Body-in-white electrophoresis line dynamic simulation modeling method and system

Abstract

The invention relates to the technical field of simulation modeling, and particularly discloses a body-in-white electrophoresis line dynamic simulation modeling method and system, and the method comprises the steps: building a body-in-white electrophoresis line initial scene static model; determining dynamic process parameters of each process in the body-in-white electrophoresis line scene based on the body-in-white parameters of the target body-in-white; on the basis of the body-in-white parameters and the dynamic process parameters of each process, common motion parameters of all common motion anchor points in the body-in-white electrophoresis line initial scene static model are determined; determining automatic parameters of all automatic anchor points in the body-in-white electrophoresis line initial scene static model based on common moving parameters of all common moving anchor points in the body-in-white electrophoresis line initial scene static model; generating a body-in-white electrophoresis line dynamic simulation model based on the body-in-white electrophoresis line scene static model, the automatic parameters of all the automatic anchor points and the common moving parameters of all the common moving anchor points; the method is used for ensuring the accuracy and continuity of the dynamic simulation of the body-in-white electrophoresis line.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation modeling, and in particular to a method and system for dynamic simulation modeling of a body-in-white electrophoresis line. Background Art

[0002] At present, in the BIW electrophoresis line, events such as BIW arrival, BIW spraying, and BIW entering the tank are all discrete events. They trigger state changes at a specific time point, and the occurrence of each event will trigger a series of operation processes to complete the pre-treatment electrophoresis process. Therefore, the BIW electrophoresis line can be regarded as a discrete event system. Modeling and simulating the BIW electrophoresis line from the perspective of discrete events helps to understand and optimize the dynamic changes and event triggering in the entire pre-treatment electrophoresis process, provide reliable decision support for engineers and enterprise managers, and help analyze and improve the efficiency and quality of the BIW electrophoresis line.

[0003] However, when the BIW passes through the processing workshop of each process of the electrophoretic line, it is necessary to import the 3D model of the BIW after the previous process and superimpose it on the processing workshop of each process, and interact with the components that perform the process processing tasks in the processing workshop. In order to simulate and model this dynamic process, it is not enough to simply superimpose the BIW model with the workshop model. This simulation modeling method cannot accurately restore the details of the dynamic process of the BIW when it is processed in the process workshop, and it is difficult to ensure the continuity and accuracy of the simulated BIW electrophoretic line dynamic model.

[0004] Therefore, the present invention proposes a body-in-white electrophoresis line dynamic simulation modeling method and system. Summary of the invention

[0005] The present invention provides a dynamic simulation modeling method and system for a body-in-white electrophoresis line, which is used to select all public anchor points and automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, and based on the public parameters of all public anchor points and the automatic parameters of all automatic anchor points, perform dynamic simulation generation on the basis of the static model of the body-in-white electrophoresis line scene, thereby ensuring the accuracy and continuity of the dynamic simulation of the body-in-white electrophoresis line, and can provide reliable support for the subsequent understanding and optimization of dynamic changes and event triggering in the entire pre-treatment electrophoresis process and related production decisions.

[0006] The present invention provides a body-in-white electrophoresis line dynamic simulation modeling method, comprising: S1: Build a static model of the initial scene of the body-in-white electrophoresis line; S2: Determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; S3: Based on the body-in-white parameters and the dynamic process parameters of each process, determine the common parameters of all common anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S4: determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S5: Generate a dynamic simulation model of the BIW electrophoresis line based on the static model of the BIW electrophoresis line scene, the automatic parameters of all automatic anchor points, and the dynamic parameters of all dynamic anchor points.

[0007] Preferably, the BIW electrophoresis line dynamic simulation modeling method, S2: determining the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW, comprises: Obtaining body-in-white parameters of at least one target body-in-white; The BIW electrophoresis standard is retrieved based on the BIW parameters of each target BIW, and the dynamic process parameters of each process of each target BIW in the BIW electrophoresis line scene are obtained.

[0008] Preferably, the body-in-white electrophoresis line dynamic simulation modeling method, S3: based on the body-in-white parameters and the dynamic process parameters of each process, determining the public dynamic parameters of all public dynamic anchor points in the static model of the body-in-white electrophoresis line initial scene, including: S301: Determine a process scene static model of each process in the initial scene static model of the body-in-white electrophoresis line; S302: based on the body-in-white parameters and the dynamic process parameters of each process, determining the anchor point sequence of each process in the process scene static model of each process in turn; S303: Determine all common anchor points of each process in the anchor point sequence of each process, and determine common parameters of all common anchor points of each process.

[0009] Preferably, the body-in-white electrophoresis line dynamic simulation modeling method, S302: based on the body-in-white parameters and the dynamic process parameters of each process, sequentially determining the anchor point sequence of each process in the process scene static model of each process, comprises: Based on the dynamic process parameters of each process, all dynamic components of each process and original dynamic parameters of each dynamic component are determined; Determine the component initial state model of each dynamic component of each process in the process scenario static model of each process; Based on the body-in-white parameters, the starting body parameters of each process are predicted and simulated; Based on the starting body parameters of each process, all anchor points of the corresponding process are selected in the component initial state model of each dynamic component of each process; Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated; According to the principle of the influence coefficient between the anchor point and the target body-in-white from large to small, all the anchor points of each process are sorted to obtain the anchor point sequence of each process.

[0010] Preferably, the BIW electrophoresis line dynamic simulation modeling method evaluates the influence coefficient between each anchor point of each process and the target BIW based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, including: Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the combined dynamic parameters between the target body-in-white and each dynamic component of each process are determined; Generate a process dynamic model for each process based on the combined action dynamic parameters between the target body-in-white and each dynamic component of each process and the process scenario static model of each process; Based on the process dynamic model of each process, a shortest distance change trend diagram between each anchor point of each process and the target body-in-white is determined as a first trend diagram of each anchor point of each process, and at the same time, a distance change trend diagram between each anchor point of each process and the physical center of the target body-in-white is determined as a second trend diagram of each anchor point of each process; Based on the first trend graph and the second trend graph of each anchor point of each process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated.

[0011] Preferably, the dynamic simulation modeling method of the body-in-white electrophoresis line evaluates the influence coefficient between each anchor point of each process and the target body-in-white based on the first trend graph and the second trend graph of each anchor point of each process, including: Based on the first trend graph and the second trend graph of each anchor point of each process, the shortest distance between each anchor point of each process and the target body-in-white is determined as the first shortest distance of each anchor point of each process, and the average rate of change of the trend in the first trend graph is determined as the first rate of change of each anchor point of each process, and at the same time, the shortest distance between each anchor point of each process and the physical center of the target body-in-white is determined as the second shortest distance of each anchor point of each process, and the average rate of change of the trend in the second trend graph is determined as the second rate of change of each anchor point of each process; The weighted sum of the reciprocal of the first shortest distance and the reciprocal of the first change rate of each anchor point of each process is used as the first sub-influence coefficient between each anchor point of each process and the target body-in-white, and the weighted sum of the reciprocal of the second shortest distance and the reciprocal of the second change rate of each anchor point of each process is used as the second sub-influence coefficient between each anchor point of each process and the target body-in-white; The sum of the first sub-influence coefficient and the second sub-influence coefficient between each anchor point of each process and the target body-in-white is regarded as the influence coefficient between each anchor point of each process and the target body-in-white.

[0012] Preferably, the body-in-white electrophoresis line dynamic simulation modeling method, S303: determining all common anchor points of each process in the anchor point sequence of each process, and determining common parameters of all common anchor points, including: All anchor points in the anchor point sequence of each process whose influence coefficient with the target body-in-white is not less than a preset influence coefficient threshold are regarded as all the common anchor points of each process; Keep the sorting order of all common anchor points of each process in the anchor point sequence of the corresponding process to obtain the common anchor point sequence of each process; Based on the process dynamic model of each process, the common parameters of all common anchor points in the common anchor point sequence of each process are determined.

[0013] Preferably, the body-in-white electrophoresis line dynamic simulation modeling method, S4: based on the public dynamic parameters of all public dynamic anchor points in the body-in-white electrophoresis line initial scene static model, determine the automatic parameters of all automatic anchor points in the body-in-white electrophoresis line initial scene static model, including: In the static model of the initial scene of the body-in-white electrophoresis line, a partial reference model of each automatic anchor point is determined; All the public anchor points in the initial state of the corresponding partial reference model in the static model of the initial scene of the body-in-white electrophoresis line are regarded as all the reference public anchor points of the corresponding automatic anchor points, and the three-dimensional constraint relationship between the corresponding automatic anchor point and each corresponding reference public anchor point is determined based on the partial reference model; Based on the static model of the initial scene of the body-in-white electrophoresis line, the common parameters of all common anchor points in each process and the three-dimensional constraint relationship between each automatic anchor point and each corresponding reference common anchor point, the automatic parameters of each automatic anchor point are determined.

[0014] Preferably, the body-in-white electrophoresis line dynamic simulation modeling method, S5: based on the body-in-white electrophoresis line scene static model and the automatic parameters of all automatic anchor points and the public parameters of all public anchor points, generating a body-in-white electrophoresis line dynamic simulation model, including: The static model of the white car electrophoresis line scene, the automatic parameters of all automatic anchor points, and the public parameters of all public anchor points are superimposed in the same frame to obtain a superimposed dynamic simulation model; The neighborhood of the superimposed position in each frame of the superimposed static simulation model is sequentially smoothed to obtain a dynamic simulation model of the electrophoresis line of the body in white.

[0015] The present invention provides a body-in-white electrophoresis line dynamic simulation modeling system, which is applied to the body-in-white electrophoresis line dynamic simulation modeling method described in any one of Embodiments 1 to 9, comprising: Model building module, used to build the static model of the initial scene of the body-in-white electrophoresis line; A process parameter determination module is used to determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; A public dynamic parameter determination module is used to determine the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the body-in-white parameters and the dynamic process parameters of each process; An automatic parameter determination module, for determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; The dynamic simulation generation module is used to generate a dynamic simulation model of the body-in-white electrophoresis line based on the static model of the body-in-white electrophoresis line scene and the automatic parameters of all automatic anchor points and the dynamic parameters of all dynamic anchor points.

[0016] The beneficial effects of the present invention compared to the prior art are as follows: by selecting all the public anchor points and automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, and based on the public parameters of all the public anchor points and the automatic parameters of all the automatic anchor points, dynamic simulation generation is performed on the basis of the static model of the body-in-white electrophoresis line scene, thereby ensuring the accuracy and continuity of the dynamic simulation of the body-in-white electrophoresis line, and providing reliable support for the subsequent understanding and optimization of the dynamic changes and event triggering in the entire pre-treatment electrophoresis process and related production decisions.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0018] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a flow chart of a dynamic simulation modeling method of a body-in-white electrophoresis line in an embodiment of the present invention; Figure 2 It is a schematic diagram of the process flow of the body-in-white electrophoresis line in an embodiment of the present invention; Figure 3 is a flowchart of a specific execution method of step S3 in an embodiment of the present invention; Figure 4 Schematic diagram of the internal functional modules of the body-in-white electrophoresis line dynamic simulation modeling system in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0021] Example 1 The present invention provides a dynamic simulation modeling method for a body-in-white electrophoresis line, referring to Figure 1 and 2 ,include: S1: Build a static model of the initial scene of the body-in-white electrophoresis line; S2: Determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; S3: Based on the body-in-white parameters and the dynamic process parameters of each process, determine the common parameters of all common anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S4: determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S5: Generate a dynamic simulation model of the BIW electrophoresis line based on the static model of the BIW electrophoresis line scene, the automatic parameters of all automatic anchor points, and the dynamic parameters of all dynamic anchor points.

[0022] In this embodiment, the static model of the initial scene of the BIW electrophoresis line is a static three-dimensional model representing the electrophoresis line in an initial state (when no process is performed on the BIW).

[0023] In this embodiment, the target BIW is a BIW that needs to use the BIW electrophoresis line dynamic simulation modeling method in this embodiment to simulate a dynamic model of the complete process of being processed by the electrophoresis line.

[0024] In this embodiment, the body-in-white parameters include parameters such as the body-in-white model or three-dimensional dimensions that affect its performance during dynamic simulation modeling.

[0025] In this embodiment, reference Figure 2 The processes in the body-in-white electrophoresis line scene include, for example, pry replacement, locking device, torrent spray washing, pre-degreasing, ..., cathode electrophoresis, ..., electrophoresis polishing and other processes.

[0026] In this embodiment, the dynamic process parameters include all dynamic components that perform process processing in each process, all processing actions performed by each dynamic component, and the running time and action path corresponding to each action, etc., which represent the dynamic form of the dynamic component in the process of completing the process processing.

[0027] In this embodiment, the movable anchor point is a position point whose distance from the target body-in-white continues to be relatively small during the corresponding process and has moved compared to the initial state, such as a position point in direct contact with the target body-in-white in an elevator, or a position point in direct contact with the target body-in-white in a robotic arm.

[0028] In this embodiment, the public parameters of the public anchor point are parameters that represent the relative movement position of the public anchor point in the corresponding process workshop during the overall dynamic process when the dynamic component completes all process processing steps of the corresponding process. It can also be understood as the dynamic movement path of the anchor point including time in the overall dynamic process.

[0029] In this embodiment, the automatic anchor point is a position point that is relatively far away from the target body in white during the processing of the corresponding process and has moved compared to the initial state, such as the remaining position points in the elevator except the position points that are in direct contact with the target body in white, or the position points in the robot arm except the position points that are in direct contact with the target body in white.

[0030] In this embodiment, the automatic parameters of the automatic anchor point are parameters that represent the relative movement position of the automatic anchor point in the corresponding process workshop during the overall dynamic process when the dynamic component completes all process processing steps of the corresponding process. It can also be understood as the dynamic movement path of the anchor point including time in the overall dynamic process.

[0031] In this embodiment, the BIW electrophoresis line dynamic simulation model is a dynamic three-dimensional model representing the three-dimensional form of the target BIW during the complete dynamic process when it is sequentially processed by all process workshops of the electrophoresis line.

[0032] The beneficial effects of the above technology are: by selecting all the public anchor points and automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, and based on the public parameters of all the public anchor points and the automatic parameters of all the automatic anchor points, dynamic simulation generation is performed on the basis of the static model of the body-in-white electrophoresis line scene, thereby ensuring the accuracy and continuity of the dynamic simulation of the body-in-white electrophoresis line, and providing reliable support for the subsequent understanding and optimization of the dynamic changes and event triggering in the entire pre-treatment electrophoresis process and related production decisions.

[0033] Embodiment 2: Based on Example 1, a dynamic simulation modeling method for a body-in-white electrophoresis line, S2: determining dynamic process parameters of each process in a body-in-white electrophoresis line scene based on body-in-white parameters of a target body-in-white, comprising: Obtaining body-in-white parameters of at least one target body-in-white; The BIW electrophoresis standard is retrieved based on the BIW parameters of each target BIW, and the dynamic process parameters of each process of each target BIW in the BIW electrophoresis line scene are obtained.

[0034] In this embodiment, the BIW electrophoresis standard includes a corresponding list of dynamic process parameters of each process of the BIW with different preset BIW parameters in the BIW electrophoresis line scenario.

[0035] The beneficial effect of the above technology is that the dynamic process parameters of each process of each target body-in-white in the body-in-white electrophoresis line scene are accurately determined.

[0036] Example 3 Based on Example 1, the dynamic simulation modeling method of the body-in-white electrophoresis line, S3: based on the body-in-white parameters and the dynamic process parameters of each process, determine the public parameters of all public anchor points in the static model of the initial scene of the body-in-white electrophoresis line, refer to Figure 3 ,include: S301: Determine a process scene static model of each process in the initial scene static model of the body-in-white electrophoresis line; S302: based on the body-in-white parameters and the dynamic process parameters of each process, determining the anchor point sequence of each process in the process scene static model of each process in turn; S303: Determine all common anchor points of each process in the anchor point sequence of each process, and determine common parameters of all common anchor points of each process.

[0037] In this embodiment, the process scene static model represents a three-dimensional model of the static state of the process workshop of each process when it is in a state scene ready to perform process processing on the body in white.

[0038] The beneficial effects of the above technology are: completing the construction of the process scene static model of each process, completing the generation of the anchor point sequence of each process, and realizing the determination of all the common anchor points and their common parameters of each process.

[0039] Embodiment 4: Based on Example 3, the body-in-white electrophoresis line dynamic simulation modeling method, S302: based on the body-in-white parameters and the dynamic process parameters of each process, sequentially determining the anchor point sequence of each process in the process scene static model of each process, includes: Based on the dynamic process parameters of each process, all dynamic components of each process and original dynamic parameters of each dynamic component are determined; Determine the component initial state model of each dynamic component of each process in the process scenario static model of each process; Based on the body-in-white parameters, the starting body parameters of each process are predicted and simulated; Based on the starting body parameters of each process, all anchor points of the corresponding process are selected in the component initial state model of each dynamic component of each process; Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated; According to the principle of the influence coefficient between the anchor point and the target body-in-white from large to small, all the anchor points of each process are sorted to obtain the anchor point sequence of each process.

[0040] In this embodiment, all dynamic components of each process are components that will move when the process of the process is completed, such as the mobile spray head of the flood spray cleaning workshop.

[0041] In this embodiment, the original dynamic parameters of the dynamic component are parameters that represent the dynamic form of the dynamic component when completing the corresponding process processing action without considering the interaction between the target body in white and the dynamic component, such as parameters that represent its moving position in the process workshop.

[0042] In this embodiment, the component initial state model of the dynamic component is a three-dimensional model representing the static state of the dynamic component when it is ready to be processed on the body-in-white.

[0043] In this embodiment, based on the body-in-white parameters, the starting body parameters of each process are predicted and simulated as follows: Based on the body-in-white parameters, the three-dimensional dimensions of the target body-in-white after each process (i.e. before entering the corresponding next process) and other parameters that affect its performance during dynamic simulation modeling are predicted as the starting body parameters of the corresponding next process; Among them, the actual body parameters of the first process are the body-in-white parameters.

[0044] In this embodiment, all anchor points of a process are all position points that move in a process workshop during the processing of the process, such as position points on the surface of a robot arm, a lift or a rotary machine.

[0045] In this embodiment, the component parameters of the dynamic component are parameters indicating the three-dimensional size of the dynamic component.

[0046] In this embodiment, the influence coefficient between the anchor point and the target BIW is a value that is proportional to the degree to which the distance between the anchor point and the target BIW continues to be relatively small during the processing of the corresponding process.

[0047] The beneficial effects of the above technology are: realizing the determination of all dynamic components of each process and the original dynamic parameters of each dynamic component, and realizing the construction of the component initial state model of each dynamic component of each process, and predicting and simulating the starting body parameters of each process, and completing the selection of all anchor points of all processes, and realizing the accurate evaluation of the influence coefficient between each anchor point of each process and the target body-in-white, and then realizing the generation of the anchor point sequence of each process based on the influence coefficient between the anchor point and the target body-in-white.

[0048] Example 5 On the basis of Example 4, the BIW electrophoresis line dynamic simulation modeling method evaluates the influence coefficient between each anchor point of each process and the target BIW based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, including: Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the combined dynamic parameters between the target body-in-white and each dynamic component of each process are determined; Generate a process dynamic model for each process based on the combined action dynamic parameters between the target body-in-white and each dynamic component of each process and the process scenario static model of each process; Based on the process dynamic model of each process, a shortest distance change trend diagram between each anchor point of each process and the target body-in-white is determined as a first trend diagram of each anchor point of each process, and at the same time, a distance change trend diagram between each anchor point of each process and the physical center of the target body-in-white is determined as a second trend diagram of each anchor point of each process; Based on the first trend graph and the second trend graph of each anchor point of each process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated.

[0049] In this embodiment, based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the combined dynamic parameters between the target body-in-white and each dynamic component of each process are determined, including: Retrieving a preset list of combined action dynamic parameters to determine the combined action dynamic parameters between the target body-in-white and each dynamic component of each process; Among them, the preset combined dynamic parameter list is a pre-prepared list of combined dynamic parameters between the target body-in-white and each dynamic component of the corresponding process, which includes different actual body parameters of each process, different component parameters of each dynamic component of the corresponding process, and different original dynamic parameters.

[0050] In this embodiment, the combined dynamic parameters of the target BIW and each dynamic component of each process represent the morphological changes caused by the dynamic components to the target BIW during the process processing of the process and the parameters of the reaction caused to the dynamic components in the process. For example, parameters representing corresponding changes in the three-dimensional dimensions of the BIW shape over time and correspondingly, parameters representing corresponding changes in the model position points of the dynamic components over time.

[0051] In this embodiment, based on the combined action dynamic parameters between the target BIW and each dynamic component of each process and the process scene static model of each process, a process dynamic model of each process is generated, including: Based on the combined dynamic parameters between the target body-in-white and each dynamic component of each process, the three-dimensional coordinates of the position points in the process scene static model of each process are changed to obtain the process scene model of each frame, and all frame process scene models are connected to obtain the process dynamic model of the corresponding process.

[0052] In this embodiment, the trend graph of the shortest distance between the anchor point and the target body-in-white (the shortest distance here is the distance between the anchor point and the model position point closest to the anchor point among all model position points of the target body-in-white) is a numerical trend graph showing how the shortest distance between the anchor point and the target body-in-white changes over time during the process processing of the process.

[0053] In this embodiment, the distance variation trend diagram between the anchor point and the physical center of the target BIW is a numerical trend diagram showing the distance variation between the anchor point and the physical center of the target BIW over time during the process of the process.

[0054] In this embodiment, the abscissa axis of the first trend graph is time, and the ordinate axis is the shortest distance between the anchor point and the target BIW; the abscissa axis of the second trend graph is time, and the ordinate value is the distance between the anchor point and the physical center of the target BIW.

[0055] The beneficial effects of the above technology are: the combined dynamic parameters between the target body-in-white and each dynamic component of each process are determined, and a process dynamic model for each process is generated. Based on the first trend graph and the second trend graph of each anchor point of each process generated, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated.

[0056] Embodiment 6: On the basis of Example 5, the dynamic simulation modeling method of the body-in-white electrophoresis line evaluates the influence coefficient between each anchor point of each process and the target body-in-white based on the first trend graph and the second trend graph of each anchor point of each process, including: Based on the first trend graph and the second trend graph of each anchor point of each process, the shortest distance between each anchor point of each process and the target body-in-white is determined as the first shortest distance of each anchor point of each process, and the average rate of change of the trend in the first trend graph is determined as the first rate of change of each anchor point of each process, and at the same time, the shortest distance between each anchor point of each process and the physical center of the target body-in-white is determined as the second shortest distance of each anchor point of each process, and the average rate of change of the trend in the second trend graph is determined as the second rate of change of each anchor point of each process; The weighted sum of the reciprocal of the first shortest distance and the reciprocal of the first change rate of each anchor point of each process is used as the first sub-influence coefficient between each anchor point of each process and the target body-in-white, and the weighted sum of the reciprocal of the second shortest distance and the reciprocal of the second change rate of each anchor point of each process is used as the second sub-influence coefficient between each anchor point of each process and the target body-in-white; The sum of the first sub-influence coefficient and the second sub-influence coefficient between each anchor point of each process and the target body-in-white is regarded as the influence coefficient between each anchor point of each process and the target body-in-white.

[0057] In this embodiment, the shortest distance between each anchor point of each process and the target body-in-white is determined, which is the minimum ordinate value in the first trend graph.

[0058] In this embodiment, the average change rate of the trend in the first trend graph or the second trend graph is the first derivative function represented by the function of the curve in the first trend graph or the second trend graph, and the average of the first derivative function values ​​corresponding to all horizontal coordinate values ​​within the horizontal coordinate axis range in the first trend graph or the second trend graph.

[0059] In this embodiment, the shortest distance between each anchor point of each process and the physical center of the target body-in-white is determined to be the minimum ordinate value in the second trend graph.

[0060] In this embodiment, the weighted sum of the reciprocal of the first shortest distance and the reciprocal of the first change rate of each anchor point in each process is: The sum of the product of the reciprocal of the first shortest distance and the corresponding weight value of each anchor point in each process and the product of the reciprocal of the first change rate and the corresponding weight value is taken as the weighted sum value; The sum of the weight value corresponding to the inverse of the first shortest distance of each anchor point and the weight value corresponding to the inverse of the first change rate is 1, and the specific numerical values ​​of the weight values ​​are analyzed using big data, for example, they can all be 0.5.

[0061] In this embodiment, the weighted sum of the reciprocal of the second shortest distance and the reciprocal of the second change rate of each anchor point in each process is: The sum of the product of the reciprocal of the second shortest distance of each anchor point of each process and the corresponding weight value, and the product of the reciprocal of the second change rate and the corresponding weight value is taken as the weighted sum value; The sum of the weight value corresponding to the inverse of the second shortest distance of each anchor point and the weight value corresponding to the inverse of the second change rate is 1, and the specific values ​​of the weight values ​​are analyzed using big data, for example, they can all be 0.5.

[0062] The beneficial effects of the above technology are: by analyzing the first trend graph and the second trend graph, the first shortest distance and the first change rate as well as the second shortest distance and the second change rate of each anchor point of each process are determined, and these parameters are further calculated to achieve accurate quantification of the influence coefficient between each anchor point of each process and the target body-in-white.

[0063] Embodiment 7: Based on Example 5, the body-in-white electrophoresis line dynamic simulation modeling method, S303: determining all common anchor points of each process in the anchor point sequence of each process, and determining common parameters of all common anchor points, including: All anchor points in the anchor point sequence of each process whose influence coefficient with the target body-in-white is not less than a preset influence coefficient threshold are regarded as all the common anchor points of each process; Keep the sorting order of all common anchor points of each process in the anchor point sequence of the corresponding process to obtain the common anchor point sequence of each process; Based on the process dynamic model of each process, the common parameters of all common anchor points in the common anchor point sequence of each process are determined.

[0064] In this embodiment, the order of all the common anchor points in the common anchor point sequence is consistent with the order of their order in the anchor point sequence.

[0065] In this embodiment, the common parameters of all common anchor points in the common anchor point sequence of each process are determined based on the process dynamic model of each process, namely: The change data of the coordinates of the position of the common anchor point in the process dynamic model that changes with time is regarded as the common parameter of the common anchor point.

[0066] The beneficial effects of the above technology are: all common dynamic anchor points are selected in the anchor point sequence, and the common dynamic anchor point sequence is constructed, and the common dynamic parameters of all reasonable anchor points in the dynamic anchor point sequence are determined.

[0067] Example 8 Based on Example 1, the dynamic simulation modeling method of the body-in-white electrophoresis line, S4: based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, determining the automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, including: In the static model of the initial scene of the body-in-white electrophoresis line, a partial reference model of each automatic anchor point is determined; All the public anchor points in the initial state of the corresponding partial reference model in the static model of the initial scene of the body-in-white electrophoresis line are regarded as all the reference public anchor points of the corresponding automatic anchor points, and the three-dimensional constraint relationship between the corresponding automatic anchor point and each corresponding reference public anchor point is determined based on the partial reference model; Based on the static model of the initial scene of the body-in-white electrophoresis line, the common parameters of all common anchor points in each process and the three-dimensional constraint relationship between each automatic anchor point and each corresponding reference common anchor point, the automatic parameters of each automatic anchor point are determined.

[0068] In this embodiment, the partial reference model of the automatic anchor point is a pre-set partial reference model range where the common anchor point is located and can be used as a reference when the automatic parameters of the automatic anchor point are subsequently determined.

[0069] In this embodiment, the common anchor point located at the corresponding part of the reference model in the initial state is the common anchor point located within the model range corresponding to the corresponding part of the reference model in the static model of the initial scene of the body-in-white electrophoresis line.

[0070] In this embodiment, the three-dimensional constraint relationship between the corresponding automatic anchor point and each corresponding reference movable anchor point determined based on the partial reference model is the three-dimensional coordinate difference between the automatic anchor point and each corresponding reference movable anchor point in the partial reference model.

[0071] In this embodiment, based on the common parameters of all common anchor points in each process in the static model of the initial scene of the body-in-white electrophoresis line and the three-dimensional constraint relationship between each automatic anchor point and each corresponding reference common anchor point, the automatic parameters of each automatic anchor point are determined, namely: Based on the change data of the position point coordinates of the common anchor points that change with time in the process dynamic model represented by the common parameters of all common anchor points of each process, and the three-dimensional coordinate difference represented by the three-dimensional constraint relationship between the corresponding automatic anchor point and the corresponding reference common anchor point, multiple groups of position point coordinate data that change with time for each automatic anchor point are determined; Among the position point coordinate data of all groups of each automatic anchor point that change with time, all position point coordinates at the same time are averaged to obtain the position point data of each automatic anchor point at each time.

[0072] The beneficial effects of the above technology are: based on the partial reference model of each automatic anchor point determined, all reference common movable anchor points of the automatic anchor point are determined, and based on the common movable parameters of all common movable anchor points of each process and the three-dimensional constraint relationship between each automatic anchor point and each corresponding reference common movable anchor point, accurate calculation of the automatic parameters of each automatic anchor point is achieved.

[0073] Embodiment 9: Based on Example 1, the body-in-white electrophoresis line dynamic simulation modeling method, S5: based on the body-in-white electrophoresis line scene static model and the automatic parameters of all automatic anchor points and the public parameters of all public anchor points, generate a body-in-white electrophoresis line dynamic simulation model, including: The static model of the white car electrophoresis line scene, the automatic parameters of all automatic anchor points, and the public parameters of all public anchor points are superimposed in the same frame to obtain a superimposed dynamic simulation model; The neighborhood of the superimposed position in each frame of the superimposed static simulation model is sequentially smoothed to obtain a dynamic simulation model of the electrophoresis line of the body in white.

[0074] In this embodiment, the static model of the white car electrophoresis line scene and the automatic parameters of all automatic anchor points and the public parameters of all public anchor points are superimposed on the same frame, that is: Determine the position data of all automatic anchor points and the position data of all movable anchor points at each moment from the automatic parameters of all automatic anchor points and the universal parameters of all universal anchor points; The position data of all movable anchor points and all automatic anchor points in the static model of the white car electrophoresis line scene are replaced with the position data of all automatic anchor points and all movable anchor points at the same moment, so as to obtain the superimposed dynamic simulation model at the corresponding moment.

[0075] In this embodiment, the following method in the prior art can be used to sequentially smooth the neighborhood of the superimposed position in each frame of the superimposed static simulation model: Local Surface Smoothing: Local surface smoothing is a method of smoothing the surface of local areas on a 3D model. These areas usually have an irregular appearance or significant bumps. In computer graphics, the goal of local surface smoothing is to make the local area of ​​the model smoother, more natural and more beautiful by applying a smoothing algorithm. The recommended methods are: Polynomial interpolation: This method achieves surface smoothing by translating and scaling vertex coordinates in local areas; Surface reconstruction: For complex local areas, you can try to use surface reconstruction algorithms. For example, use surface fitting algorithms such as the least squares method to fit the boundaries of the local area to achieve smoothing; Surface fusion: A smoothing effect can be achieved by merging a local area with its adjacent areas and using a certain weight factor to control the degree of fusion.

[0076] Volumetric Discretization: Volumetric Discretization is to divide the entire model into many small volume segments and perform specific sampling and processing on each segment. The process of volumetric discretization can be achieved through some commonly used volumetric discretization algorithms, such as: Mesh generation: objects can be meshed using tetrahedral mesh, octahedral mesh, etc. Sampling and interpolation: At each grid point, a certain number of sampling and interpolation can be performed. This can obtain a volume resolution representation of the object at different resolutions; Smoothing: Smoothing the local area of ​​each grid point using the above-mentioned local surface smoothing method; Reassemble: Reassemble the processed meshes into a high-resolution volume resolved representation.

[0077] By combining the above two methods, the neighborhood of the superimposed position in each frame of the superimposed dynamic simulation model and the superimposed static simulation model can be smoothed while ensuring the accuracy of the model.

[0078] The beneficial effects of the above technology are: realizing the same frame superposition of the static model of the white car electrophoresis line scene and the automatic parameters of all automatic anchor points and the public parameters of all public anchor points, and smoothing the neighborhood of the superimposed position in the static simulation model of each frame superimposed in the superimposed dynamic simulation model in turn, thereby ensuring the accuracy and continuity of the dynamic simulation of the white car electrophoresis line.

[0079] Embodiment 10: The present invention provides a body-in-white electrophoresis line dynamic simulation modeling system, which is applied to the body-in-white electrophoresis line dynamic simulation modeling method described in any one of embodiments 1 to 9, referring to Figure 4 ,include: Model building module, used to build the static model of the initial scene of the body-in-white electrophoresis line; A process parameter determination module is used to determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; A public dynamic parameter determination module is used to determine the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the body-in-white parameters and the dynamic process parameters of each process; An automatic parameter determination module, for determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; The dynamic simulation generation module is used to generate a dynamic simulation model of the body-in-white electrophoresis line based on the static model of the body-in-white electrophoresis line scene and the automatic parameters of all automatic anchor points and the dynamic parameters of all dynamic anchor points.

[0080] The beneficial effects of the above technology are: by selecting all the public anchor points and automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, and based on the public parameters of all the public anchor points and the automatic parameters of all the automatic anchor points, dynamic simulation generation is performed on the basis of the static model of the body-in-white electrophoresis line scene, thereby ensuring the accuracy and continuity of the dynamic simulation of the body-in-white electrophoresis line, and providing reliable support for the subsequent understanding and optimization of the dynamic changes and event triggering in the entire pre-treatment electrophoresis process and related production decisions.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A dynamic simulation modeling method for a body-in-white electrophoresis line, characterized in that: include: S1: Build a static model of the initial scene of the body-in-white electrophoresis line; S2: Determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; S3: Based on the body-in-white parameters and the dynamic process parameters of each process, determine the common parameters of all common anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S4: determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; S5: Generate a dynamic simulation model of the BIW electrophoresis line based on the static model of the BIW electrophoresis line scene, the automatic parameters of all automatic anchor points, and the dynamic parameters of all dynamic anchor points.

2. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 1 is characterized in that: S2: Determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW, including: Obtaining body-in-white parameters of at least one target body-in-white; The BIW electrophoresis standard is retrieved based on the BIW parameters of each target BIW, and the dynamic process parameters of each process of each target BIW in the BIW electrophoresis line scene are obtained.

3. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 1 is characterized in that: S3: Based on the body-in-white parameters and the dynamic process parameters of each process, determine the dynamic parameters of all dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, including: S301: Determine a process scene static model of each process in the initial scene static model of the body-in-white electrophoresis line; S302: based on the body-in-white parameters and the dynamic process parameters of each process, determining the anchor point sequence of each process in the process scene static model of each process in turn; S303: Determine all common anchor points of each process in the anchor point sequence of each process, and determine common parameters of all common anchor points of each process.

4. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 3 is characterized in that: S302: Based on the body-in-white parameters and the dynamic process parameters of each process, the anchor point sequence of each process is determined in the process scene static model of each process in turn, including: Based on the dynamic process parameters of each process, all dynamic components of each process and original dynamic parameters of each dynamic component are determined; Determine the component initial state model of each dynamic component of each process in the process scenario static model of each process; Based on the body-in-white parameters, the starting body parameters of each process are predicted and simulated; Based on the starting body parameters of each process, all anchor points of the corresponding process are selected in the component initial state model of each dynamic component of each process; Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated; According to the principle of the influence coefficient between the anchor point and the target body-in-white from large to small, all the anchor points of each process are sorted to obtain the anchor point sequence of each process.

5. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 4 is characterized in that: Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated, including: Based on the starting body parameters of each process and the component parameters and original dynamic parameters of each dynamic component of the corresponding process, the combined dynamic parameters between the target body-in-white and each dynamic component of each process are determined; Generate a process dynamic model for each process based on the combined action dynamic parameters between the target body-in-white and each dynamic component of each process and the process scenario static model of each process; Based on the process dynamic model of each process, a shortest distance change trend diagram between each anchor point of each process and the target body-in-white is determined as a first trend diagram of each anchor point of each process, and at the same time, a distance change trend diagram between each anchor point of each process and the physical center of the target body-in-white is determined as a second trend diagram of each anchor point of each process; Based on the first trend graph and the second trend graph of each anchor point of each process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated.

6. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 5 is characterized in that: Based on the first trend graph and the second trend graph of each anchor point of each process, the influence coefficient between each anchor point of each process and the target body-in-white is evaluated, including: Based on the first trend graph and the second trend graph of each anchor point of each process, the shortest distance between each anchor point of each process and the target body-in-white is determined as the first shortest distance of each anchor point of each process, and the average rate of change of the trend in the first trend graph is determined as the first rate of change of each anchor point of each process, and at the same time, the shortest distance between each anchor point of each process and the physical center of the target body-in-white is determined as the second shortest distance of each anchor point of each process, and the average rate of change of the trend in the second trend graph is determined as the second rate of change of each anchor point of each process; The weighted sum of the reciprocal of the first shortest distance and the reciprocal of the first change rate of each anchor point of each process is used as the first sub-influence coefficient between each anchor point of each process and the target body-in-white, and the weighted sum of the reciprocal of the second shortest distance and the reciprocal of the second change rate of each anchor point of each process is used as the second sub-influence coefficient between each anchor point of each process and the target body-in-white; The sum of the first sub-influence coefficient and the second sub-influence coefficient between each anchor point of each process and the target body-in-white is regarded as the influence coefficient between each anchor point of each process and the target body-in-white.

7. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 5 is characterized in that: S303: Determine all common anchor points of each process in the anchor point sequence of each process, and determine common parameters of all common anchor points, including: All anchor points in the anchor point sequence of each process whose influence coefficient with the target body-in-white is not less than a preset influence coefficient threshold are regarded as all the common anchor points of each process; Keep the sorting order of all common anchor points of each process in the anchor point sequence of the corresponding process to obtain the common anchor point sequence of each process; Based on the process dynamic model of each process, the common parameters of all common anchor points in the common anchor point sequence of each process are determined.

8. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 1 is characterized in that: S4: Based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line, the automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line are determined, including: In the static model of the initial scene of the body-in-white electrophoresis line, a partial reference model of each automatic anchor point is determined; All the public anchor points in the initial state of the corresponding partial reference model in the static model of the initial scene of the body-in-white electrophoresis line are regarded as all the reference public anchor points of the corresponding automatic anchor points, and the three-dimensional constraint relationship between the corresponding automatic anchor point and each corresponding reference public anchor point is determined based on the partial reference model; Based on the static model of the initial scene of the body-in-white electrophoresis line, the common parameters of all common anchor points in each process and the three-dimensional constraint relationship between each automatic anchor point and each corresponding reference common anchor point, the automatic parameters of each automatic anchor point are determined.

9. The body-in-white electrophoresis line dynamic simulation modeling method according to claim 1, characterized in that: S5: Generate a dynamic simulation model of the BIW electrophoresis line based on the static model of the BIW electrophoresis line scene, the automatic parameters of all automatic anchor points, and the dynamic parameters of all dynamic anchor points, including: The static model of the white car electrophoresis line scene, the automatic parameters of all automatic anchor points, and the public parameters of all public anchor points are superimposed in the same frame to obtain a superimposed dynamic simulation model; The neighborhood of the superimposed position in each frame of the superimposed static simulation model is sequentially smoothed to obtain a dynamic simulation model of the electrophoresis line of the body in white.

10. The body-in-white electrophoresis line dynamic simulation modeling system is characterized by: The body-in-white electrophoresis line dynamic simulation modeling method applied to any one of claims 1 to 9 comprises: Model building module, used to build the static model of the initial scene of the body-in-white electrophoresis line; A process parameter determination module is used to determine the dynamic process parameters of each process in the BIW electrophoresis line scene based on the BIW parameters of the target BIW; A public dynamic parameter determination module is used to determine the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the body-in-white parameters and the dynamic process parameters of each process; An automatic parameter determination module, for determining automatic parameters of all automatic anchor points in the static model of the initial scene of the body-in-white electrophoresis line based on the public dynamic parameters of all public dynamic anchor points in the static model of the initial scene of the body-in-white electrophoresis line; The dynamic simulation generation module is used to generate a dynamic simulation model of the body-in-white electrophoresis line based on the static model of the body-in-white electrophoresis line scene and the automatic parameters of all automatic anchor points and the dynamic parameters of all dynamic anchor points.

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