Laser ultrasonic detection method for metal surface microcrack depth

Abstract

The invention discloses a laser ultrasonic detection method for metal surface microcrack depth, which comprises three steps of laser excitation, laser detection and signal processing, and comprises the following steps: based on a phase grating, combining a grating modulated laser pulse signal simulated by a finite element method with an experimental signal to construct a data set; adding a random Gaussian noise amplification data set, and carrying out wavelet transform processing on the simulation signal and the experiment signal; and subsequent signals are processed by using the deep neural network. According to the laser narrow-band ultrasonic micro-crack identification method based on deep learning, a quantitative characterization device for the depth of the micro-crack on the metal surface is designed, and the micro-crack on the surface of a metal material can be reliably and flexibly characterized; and the method can be further expanded into a universal fully contactless automatic detection method for representing surface and subsurface defects of metal and semiconductor materials of dozens of microns or even submicrons.

Description

technical field [0001] The invention relates to a laser ultrasonic detection method, in particular to a laser ultrasonic detection method for the depth of micro-cracks on a metal surface. Background technique [0002] Surface and subsurface defects are the most common types of material defects in metals. Affected by external conditions such as radiation and corrosion, metal materials are prone to produce tiny internal or surface defects, resulting in material damage. These defects are often invisible. If the defects cannot be found in time and corresponding countermeasures are taken, the defects will continue to expand, there will be potential safety hazards, and even serious safety accidents will occur. [0003] Compared with magnetic particle testing, X-ray testing, eddy current testing, and penetration testing, ultrasonic testing has the advantages of wide application range, strong penetration ability, fast detection speed, etc., and is harmless to human body and enviro...

AI Technical Summary

Problems solved by technology

However, in order to improve the signal-to-noise ratio, large laser power must be concentrated on a small spot, which often results in localized damage to the sample

In addition, because the conventional feature extraction of ultrasonic signals has limitations at low signal-to-noise ratios, the detection of defect depth has always been a difficult point in the ultrasonic field

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