Method for identifying fine crack impact signal of metal deep drawing part

Abstract

The invention discloses a method for identifying a fine crack impact signal of a metal deep drawing part. The method comprises the following steps: acquiring a fine crack acoustic emission impact signal of a metal deep drawing part by using an acoustic emission sensor, carrying out preamplification, filtering and A/D conversion pretreatment on the acquired signal, inputting the pretreated signal into a computer, analyzing the wavelet packets, reconstructing data at different wave bands after the wavelet packets are decomposed, carrying out time series analysis on the denoised acoustic emission signal by using a time series method, establishing a time series model, and finally, identifying the state of the metal deep drawing part in the computer by combining a fuzzy comprehensive judgment method with maximum membership grade principle. The invention can enhance the accuracy that characteristic parameters reflect the actual working conditions can greatly reduce the sampling number on the premise of ensuring to acquire sufficient information, has the advantages of accurate and clear frequency positioning, and is suitable for the occasions with high requirements for on-line monitoring.

Description

technical field [0001] The invention relates to a state detection and fault diagnosis method based on the acoustic emission technology of metal parts, in particular to a method for identifying early micro-cracks of metal parts in a deep-drawing state. Background technique [0002] Deep drawing is a stamping process that uses a special mold to support a flat blank to open a hollow part. The deep drawing method can be used to make cylindrical, stepped, conical, spherical and other irregularly shaped thin-walled parts. If it is combined with other stamping forming processes, it can also manufacture parts with extremely complex shapes. Using the deep drawing method to manufacture thin-walled hollow parts, the production efficiency is high, the material is saved, the strength and rigidity of the parts are good, the precision is high, and the processing range of deep drawing is very wide, ranging from small parts with a diameter of a few millimeters to large parts with a diameter ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the inaccuracy and inefficiency of extracting the crack characteristic parameters of metal deep drawing parts in the prior art, and to propose a method based on wavelet packet decomposition and automatic analysis with high accuracy, high efficiency and fast calculation speed. Recognition Method of Impact Acoustic Emission Signals of Early Micro-cracks in Deep-drawn Metal Parts Based on Regression Spectrum Analysis

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