Quantitative evaluation method of arc sound spectrum based on sample entropy

Arc sound analysis is an effective way to evaluate the stability of the arc welding process. Current methods cannot effectively quantify the disorder of the process. By studying the characteristics of the arc sound signal, we found that low frequency random mutation of arc sound power resulted from unstable factors, such as splashes or short circuits, increased the complexity and randomness of the arc sound signals. Then the arc sound signals were visualized on time-frequency interface by means of spectrogram, and it was found that the max power spectral density (PSD) distribution of spectrogram was closely related to the stability of arc welding process. Moreover, a method based on sample entropy was proposed to further quantify the relation. Finally, considering the factors such as averages of max PSD and the standard deviations of sample entropy, a compound quantitative evaluation indicator, arc sound sample entropy (ASSE), which can avoid the influence of different parameters on the quantitative results, was proposed, so that the stability of arc welding process can be quantitatively presented. Testing results showed that the accuracy rate of the method was more than 90 percent.