An Image-Based Method for Acquiring Safety Margin of Sheet Metal Forming Process Parameters

Abstract

An image-based method for obtaining safety margins of sheet metal forming process parameters. First, a training image set is obtained. Each element in the training image set is a set of forming process parameters extracted from the space of the forming process parameter range of the preset forming device. And input the compositional process parameters into the molding simulation software to obtain a plane view of a preset perspective of the three-dimensional molding simulation diagram as an element in the training image set, then synthesize the best molding target image, and extract each Elements and molding feature parameters of the best molding target image. Then obtain the forming mathematical model, so as to input the N composition process parameters into the forming mathematical model, and use the forming characteristic parameters corresponding to the best forming target image as the target, and obtain the N that satisfies the preset constraints. 1 Composition process parameters. Last to N 1 The value of each molding process parameter in the compositional process parameters is distributed and counted to obtain the safety margin of the molding process parameters.

Description

technical field [0001] The invention relates to the technical field of forming technology, in particular to an image-based method for obtaining a safety margin of a sheet metal forming process parameter. Background technique [0002] Sheet metal forming is widely used in various fields of life, especially in the field of automobiles. More than 70% of auto parts are formed by stamping. Sheet metal forming becomes an increasingly difficult problem as product quality requirements and complexity increase. There are many factors that affect the molding quality, among which the most critical factor is the molding process parameters. Small changes in molding process parameters may cause huge differences in molding quality. Therefore, solving the molding process parameters has always been a major concern in the academic circles. At present, the mainstream parameter inversion method in the world is based on the hybrid numerical method combining experiment and finite element simula...

AI Technical Summary

Problems solved by technology

However, with the increase of parameters, its calculation cost increases exponentially, which leads to a significant increase in product design cycle

There are many uncertainties in actual engineering, so there should be a safe range for the molding parameters, and many inverse methods do not consider the uncertainty problem, and the inverse calculations are all point estimates of parameter values

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