金属拉深件拉深过程微裂纹AE信号特征参数的优化及状态识别

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振动与冲击 ›› 2012, Vol. 31 ›› Issue (17) : 154-158.

论文

金属拉深件拉深过程微裂纹AE信号特征参数的优化及状态识别

骆志高范祥伟陈强

作者信息 +

The AE signal characteristic parameters optimization of initial crack and status identification for drawing parts

LUO Zhi-gao, FAN Xiang-wei, CHEN Qiang

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摘要

本文通过对拉深件成型状态的声发射测试，进行了拉深过程AE特征参数信号的提取。对采集到的信号进行局域波分解后提取各IMF(Intrinsic Mode Function)的能量值作为初始特征参数，应用遗传算法对初始特征参数进行优化，生成最优特征参数。采用简单的马氏距离方法，将正常状态和微裂纹状态两种质量状态下的实验数据进行计算，比较两种状态下马氏距离的大小，取其中最小判别距离对应的状态为测试样本的状态类型。研究结果说明了该方法可以有效地识别出拉深件的微裂纹AE信号，从而判断出拉深件的初始裂纹状态，实现AE信号特征参数的优化及对金属拉深件成型质量状态的识别。

Abstract

This study processed the characteristic parameters extraction of acoustic emission signals through the acoustic emission test of the drawing parts molding state. The collected signals were processed the local wave decomposition to extract the energy value of each IMF (Intrinsic Mode Function) as the initial characteristic parameters, which were optimized by genetic algorithm to create the optimal characteristic parameters. The experimental data between the normal condition and the crack state were computed by the simple Mahalanobis distance method to compare the big or small of the Mathalanobis distance during the two states, and then the state corresponding to the minimum discriminated distance was the state type of the test sample. The research results states that this way can recognize effectively the crack acoustic emission signals of the drawing parts to judge the initial crack state of the drawing parts as well as achieve the characteristic parameters optimization of the acoustic emission and the molding quality state recognition of the metal drawing parts.

导出引用

骆志高范祥伟陈强 . 金属拉深件拉深过程微裂纹AE信号特征参数的优化及状态识别[J]. 振动与冲击, 2012, 31(17): 154-158

LUO Zhi-gao;FAN Xiang-wei;CHEN Qiang. The AE signal characteristic parameters optimization of initial crack and status identification for drawing parts[J]. Journal of Vibration and Shock, 2012, 31(17): 154-158