• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (4): 60-64.

• 论文 • 上一篇    下一篇

基于小波的全数字逆变焊机信号处理

段彬;孙同景;李振华;张光先;梅高青   

  1. 山东大学控制科学与工程学院
  • 发布日期:2010-02-20

Signal Processing of All-digital Inverter Welder Based on Wavelet

DUAN Bin;SUN Tongjing;LI Zhenhua;ZHANG Guangxian;MEI Gaoqing   

  1. College of Control Science and Engineering, University of Shandong
  • Published:2010-02-20

摘要: 从强干扰、高压、大电流的恶劣工作环境中,获得逆变焊机有用信号,是全数字焊接电源研发和工艺评判的关键。在分析研究脉冲宽度调制(Pulse width modulation, PWM)驱动原理的基础上,提出先对逆变焊机PWM驱动信号级的电流信号进行去噪,进而实现整个焊接电流信号的噪声滤除方法。构建硬门限阈值函数对信号进行小波分解,对小波分解的详细系数集去噪。同时构建模极大值判别函数,来搜寻详细系数的噪声奇异点,利用搜索结果对近似系数集的噪声进行线性滤除。选择相关参数的合适数值进行仿真试验,结果表明,该去噪方法能够很好地滤除焊接电流的噪声,保证信号不失真,获得有用的信号特征,为全数字逆变电源的研究和性能评价奠定基础。

关键词: 模极大值, 全数字逆变焊机, 小波变换, 性能评价, 阈值

Abstract: The working environment of inverter power sources is filled with strong interference, high voltage and current. To obtain useful signals of the inverter welding machine from harsh environment is the key to R&D and technological evaluation of all-digital welding power source. A new method is put forward after analysis and research on the principle of pulse width modulation (PWM) driving, i.e. the current signal of inverter welding machine at PWM driving level is denoised first, then noise filtering of the whole welding current signal is carried out. Hard threshold function is constructed to carry out wavelet decomposition of signal, and the detail coefficients are denoised. At the same time, modulus maxima discriminant function is constructed to search noise singular points from detail coefficients. The search results are used to denoise approximation coefficients linearly. Simulation experiments based on selection of appropriate correlation parameters show that the method can filter welding current noise effectively, ensure distortion-free signal and obtain useful signal characteristics, thereby laying the foundation for the research and performance evaluation of all-digital inverter power source.

Key words: All digital inverter, Modulus maxima, Performance evaluation, Threshold, Wavelet transform

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