Part local defect repairing method based on finite element simulation analysis and digital reverse modeling
By combining 3D laser scanning and industrial CT to acquire part data, constructing a finite element analysis model, determining the repair range, and adopting a gradient transition structure design, the problems of inaccurate repair and resource waste in traditional repair methods are solved, achieving efficient and economical repair of local defects in parts.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-14
- Publication Date
- 2026-03-24
AI Technical Summary
Existing technologies for repairing local defects in mechanical parts suffer from inaccurate repair and significant material waste. Especially in high-frequency vibration and corrosive environments, traditional repair methods are prone to causing part deformation and performance degradation, and it is difficult to accurately control the repair range.
By combining 3D laser scanning and industrial CT to acquire surface and internal data of parts, a finite element analysis model is constructed. The repair scope and scheme are determined through simulation analysis. A gradient transition structure is designed and a process table is generated to achieve precise repair.
It achieves precision and consistency in the repair of local defects in parts, reduces resource waste, improves repair efficiency and economy, and ensures that the mechanical properties of the repaired parts are consistent with the original design.
Smart Images
Figure CN121723740A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of mechanical parts repair, and more specifically, to a method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling. Background Technology
[0002] In core equipment sectors such as aerospace, engineering machinery, and automobile manufacturing, mechanical parts are subjected to complex service environments including high-frequency vibration, alternating loads, and corrosive media for extended periods, making them highly susceptible to localized defects such as cracks, pitting, and wear. If these defects are not repaired promptly, they will gradually expand and cause stress concentration, leading to a significant decrease in the load-bearing capacity of the parts. In severe cases, this can even cause equipment downtime, component breakage, and other safety accidents, resulting not only in high maintenance costs but also potentially serious safety hazards.
[0003] Currently, there are various traditional techniques for repairing local defects in mechanical parts, such as welding, thermal spraying, and electroplating. However, these traditional repair processes often involve high-temperature operations, which can easily lead to deformation of the part's substrate, coarse grains, or new microcracks, damaging the part's original mechanical properties. The repair scope and process parameters largely depend on the operator's experience and judgment. For internally hidden defects or parts with complex curved surfaces, it is difficult to accurately control the defect boundaries and repair depth, often resulting in under-repair or over-repair, which affects the repair quality and wastes materials and time.
[0004] To address the aforementioned problems, a technical solution is provided. Summary of the Invention
[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a method for repairing local defects of parts based on finite element simulation analysis and digital reverse modeling, so as to solve the problems mentioned in the background art.
[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling, characterized by the following steps: Step S1: Use a 3D laser scanner to scan the surface of the part to be repaired, obtain point cloud data of the surface of the part to be repaired, and use industrial CT to scan the defect area to obtain the internal 3D morphological data of the defect of the part to be repaired, and obtain the initial 3D data model. Step S2: Gather the initial three-dimensional data model and construct the finite element analysis model; Step S3: Perform mechanical performance simulation analysis on the defect area using a finite element analysis model to obtain stress distribution cloud map, strain concentration area and maximum load-bearing capacity attenuation coefficient around the defect, determine the degree of impact of the defect on the overall performance of the part, and determine the repair scope and repair plan. Step S4: Based on the reverse data and repair scheme of the initial 3D data model, perform defect repair processing on the initial 3D data model.
[0007] In a preferred embodiment, in step S1, a three-dimensional laser scanner is used to perform a full-surface scan of the part to be repaired. During the scanning process, it is necessary to ensure that the scanner and the surface of the part are kept at a stable distance. By continuously moving the scanning device or rotating the part, the outer contour and surface details of the part are collected in all directions, thereby obtaining the surface point cloud data of the part. By using industrial CT to scan the defect area and adjusting the scanning parameters of the CT equipment, including tube voltage, tube current and scanning slice thickness, three-dimensional morphological data of the interior of the defect in the part to be repaired is obtained. This data includes crack length, pit depth, wear thickness and the boundary range between the defect and the substrate. The point cloud data of the surface of the part to be repaired and the three-dimensional morphological data of the interior of the defect are integrated to obtain an initial three-dimensional data model.
[0008] In a preferred embodiment, in step S2, the initial three-dimensional data model is imported into the finite element simulation software, a finite element analysis model containing the defect area is built, the boundary conditions of the model are set, and the constraint positions and constraint types are defined according to the installation method and stress conditions of the parts in the actual equipment.
[0009] In a preferred embodiment, in step S3, a mechanical property simulation analysis is performed on the defect area. The stress distribution around the defect is calculated using the solver of the finite element software, and a stress cloud map is generated to visually show the location and size of the stress concentration area. Analyze the deformation trend in the strain concentration area, assess the degree of deformation of the part under stress, calculate the attenuation coefficient of the maximum load-bearing capacity, quantify the impact of defects on the load-bearing performance of the part, and determine the minimum repair range.
[0010] In a preferred embodiment, a repair scheme is designed based on the results of simulation analysis, including the selection of repair materials, the thickness gradient of the filler layer, welding or spraying process parameters, and the preheating temperature. The feasibility of the repair scheme was verified by simulation. The parameters of the repair scheme were input into the finite element model, and mechanical analysis was performed again to check whether the stress distribution of the repaired parts was uniform and whether the residual stress was within the specified range. If there is stress concentration or excessive residual stress, the repair plan needs to be optimized and adjusted until the performance requirements of the parts are met.
[0011] In a preferred embodiment, in step S4, based on the reverse data and repair scheme of the initial three-dimensional data model, the defect area is segmented in the three-dimensional modeling software, and the model data of the defective part is deleted. Based on the repair area and filling parameters, a three-dimensional model of the repair area is constructed that is seamlessly connected to the part substrate. The model adopts a gradient transition structure, which is divided into a base layer, a transition layer and a surface layer from the bottom of the defect to the surface. The surface roughness is consistent with the original part. Perform Boolean operations on the repair model and the part base model to generate the repaired target model, and export it to CAM software to generate CNC machining paths.
[0012] In a preferred embodiment, when performing repair based on the CNC machining path, if additive manufacturing is used, the repair area is sliced into layers at a preset interval according to the characteristics of the machining parameters. Each slice contains the coordinate values corresponding to the defect, and a first process table is generated. If subtractive repair is adopted, a machining reference surface is established based on the initial three-dimensional data model, with the maximum depth of the defect as the repair starting point and the original part surface as the repair ending point, and a second process table is generated. If it is a composite repair of additive and subtractive manufacturing, a first process table is first generated for the additive manufacturing area, and then a second process table containing compensation values is generated for the composite repair area. The compensation values are determined by the dimensional deviation after additive repair.
[0013] In a preferred embodiment, when estimating the repair cost, a first cost parameter for the additive or subtractive manufacturing process is obtained based on a first process table and preset process cost data, and a second cost parameter is obtained by combining the material usage in the repair area. The two together form the first repair cost. If it is a composite repair, the third cost parameter of the composite process is obtained based on the second process table and the preset process cost data as the second repair cost; By comparing the repair cost with a preset cost threshold, it is determined whether to perform the repair. If the cost exceeds the threshold, a repair diagnostic report is generated; otherwise, the process schedule is executed.
[0014] The technical effects and advantages of the present invention regarding a method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling are as follows: 1. By combining 3D laser scanning with industrial CT, the 3D morphology of surface and internal defects of parts is fully captured, providing comprehensive and accurate raw data for repair; finite element simulation analysis is based on real working conditions to build a model and accurately assess the impact of defects on the mechanical properties of parts, so that the repair scope and scheme design are free from experience dependence, fundamentally solving the problems of incomplete defect identification and blind repair schemes in traditional repair. 2. The repair area adopts a gradient transition structure design to ensure seamless connection and performance matching with the substrate; standardized process tables are generated for different repair processes, clarifying processing parameters and steps, reducing reliance on operational experience, and scientifically controlling the economics of repair through a cost prediction mechanism, ensuring that the mechanical properties of the repaired parts are consistent with the original design, improving repair efficiency, reducing resource waste, and applicable to various complex parts local defect repair scenarios. Attached Figure Description
[0015] Figure 1 This is a flowchart illustrating a method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling, according to the present invention. Detailed Implementation
[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0017] Example 1 Figure 1 This invention presents a method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling, specifically including the following steps: Step S1: Use a 3D laser scanner to scan the surface of the part to be repaired, obtain point cloud data of the surface of the part to be repaired, and use industrial CT to scan the defect area to obtain the internal 3D morphological data of the defect of the part to be repaired, and obtain the initial 3D data model. Step S2: Gather the initial three-dimensional data model and construct the finite element analysis model; Step S3: Perform mechanical performance simulation analysis on the defect area using a finite element analysis model to obtain stress distribution cloud map, strain concentration area and maximum load-bearing capacity attenuation coefficient around the defect, determine the degree of impact of the defect on the overall performance of the part, and determine the repair scope and repair plan. Step S4: Based on the reverse data and repair scheme of the initial 3D data model, perform defect repair processing on the initial 3D data model.
[0018] In step S1, a three-dimensional laser scanner is used to perform a full-surface scan of the part to be repaired. During the scanning process, it is necessary to ensure that the scanner maintains a stable distance from the surface of the part. By continuously moving the scanning device or rotating the part, the outer contour and surface details of the part are collected in all directions, thereby obtaining the surface point cloud data of the part. By using industrial CT to scan the defect area and adjusting the scanning parameters of the CT equipment, including tube voltage, tube current and scanning slice thickness, three-dimensional morphological data of the interior of the defect in the part to be repaired is obtained. This data includes crack length, pit depth, wear thickness and the boundary range between the defect and the substrate. The point cloud data of the surface of the part to be repaired and the three-dimensional morphological data of the interior of the defect are integrated to obtain an initial three-dimensional data model.
[0019] A 3D laser scanner's full-surface scan acquires highly accurate surface point cloud data, accurately reproducing the part's appearance. Meanwhile, industrial CT scans of defect areas penetrate deep into the defect, clearly revealing key information such as crack length, pit depth, wear thickness, and the boundary between the defect and the substrate. Integrating these two types of data to generate an initial 3D data model allows for comparison of the repaired part with the initial 3D data model and the repaired target model after repair. This comprehensive evaluation of the repair effect, considering dimensional accuracy, surface quality, and internal defects, ensures the repaired part meets actual service requirements and guarantees the reliability of the repair.
[0020] In step S2, the initial three-dimensional data model is imported into the finite element simulation software to build a finite element analysis model containing the defect area, set the boundary conditions of the model, and define the constraint positions and constraint types according to the installation method and stress conditions of the parts in the actual equipment.
[0021] After importing the initial 3D data model into the finite element software, the constructed analysis model fully preserves the detailed features of the defect area, ensuring that the morphology, location, and relationship of the defect with the substrate are realistically reproduced in the simulation environment. Boundary conditions set based on the actual installation method and stress conditions of the part, including constraint location and constraint type, can accurately simulate the stress state of the part during service. For example, fixed constraints correspond to the rigid connection between the part and the equipment, making the simulation environment highly consistent with the real working scenario. After repair, a secondary simulation can be performed on the repaired part based on the same boundary conditions and load conditions. The results can be compared with the analysis data before repair to intuitively evaluate the improvement effect of the repair on the mechanical properties of the part, further ensuring the reliability of the repair quality.
[0022] In step S3, a mechanical property simulation analysis is performed on the defect area. The stress distribution around the defect is calculated using the solver of the finite element software, and a stress cloud map is generated to visually show the location and size of the stress concentration area. Analyze the deformation trend in the strain concentration area, assess the degree of deformation of the part under stress, calculate the attenuation coefficient of the maximum load-bearing capacity, quantify the impact of defects on the load-bearing performance of the part, and determine the minimum repair range.
[0023] Based on the simulation analysis results, a repair scheme was designed, including the selection of repair materials, the thickness gradient of the filler layer, welding or spraying process parameters, and the preheating temperature. The feasibility of the repair scheme was verified by simulation. The parameters of the repair scheme were input into the finite element model, and mechanical analysis was performed again to check whether the stress distribution of the repaired parts was uniform and whether the residual stress was within the specified range. If there is stress concentration or excessive residual stress, the repair plan needs to be optimized and adjusted until the performance requirements of the parts are met.
[0024] Stress cloud maps visually present the location and size of stress concentration areas around defects. Deformation trend analysis of strain concentration areas can predict the failure risk of parts under stress. Quantitative calculation of the maximum load-bearing capacity attenuation coefficient clarifies the degree to which defects weaken the load-bearing performance of parts from a numerical perspective. This ensures that the determination of the minimum repair area is no longer based on subjective assumptions but on objective mechanical data, guaranteeing that the repair area covers all risk areas and ensuring a high degree of matching between the mechanical properties of the repair material and the substrate material, avoiding secondary stress caused by differences in material properties. The design of the filler layer thickness gradient achieves a smooth transition between the repair area and the substrate, effectively reducing stress concentration. Optimization of welding or spraying process parameters and preheating temperature ensures the metallurgical bonding strength and residual stress control in the repair area. Simulation-verified repair schemes ensure uniform stress distribution and that residual stress is within a safe range after repair, fundamentally guaranteeing the consistency of the mechanical properties of the repaired part with the original design.
[0025] In step S4, based on the reverse data and repair plan of the initial 3D data model, the defect area is segmented in the 3D modeling software, and the model data of the defective part is deleted. Based on the repair area and filling parameters, a three-dimensional model of the repair area is constructed that is seamlessly connected to the part substrate. The model adopts a gradient transition structure, which is divided into a base layer, a transition layer and a surface layer from the bottom of the defect to the surface. The surface roughness is consistent with the original part. Perform Boolean operations on the repair model and the part base model to generate the repaired target model, and export it to CAM software to generate CNC machining paths.
[0026] When performing repair based on CNC machining path, if additive manufacturing is used, the repair area is sliced into layers at preset intervals according to the characteristics of machining parameters. Each layer of slice data contains the coordinate values corresponding to the defect, and the first process table is generated. If subtractive repair is adopted, a machining reference surface is established based on the initial three-dimensional data model, with the maximum depth of the defect as the repair starting point and the original part surface as the repair ending point, and a second process table is generated. If it is a composite repair of additive and subtractive manufacturing, a first process table is first generated for the additive manufacturing area, and then a second process table containing compensation values is generated for the composite repair area. The compensation values are determined by the dimensional deviation after additive repair.
[0027] When estimating repair costs, the first cost parameter of additive or subtractive manufacturing process is obtained based on the first process table and preset process cost data, and the second cost parameter is obtained by combining the material usage in the repair area. The two together form the first repair cost. If it is a composite repair, the third cost parameter of the composite process is obtained based on the second process table and the preset process cost data as the second repair cost; By comparing the repair cost with a preset cost threshold, it is determined whether to perform the repair. If the cost exceeds the threshold, a repair diagnostic report is generated; otherwise, the process schedule is executed.
[0028] The 3D model of the repair area, constructed based on reverse engineering data and the repair scheme, employs a gradient transition structure to achieve seamless integration with the original part substrate. The surface roughness remains consistent with the original part, ensuring a high degree of fusion between the repair area and the original part. This allows for precise alignment of the layered slicing in additive manufacturing and the setting of the machining reference surface in subtractive repair with the defect location, avoiding dimensional deviations and shape distortions during processing and guaranteeing the dimensional accuracy and appearance consistency of the repaired part.
[0029] For different repair processes, the generated process tables transform abstract repair schemes into specific processing parameters and steps. Additive manufacturing's layered slicing data clearly defines the processing coordinates and material usage for each layer; subtractive manufacturing's processing reference plane and repair start and end points clearly define the processing range; and composite repair's compensation values solve the dimensional matching problem of multi-process integration. This significantly reduces reliance on operator experience and improves the efficiency and consistency of the repair process.
[0030] By calculating the cost parameters and material usage of different process schedules, a repair cost is formed. The repair cost is compared with a preset cost threshold. If the cost exceeds the threshold, a diagnostic report is generated to avoid ineffective investment. If it does not exceed the threshold, the process schedule is executed to advance the repair, thus achieving the economic rationality of part repair.
[0031] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0032] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling, characterized in that, Includes the following steps: Step S1: Use a 3D laser scanner to scan the surface of the part to be repaired, obtain point cloud data of the surface of the part to be repaired, and use industrial CT to scan the defect area to obtain the internal 3D morphological data of the defect of the part to be repaired, and obtain the initial 3D data model. Step S2: Gather the initial three-dimensional data model and construct the finite element analysis model; Step S3: Perform mechanical performance simulation analysis on the defect area using a finite element analysis model to obtain stress distribution cloud map, strain concentration area and maximum load-bearing capacity attenuation coefficient around the defect, determine the degree of impact of the defect on the overall performance of the part, and determine the repair scope and repair plan. Step S4: Based on the reverse data and repair scheme of the initial 3D data model, perform defect repair processing on the initial 3D data model.
2. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 1, characterized in that: In step S1, a three-dimensional laser scanner is used to perform a full-surface scan of the part to be repaired. During the scanning process, it is necessary to ensure that the scanner maintains a stable distance from the surface of the part. By continuously moving the scanning device or rotating the part, the outer contour and surface details of the part are collected in all directions, thereby obtaining the surface point cloud data of the part. By using industrial CT to scan the defect area and adjusting the scanning parameters of the CT equipment, including tube voltage, tube current and scanning slice thickness, three-dimensional morphological data of the interior of the defect in the part to be repaired is obtained. This data includes crack length, pit depth, wear thickness and the boundary range between the defect and the substrate. The point cloud data of the surface of the part to be repaired and the three-dimensional morphological data of the interior of the defect are integrated to obtain an initial three-dimensional data model.
3. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 2, characterized in that: In step S2, the initial three-dimensional data model is imported into the finite element simulation software to build a finite element analysis model containing the defect area, set the boundary conditions of the model, and define the constraint positions and constraint types according to the installation method and stress conditions of the parts in the actual equipment.
4. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 3, characterized in that: In step S3, a mechanical property simulation analysis is performed on the defect area. The stress distribution around the defect is calculated using the solver of the finite element software, and a stress cloud map is generated to visually show the location and size of the stress concentration area. Analyze the deformation trend in the strain concentration area, assess the degree of deformation of the part under stress, calculate the attenuation coefficient of the maximum load-bearing capacity, quantify the impact of defects on the load-bearing performance of the part, and determine the minimum repair range.
5. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 4, characterized in that: Based on the simulation analysis results, a repair scheme was designed, including the selection of repair materials, the thickness gradient of the filler layer, welding or spraying process parameters, and the preheating temperature. The feasibility of the repair scheme was verified by simulation. The parameters of the repair scheme were input into the finite element model, and mechanical analysis was performed again to check whether the stress distribution of the repaired parts was uniform and whether the residual stress was within the specified range. If there is stress concentration or excessive residual stress, the repair plan needs to be optimized and adjusted until the performance requirements of the parts are met.
6. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 5, characterized in that: In step S4, based on the reverse data and repair plan of the initial 3D data model, the defect area is segmented in the 3D modeling software, and the model data of the defective part is deleted. Based on the repair area and filling parameters, a three-dimensional model of the repair area is constructed that is seamlessly connected to the part substrate. The model adopts a gradient transition structure, which is divided into a base layer, a transition layer and a surface layer from the bottom of the defect to the surface. The surface roughness is consistent with the original part. Perform Boolean operations on the repair model and the part base model to generate the repaired target model, and export it to CAM software to generate CNC machining paths.
7. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 6, characterized in that: When performing repair based on CNC machining path, if additive manufacturing is used, the repair area is sliced into layers at preset intervals according to the characteristics of machining parameters. Each layer of slice data contains the coordinate values corresponding to the defect, and the first process table is generated. If subtractive repair is adopted, a machining reference surface is established based on the initial three-dimensional data model, with the maximum depth of the defect as the repair starting point and the original part surface as the repair ending point, and a second process table is generated. If it is a composite repair of additive and subtractive manufacturing, a first process table is first generated for the additive manufacturing area, and then a second process table containing compensation values is generated for the composite repair area. The compensation values are determined by the dimensional deviation after additive repair.
8. The method for repairing local defects in parts based on finite element simulation analysis and digital reverse modeling according to claim 7, characterized in that: When estimating repair costs, the first cost parameter of additive or subtractive manufacturing process is obtained based on the first process table and preset process cost data, and the second cost parameter is obtained by combining the material usage in the repair area. The two together form the first repair cost. If it is a composite repair, the third cost parameter of the composite process is obtained based on the second process table and the preset process cost data as the second repair cost; By comparing the repair cost with a preset cost threshold, it is determined whether to perform the repair. If the cost exceeds the threshold, a repair diagnostic report is generated; otherwise, the process schedule is executed.