基于声发射信号k9光学玻璃划痕形貌及粗糙度预测

doi:10.16180/j.cnki.issn1007-7820.2020.03.006

Abstract

Abstract:

The current k9 optical glass material removal lacks the problem described by acoustic emission signals. A method based on acoustic emission signals to establish a theoretical model of scratch morphology was proposed to describe the method of scratch morphology and roughness prediction. Specifically, a single random abrasive scraper was used to perform a deep-depth squeaking acoustic emission test on the k9 optical glass on a five-axis joint bed and a bandpass filter was designed to analyze and process the acoustic emission signal. The amplitude of the target time domain acoustic emission signal was about 0.01dB, and the signal energy of the fourier transform of the acoustic emission signal in the target frequency domain was concentrated in the low frequency range of 60~160 kHz. The scratch roughness was calculated by the surface scratch model of the transmitted signal, and was further compared with the roughness measured by the microscope. The results showed that the predicted value of the proposed method was closer to the true value.

Key words: the k9 glass, acoustic emission signal, target frequency domain, energyconcentration, surface roughness profile, scratch roughness

CLC Number:

TN911.72

HU Jixiong,JIANG Chen,LANG Xiaohu. k9 Glass Squeaking Acoustic Emission Signal Scratch Profile and Roughness Prediction[J].Electronic Science and Technology, 2020, 33(3): 26-32.

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工艺参数	数值
划刻深度	15~40 μm
工作台移动速度	3~10 mm·s^-1

k9 Glass Squeaking Acoustic Emission Signal Scratch Profile and Roughness Prediction

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