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

摘要/Abstract

摘要：

针对目前k9光学玻璃材料去除缺乏以声发射信号描述的问题,文中采用了基于声发射信号建立划痕形貌理论模型来描述划痕形貌及粗糙度预测的方法。该方法采用单颗随机磨粒刮头,在五轴联动机床上对k9光学玻璃进行变深度划刻声发射试验,并设计带通滤波器对声发射信号进行分析处理。目标时域声发射信号幅值约0.01dB,对目标频域内声发射信号进行傅里叶变换,得到信号能量集中在60~160 kHz低频段。最后,通过发射信号划痕表面的划痕形貌模型计算划痕粗糙度,并将结果与显微镜测量出的粗糙度值做对比。实验结果显示,新方法的预测值更为接近真实值。

关键词: k9光学玻璃, 声发射信号, 目标频域, 能量集中, 表面形貌, 划痕粗糙度

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

中图分类号:

TN911.72

胡吉雄,姜晨,郎小虎. 基于声发射信号k9光学玻璃划痕形貌及粗糙度预测[J]. 电子科技, 2020, 33(3): 26-32.

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