小波
声学
信号(编程语言)
理论(学习稳定性)
窗口函数
弧(几何)
信号处理
能量(信号处理)
计算机科学
工程类
电子工程
数学
数字信号处理
人工智能
统计
电信
物理
光谱密度
机械工程
机器学习
程序设计语言
出处
期刊:Measurement
[Elsevier BV]
日期:2017-04-12
卷期号:105: 98-105
被引量:12
标识
DOI:10.1016/j.measurement.2017.04.015
摘要
Abstract This paper employed the short time energy of arc sound signals to online quantitatively describe the stability of arc sound signal. At first, the signal can be preprocessed by wavelet packet filtering, and then detailed information of the short time energy of the signal was obtained using hamming window. After statistical analyzed the short time energy, the energy distribution possibility and cumulative distribution function of the signal can be collected. Then a proposed stability evaluation criterion was employed to quantitatively describe the stability of arc sound signal. Relative experimental data showed that more stable signal corresponded lager value of the criterion. The proposed method which combined the short time energy and statistical analysis was supported by many actual experiments. This contribution can benefit the quantitative evaluation of the arc welding process, and instructed the future parameters optimization to obtain welding products with high quality.
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