Engine disassembly apparatus based on three-dimensional scanning and modeling

Abstract

The application discloses an engine disassembly device based on three-dimensional scanning and modeling, and relates to the field of data processing, comprising: determining a scanning device and a scanning distance, collecting scanning data of an engine, and determining a scanning feature distribution. Based on the scanning feature distribution, feature quantization and scanning data splicing are performed to determine engine scanning data. Based on the engine scanning data, three-dimensional modeling is performed to determine an engine three-dimensional model. According to the engine three-dimensional model, hierarchical weighting calculation is performed to analyze the engine structure, determine a quality evaluation coefficient, and obtain an engine disassembly sequence. According to a disassembly tool, the engine disassembly sequence is combined, disassembly simulation is performed on the engine three-dimensional model, a disassembly scheme is generated, and engine disassembly based on the disassembly scheme is performed. The technical problems of low disassembly efficiency, poor precision and high cost of the engine disassembly scheme in the prior art are solved.

Description

Technical Field

[0001] The present application relates to data processing related fields, and in particular to engine disassembly equipment based on three-dimensional scanning and modeling. Background Art

[0002] In modern industry, engine maintenance and disassembly are complex and critical tasks. Traditional engine disassembly methods often rely on manual experience, requiring significant time and human resources, and are unable to meet the demands for rapid repair or replacement. These methods also suffer from low efficiency, poor precision, and high costs, making them difficult to meet the demands of modern industry for efficient and precise disassembly.

[0003] Therefore, the engine disassembly scheme in the prior art has technical problems of low efficiency, poor precision and high disassembly cost. Summary of the Invention

[0004] This application addresses the technical issues of low efficiency, poor precision, and high costs associated with existing engine disassembly solutions by providing engine disassembly equipment based on 3D scanning and modeling. By analyzing and acquiring the engine disassembly sequence using 3D scanning and modeling technology, a disassembly solution is automatically generated based on the disassembly sequence, achieving efficient engine disassembly, improving disassembly precision, and reducing disassembly costs.

[0005] The present application provides an engine disassembly device based on three-dimensional scanning and modeling, including: a scanning feature distribution determination module, which is used to determine the scanning device and the scanning distance, collect the scanning data of the engine, and determine the scanning feature distribution. An engine scanning data determination module, which is used to perform feature quantification and scanning data splicing based on the scanning feature distribution to determine the engine scanning data. An engine three-dimensional model determination module, which is used to perform three-dimensional modeling based on the engine scanning data to determine the engine three-dimensional model. An engine disassembly sequence acquisition module, which is used to perform hierarchical weighted calculation based on the engine three-dimensional model, analyze the engine structure, determine the quality assessment coefficient, and obtain the engine disassembly sequence. A disassembly plan generation module, which is used to perform disassembly simulation through the engine three-dimensional model based on the disassembly tool and the engine disassembly sequence, generate a disassembly plan, and execute engine disassembly based on the disassembly plan.

[0006] In a possible implementation, the scanning feature distribution determination module is further configured to: determine a scanning matrix for a three-dimensional scan, wherein the scanning matrix comprises scanning devices as matrix rows and engine types as matrix columns, with a one-to-many mapping relationship between the scanning devices and the engine types; construct a scanning distance classifier, attach it to a scanning unit, and enable self-targeting. The scanning unit includes multiple scanning devices. In conjunction with the scanning unit, the scanning data of the engine is collected, and scanning feature analysis and integration of the scanning distance classifier is performed using the scanning matrix as a guide to determine the scanning feature distribution.

[0007] In a possible implementation, the scanning feature distribution determination module is further configured to: determine the minimum distance target based on the scan coverage distance of a neighboring scanning device; locate the spatial proximity scanning feature positions based on the minimum distance target in conjunction with the scanning distance classifier; and determine a spatial scan type distribution based on the minimum distance target. Furthermore, the spatial scan type distribution is added to the scan feature distribution based on the multiple scanning devices of the scanning unit.

[0008] In a possible implementation, the engine disassembly sequence acquisition module is further configured to: determine a standardized engine 3D model based on the engine 3D model, the standardized engine 3D model serving as a reference for the engine 3D model, wherein the standardized engine 3D model includes vector features; perform a primary feature weighting and a primary assembly calculation on the engine scan data based on a mapping relationship between the engine 3D model and the vector features to determine an initial engine index coefficient; and perform a secondary weighting and a secondary assembly calculation on the initial engine index coefficients based on index importance to determine a first quality assessment coefficient.

[0009] In a possible implementation, the engine disassembly sequence acquisition module is further configured to: determine first quality data based on the engine structure; perform a production loss assessment based on the engine production steps to determine second quality data; fit the first quality data and the second quality data to determine a second quality assessment coefficient; and perform a comprehensive calculation of the first quality assessment coefficient and the second quality assessment coefficient to determine the quality assessment coefficient.

[0010] In a possible implementation, the engine disassembly sequence acquisition module is further configured to: determine a derived assessment target and a derived assessment characteristic; and determine an assessment decision method based on the derived assessment characteristic, wherein the derived assessment target includes at least one item; traverse the engine scan data to extract derived correlation features based on the derived assessment target; traverse the derived correlation features, and, based on the derived assessment characteristic, evaluate and determine a derived assessment coefficient, which is added to the quality assessment coefficient.

[0011] In a possible implementation, the engine disassembly sequence acquisition module is further configured to: traverse the quality assessment coefficients to determine quality defects of the engine; match the engine disassembly sequence based on the quality defects to acquire the engine disassembly sequence, wherein the engine disassembly sequence includes the disassembly sequence of the finished engine.

[0012] In a possible implementation, the engine disassembly sequence acquisition module is further configured to: trace the quality defects, locate production nodes and optimize production decisions based on the engine production steps, determine an optimization strategy, and reversely optimize engine production based on the optimization strategy.

[0013] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0014] The engine disassembly equipment based on 3D scanning and modeling provided herein includes: a scanning feature distribution determination module, configured to determine the scanning distance between the scanning device and the engine, collect engine scan data, and determine the scanning feature distribution; an engine scan data determination module, configured to perform feature quantification and scan data splicing based on the scan feature distribution to determine the engine scan data; an engine 3D model determination module, configured to perform 3D modeling based on the engine scan data to determine the engine 3D model; an engine disassembly sequence acquisition module, configured to perform hierarchical weighted calculation based on the engine 3D model, analyze the engine structure, determine the quality assessment coefficient, and obtain the engine disassembly sequence; and a disassembly plan generation module, configured to perform a disassembly simulation using the engine 3D model based on the disassembly tool and the engine disassembly sequence, generate a disassembly plan, and execute the engine disassembly based on the disassembly plan. This solves the technical problems of low efficiency, poor accuracy, and high disassembly costs associated with prior engine disassembly plans. By analyzing and acquiring the engine disassembly sequence through 3D scanning and modeling technology, and automatically generating a disassembly plan based on the disassembly sequence, the disassembly achieves efficient engine disassembly, improves disassembly accuracy, and reduces disassembly costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention are briefly described below. Flowcharts are used in this application to illustrate the operations performed by the devices according to the embodiments of the present application. It should be understood that the preceding or following operations do not necessarily need to be performed in exact order. Instead, various steps may be processed in reverse order or simultaneously, as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0016] Figure 1 A schematic diagram of the structure of an engine disassembly device based on three-dimensional scanning and modeling provided in an embodiment of the present application;

[0017] Figure 2 A schematic diagram of a flow chart of determining the scanning feature distribution by a scanning feature distribution determination module in an engine disassembly device based on three-dimensional scanning and modeling in this application.

[0018] Explanation of reference numerals: scanning feature distribution determining module 11 , engine scanning data determining module 12 , engine three-dimensional model determining module 13 , engine disassembly sequence acquiring module 14 , disassembly plan generating module 15 . DETAILED DESCRIPTION

[0019] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0020] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0021] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, devices, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0022] The embodiment of the present application provides an engine disassembly device based on three-dimensional scanning and modeling, such as Figure 1 As shown, the device includes:

[0023] The scanning feature distribution determination module 11 is used to determine the scanning device and the scanning distance, collect the scanning data of the engine, and determine the scanning feature distribution.

[0024] The engine scan data determination module 12 is configured to perform feature quantification and scan data splicing based on the scan feature distribution to determine the engine scan data.

[0025] The engine three-dimensional model determination module 13 is used to perform three-dimensional modeling based on the engine scanning data to determine the engine three-dimensional model.

[0026] An engine disassembly device based on 3D scanning and modeling includes a scanning feature distribution determination module 11 for determining the scanning device and the scanning distance. The scanning device is a 3D scanner, a device used to capture 3D surface data of an object. It generates high-precision 3D point cloud data by measuring the spatial coordinates of each point on the object's surface. 3D point cloud data contains the 3D coordinate information of points on the object's surface and is typically stored in the form of a point cloud. This point cloud data can be used for various applications, such as 3D modeling, reverse engineering, quality control, and measurement analysis. Specifically, various 3D scanning devices such as laser scanners can be used. The scanning distance is the distance between the scanning device and the engine. The scanning device collects engine scan data to determine the scanning feature distribution. The scanning feature distribution is the engine scan data collected by each acquisition device. Subsequently, the engine scan data determination module 12 performs feature quantization and scan data concatenation on the scanning feature distribution. Specifically, the scanning feature distribution is preprocessed through steps such as denoising, filtering, and downsampling. Feature points are extracted from the preprocessed point cloud data. Key feature points are extracted from the point cloud data using a feature extraction algorithm (such as SIFT or ORB). Feature points are matched to find corresponding feature points in the data collected by each device. The matched feature points are then registered and spliced ​​to generate a complete 3D point cloud model, confirming the engine scan data. Furthermore, the engine 3D model determination module 13 performs 3D modeling based on the engine scan data to determine the engine 3D model.

[0027] Further, such as Figure 2 As shown, the scanning feature distribution determination module 11 is further configured to: determine a scanning matrix for three-dimensional scanning, wherein the scanning matrix comprises scanning devices as matrix rows and engine types as matrix columns, with a one-to-many mapping relationship between scanning devices and engine types; construct a scanning distance classifier and attach it to a scanning unit. The scanning distance classifier can self-set targets, and the scanning unit includes multiple scanning devices. In conjunction with the scanning unit, the engine's scanning data is collected, and scanning feature analysis and integration are performed on the scanning distance classifier using the scanning matrix as a guide to determine the scanning feature distribution.

[0028] Specifically, determining the scanning feature distribution includes: determining a scanning matrix for three-dimensional scanning, wherein the scanning matrix records the mapping relationship between different engine categories and the layout of scanning equipment, wherein the scanning matrix has scanning equipment as matrix rows and engine types as matrix columns, and there is a one-to-many mapping relationship between the scanning equipment and the engine types. Constructing a scanning distance classifier, wherein the scanning distance classifier is constructed based on historical acquisition record data, and extracting the position layout relationship between the engine category and the corresponding scanning equipment under the minimum distance target condition through the historical acquisition record data. Constructing a scanning distance classifier based on the distance layout relationship between all engine categories and corresponding scanning equipment, the scanning distance classifier is used to match the acquisition distribution position of the corresponding acquisition equipment according to the engine category. Adding the constructed scanning distance classifier to the scanning unit, the scanning distance classifier can automatically set the engine target and the corresponding scanning equipment layout position, wherein the layout position includes the distance from the engine when performing the scan and the specific distribution position of the equipment, and the scanning unit includes multiple scanning equipment. In combination with the scanning unit, the scanning data of the engine is collected, and the scanning distance classifier is subjected to scanning feature analysis and integration guided by the scanning matrix to determine the scanning feature distribution, which is the engine scanning data collected by each scanning device at the corresponding collection position.

[0029] Furthermore, the scanning feature distribution determination module 11 is also used to: based on the scanning coverage distance of the adjacent scanning device, take the adjacent scanning device as the minimum distance target. Based on the minimum distance target, combine the scanning distance classifier to perform spatial adjacent scanning feature position positioning, and combine to determine the spatial scanning type distribution. Combined with the multiple scanning devices of the scanning unit, the spatial scanning type distribution is added to the scanning feature distribution. The scanning coverage distance of the adjacent scanning device is collected. The scanning coverage distance of the adjacent scanning device is the scanning coverage distance for scanning engine data. Based on the scanning coverage distance of the adjacent scanning device, take the adjacent scanning device as the minimum distance target. The minimum distance target is the minimum coverage distance of the engine with the best scanning effect when the scanning device is deployed. Based on the minimum distance target, combine the scanning distance classifier to perform spatial adjacent scanning feature position positioning, determine the distribution position of each scanning device, and determine the spatial scanning type distribution, that is, the distribution position of each device, according to the distribution position combination. Finally, combined with the multiple scanning devices of the scanning unit, the spatial scanning type distribution is added to the scanning feature distribution.

[0030] The engine disassembly sequence acquisition module 14 is used to perform hierarchical weighted calculation based on the three-dimensional engine model, analyze the engine structure, determine the quality assessment coefficient, and acquire the engine disassembly sequence.

[0031] The disassembly plan generating module 15 is configured to perform disassembly simulation using the engine three-dimensional model according to the disassembly tool and the engine disassembly sequence, generate a disassembly plan, and execute engine disassembly based on the disassembly plan.

[0032] The engine disassembly sequence acquisition module 14 performs a hierarchical weighted calculation based on the three-dimensional engine model, analyzes the engine structure, and determines a quality assessment coefficient. Based on the quality assessment coefficient, the engine disassembly sequence is acquired. Finally, based on the acquired engine disassembly sequence, the disassembly plan generation module 15 acquires disassembly tools based on a database of disassembly tools. The database contains information such as the functions, dimensions, and applicable scenarios of all tools included in the disassembly execution equipment. The disassembly execution equipment is composed of multiple robotic arms. In conjunction with the engine disassembly sequence, a disassembly simulation is performed based on the three-dimensional engine model and the disassembly tools. This disassembly simulation can be performed using three-dimensional modeling software, such as CAD or SolidWorks, to complete a disassembly simulation based on the disassembly sequence. Based on the disassembly simulation results, the modeling software coordinates are matched with the coordinates of the disassembly execution equipment to generate a disassembly plan, and the engine disassembly based on the disassembly plan is executed. This solves the technical problems of low efficiency, poor accuracy, and high disassembly costs in existing engine disassembly plans. The engine disassembly sequence is analyzed and obtained through 3D scanning and modeling technology, and a disassembly plan is automatically generated based on the disassembly sequence, thereby achieving efficient engine disassembly, improving disassembly accuracy, and reducing disassembly costs.

[0033] Furthermore, the engine disassembly sequence acquisition module 14 is further configured to: determine a standardized engine 3D model based on the engine 3D model, wherein the standardized engine 3D model serves as a reference for the engine 3D model, wherein the standardized engine 3D model includes vector features; perform a primary feature weighting and a primary assembly calculation on the engine scan data based on a mapping relationship between the engine 3D model and the vector features to determine an initial engine index coefficient; and perform a secondary weighting and a secondary assembly calculation on the initial engine index coefficients based on index importance to determine a first quality assessment coefficient.

[0034] According to the engine 3D model obtained by scanning, the 3D model is aligned and scaled with the preset standard engine model. For example, the 3D model and the standard engine model are scaled in equal proportions, and the side view of the 3D model is aligned with the side view of the standard engine model to obtain the side view of the scaled 3D model. Figure 1A standardized 3D engine model is determined. A standardized 3D engine model is a 3D model with a unified reference standard, serving as a benchmark for subsequent feature weighting and calculation. The standardized model includes vector features, such as the importance, size, and location of specific components. Based on the mapping relationship between the 3D engine model and the vector features, the point cloud features in the scanned data are mapped to the vector features of the standardized model to determine the corresponding position and attributes of each point cloud feature in the standardized model. Each vector feature includes initially set index parameters, which are predefined by the operator and reflect the importance of each component. Feature weighting and assembly calculation are performed on the engine scan data. Each feature is assigned a weight based on its relative importance. For example, key engine components (such as the cylinder block and piston) are assigned higher weights, while less important components (such as bolts and gaskets) are assigned lower weights. The weighted features are then weighted and summed to complete the assembly calculation of the index coefficients for each vector feature, thereby determining the initial engine index coefficient. Furthermore, the initial engine index coefficients are traversed, and secondary weighting and secondary assembly calculation are performed based on the index importance to determine a first quality assessment coefficient.

[0035] Furthermore, the engine disassembly sequence acquisition module 14 is further configured to: determine first quality data based on the engine structure; perform production loss assessment based on the engine production steps to determine second quality data; fit the first quality data and the second quality data to determine a second quality assessment coefficient; and perform a comprehensive calculation of the first quality assessment coefficient and the second quality assessment coefficient to determine the quality assessment coefficient.

[0036] Determining the quality assessment coefficient includes: determining first quality data based on the engine structure, where the first quality data is a recorded initial quality standard parameter for a part. A longer design life of a part corresponds to a higher initial quality standard parameter value. For example, a cylinder with a design service life of 20 years corresponds to an initial quality standard parameter value of 200, and a drive belt with a design service life of 5 years corresponds to an initial quality standard parameter value of 50. Subsequently, interactively analyzing the production steps of the engine, determining production losses during the production steps, performing a production loss assessment, and obtaining a production loss ratio, thereby determining second quality data, where the second quality data is 1 minus the production loss ratio. Fitting the first quality data and the second quality data, multiplying the two, determines a second quality assessment coefficient. A comprehensive calculation is performed on the first and second quality assessment coefficients, where the comprehensive calculation can be performed using a weighted summation method. The specific weight setting can be set based on the preferences of professional technicians to determine the quality assessment coefficient.

[0037] Furthermore, the engine disassembly sequence acquisition module 14 is further configured to determine a derived evaluation target and a derived evaluation characteristic, and determine an evaluation decision method in combination with the derived evaluation characteristic, wherein the derived evaluation target includes at least one item.

[0038] Based on the derived evaluation target, the engine scan data is traversed to extract derived correlation features.

[0039] The derived association features are traversed, and the derived evaluation characteristics are combined to determine the derived evaluation coefficient, which is added to the quality evaluation coefficient.

[0040] The determination of the quality assessment coefficient also includes: determining a derived assessment target and determining a derived assessment characteristic, wherein the derived assessment target determines at least one derived assessment target based on the specific usage scenario and performance requirements of the engine. For example, durability, fatigue resistance, thermal stability, etc. The corresponding assessment characteristics are determined according to the derived assessment target. For example, for durability, the assessment characteristics include the design life of the parts, etc. The assessment decision method is determined in combination with the derived assessment characteristics. Taking durability as an example, the corresponding assessment decision method is the design life of each part. Further, based on the derived assessment target, the engine scanning data is traversed to extract derived associated features. The derived associated features are features that are correlated with the derived assessment target. The features can be specific part objects, associated parts, etc. that are correlated with the derived assessment target. The derived associated features are traversed, and in combination with the derived evaluation characteristics, a derived evaluation coefficient is evaluated to determine the derived evaluation coefficient. That is, according to the parts contained in the derived associated features, the parts are evaluated based on the derived evaluation characteristics. The specific evaluation process can be carried out by comparing the standard values ​​to obtain the difference between the part characteristics and the standard part characteristic values. Taking durability as an example, the difference between the design life of the part and the design life of the standard part is obtained during the evaluation to obtain the derived evaluation coefficient and add it to the quality evaluation coefficient.

[0041] Furthermore, the engine disassembly sequence acquisition module 14 is further configured to: traverse the quality assessment coefficients to determine the quality defects of the engine, match the engine disassembly sequence based on the quality defects, and acquire the engine disassembly sequence, wherein the engine disassembly sequence includes the disassembly sequence of the finished engine.

[0042] Obtaining the engine disassembly order includes traversing the quality assessment coefficients to determine the engine's quality defects, where the engine's quality defects are parts whose quality assessment coefficients are less than or equal to a corresponding quality defect threshold, where the quality defect threshold is the minimum quality assessment coefficient when a quality defect exists. Subsequently, the engine disassembly order is matched based on the deviation ratio between each quality assessment coefficient and the corresponding quality defect threshold, sorted by deviation ratio. The higher the deviation ratio sorting result, the higher the disassembly priority. Based on the sorting results, the engine disassembly order is obtained, where the engine disassembly order includes the order in which the finished engine is disassembled.

[0043] Furthermore, the engine disassembly sequence acquisition module 14 is further configured to: trace the quality defects, locate production nodes and optimize production decisions based on the engine production steps, determine an optimization strategy, and reversely optimize the engine production based on the optimization strategy.

[0044] Based on the quality defect big data, the source of the quality defect is traced to obtain the specific cause of the quality defect. The production node location corresponding to the engine production step is determined based on the production process. The production decision optimization is completed and the optimization strategy is determined. The optimization decision is obtained through analysis by professional technicians. Based on the optimization strategy, the engine production optimization is reversed.

[0045] The engine disassembly equipment based on 3D scanning and modeling provided in an embodiment of the present application includes: a scanning feature distribution determination module for determining the scanning distance between the scanning device and the engine, collecting engine scan data, and determining the scanning feature distribution; an engine scan data determination module for performing feature quantification and scan data splicing based on the scan feature distribution to determine the engine scan data; an engine 3D model determination module for performing 3D modeling based on the engine scan data to determine the engine 3D model; an engine disassembly sequence acquisition module for performing hierarchical weighted calculation based on the engine 3D model, analyzing the engine structure, determining the quality assessment coefficient, and obtaining the engine disassembly sequence; and a disassembly plan generation module for performing a disassembly simulation using the engine 3D model based on the disassembly tool and the engine disassembly sequence, generating a disassembly plan, and executing the engine disassembly based on the disassembly plan. This solves the technical problems of low efficiency, poor accuracy, and high disassembly costs associated with prior art engine disassembly plans. By analyzing and acquiring the engine disassembly sequence through 3D scanning and modeling technology, and automatically generating a disassembly plan based on the disassembly sequence, the disassembly achieves efficient engine disassembly, improves disassembly accuracy, and reduces disassembly costs.

[0046] The above specific embodiments do not constitute a limitation to the scope of protection of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application should be included in the scope of protection of this application. In some cases, the actions or steps recorded in this application can be performed in an order different from that in the embodiments and can still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. Engine disassembly equipment based on 3D scanning and modeling, characterized by: include: A scanning feature distribution determination module is used to determine the scanning device and the scanning distance, collect the scanning data of the engine, and determine the scanning feature distribution; An engine scan data determination module, configured to perform feature quantification and scan data splicing based on the scan feature distribution to determine the engine scan data; An engine three-dimensional model determination module, configured to perform three-dimensional modeling based on the engine scanning data to determine the engine three-dimensional model; An engine disassembly sequence acquisition module is used to perform hierarchical weighted calculation based on the three-dimensional engine model, analyze the engine structure, determine the quality assessment coefficient, and obtain the engine disassembly sequence; a disassembly plan generating module, configured to perform a disassembly simulation using the three-dimensional engine model according to the disassembly tool and the engine disassembly sequence, generate a disassembly plan, and execute engine disassembly based on the disassembly plan; The hierarchical weighting calculation includes: Determining a standardized engine three-dimensional model based on the engine three-dimensional model, wherein the standardized engine three-dimensional model is a reference for the engine three-dimensional model, wherein the standardized engine three-dimensional model includes vector features; Based on the mapping relationship between the three-dimensional engine model and the vector features, performing a feature weighting and an assembly calculation on the engine scanning data to determine an initial engine index coefficient; Traversing the initial engine index coefficients, performing secondary weighting and secondary assembly calculation based on index importance, and determining a first quality assessment coefficient; Determining the quality assessment coefficient includes: determining first quality data based on the engine structure; Interacting with the production steps of the engine, performing production loss assessment, and determining second quality data; fitting the first quality data and the second quality data to determine a second quality assessment coefficient; Performing a comprehensive calculation on the first quality assessment coefficient and the second quality assessment coefficient to determine the quality assessment coefficient; The obtaining of the engine disassembly sequence includes: Traversing the quality assessment coefficients to determine the quality defects of the engine; An engine disassembly sequence is matched according to the quality defects to obtain the engine disassembly sequence, wherein the engine disassembly sequence includes a disassembly sequence of a finished engine.

2. The engine disassembly equipment based on three-dimensional scanning and modeling according to claim 1, characterized in that: The determining of the scanning feature distribution includes: Determine a scanning matrix for three-dimensional scanning, wherein the scanning matrix has scanning devices as matrix rows and engine types as matrix columns, and there is a one-to-many mapping relationship between the scanning devices and the engine types; Constructing a scanning distance classifier and adding it to a scanning unit, wherein the scanning distance classifier can perform self-targeting, and the scanning unit includes multiple scanning devices; In combination with the scanning unit, the scanning data of the engine is collected, and the scanning distance classifier is subjected to scanning feature analysis and integration with the scanning matrix as a guide to determine the scanning feature distribution.

3. The engine disassembly equipment based on three-dimensional scanning and modeling according to claim 2, characterized in that: The determining of the scanning feature distribution further includes: According to the scanning coverage distance of the adjacent scanning device, the adjacent scanning device is used as the minimum distance target; Based on the minimum distance target, the spatial proximity scanning feature position is located in combination with the scanning distance classifier, and the spatial scanning type distribution is determined in combination; In combination with a plurality of scanning devices of the scanning unit, the spatial scan type distribution is added to the scan feature distribution.

4. The engine disassembly equipment based on three-dimensional scanning and modeling according to claim 1, characterized in that: The determining of the quality assessment coefficient further includes: Determining a derived evaluation target and a derived evaluation characteristic, and determining an evaluation decision method in combination with the derived evaluation characteristic, wherein the derived evaluation target includes at least one item; Based on the derived evaluation target, traversing the engine scan data to extract derived correlation features; The derived association features are traversed, and the derived evaluation characteristics are combined to determine the derived evaluation coefficient, which is added to the quality evaluation coefficient.

5. The engine disassembly equipment based on three-dimensional scanning and modeling according to claim 1, characterized in that: The obtaining of the engine disassembly sequence further includes: Trace the quality defects to their source, locate production nodes and optimize production decisions based on the engine production steps, and determine the optimization strategy; Based on the optimization strategy, the production optimization of the engine is performed in reverse.

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