, multiple sets of parameter samples are generated using the Monte Carlo method.

3. The quantitative mapping method for maintenance accessibility according to claim 1, characterized in that, Also includes: Construct a conditional probability matrix to represent the coupling constraints between continuous and discrete variables.

4. The quantitative mapping method for maintenance accessibility according to claim 1, characterized in that, The formula for calculating the visual accessibility index is as follows: in, Indicators of visual accessibility Indicates the evaluation value of the field of view factor. This represents the target attitude factor evaluation value. This indicates the visual comfort assessment value. Indicates the visual work efficiency assessment value. The corresponding weights are given, and the sum of the weights is 1.

5. The quantitative mapping method for maintenance accessibility according to claim 2, characterized in that, The formula for calculating the entity accessibility index is as follows: in, The reference time for the start of the action. The reciprocal of the information processing rate. This is the length of the operation path. The target size.

6. The quantitative mapping method for maintenance accessibility according to claim 1, characterized in that, The spatial accessibility metrics are as follows: in, This represents the average gap value. and This indicates the upper and lower limits of the scale boundaries. This represents the probability of interference.

7. The quantitative mapping method for maintenance accessibility according to claim 1, characterized in that, The step of classifying based on the evaluation score specifically includes: A multidimensional index dataset is constructed based on the evaluation scores, and the quantiles of each index are determined according to the cumulative distribution function. Based on the quantization points, the continuous quantization results are divided into discrete level intervals to obtain the original quantization levels.

8. The quantitative mapping method for maintenance accessibility according to claim 6, characterized in that, Also includes: Expert scores and operator questionnaire scores are collected and weighted together with the original quantitative grades to obtain the final calibration grade.

9. A quantitative mapping system for maintenance accessibility, characterized in that, include: The parameter module is used to acquire scene information and generate parameter samples; The scenario module reconstructs a virtual maintenance scenario based on the parameter samples to obtain scenario samples; The quantification module defines visual accessibility indicators, physical accessibility indicators, and spatial accessibility indicators, and evaluates the scene samples to obtain a comprehensive evaluation. The grading module performs grading based on the comprehensive evaluation.

10. An apparatus, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a method as described in any one of claims 1-8.

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