Choi-Williams时频分布在CO_2焊接电信号检测中的应用

Application of Choi-Williams distribution to electrical signals detecton in CO_2 arc welding

利用二次型时频分析Wigner-Vill分布的改进算法——Choi-Williams(CWD)时频分布研究CO2焊接过程所采集的电弧电压信号,把信号置于时频空间内进行分析,获得相关信号的时频分布图。对于CWD分布的核函数中平滑因子确定前提下的其它四个重要参数,即时窗类型、时窗长度、频窗类型和频窗长度对时频谱图分析效果的影响进行了讨论。进而引入信息熵的概念,并分析了时频分析基于信息熵的参数优化。最后分析了采用最小信息熵的CWD分布参数优化后的一组电弧电压信号时频分布图。结果表明,利用Choi-Williams分布及信息熵最小原则可以描述弧焊电信号的时频分布,并有效抑制交叉项干扰,同时保持较高的时频分辨率。

Time-frequency distribution of Choi-Williams,which is the algorithm modified based on Wigner-Vill distribution,was used to study arc voltage signals acquired during CO2 arc welding.The signals was analyzed in time-frequency domain to get the time-frequency distribution pattern.The influence of four parameters such as analysis window type and analysis window width of time and frequency on analysis efficiency of distribution pattern was discussed on the premise of smoothing factor in kernel function of Choi-Williams algorithm.And then,the concept of information entropy was introduced.The parameters of Choi-Williams distribution were optimized by information entropy calculating which is meaningful to improve the efficiency of time-frequency analysis.The result of experiment analysis shows that the time-frequency distribution of electrical signals during welding can be expressed by Choi-Williams distribution and the principle of minimum information entropy.And then,the cross term interference is inhibited effectively and better time-frequency centralizing is obtained.