A magnetic control submerged-
arc welding seam tracking
signal analyzing method based on experience
wavelet transformation mainly solves the problems that existing hardware filtering is not complete, low-frequency interference signals similar to seam tracking signals are difficult to filter out by a
wavelet filtering method, and EMD unreasonable
decomposition convergence conditions, over-envelope, under-envelope and the like are liable to cause
modal aliasing. According to the key points of the technical scheme, a magnetic control submerged-
arc welding arc sensor controls swinging of arcs so as to carry out
welding seam groove scanning, a Hall sensor collects original signals and carries out hardware filtering
processing on the original signals, the experience
wavelet transformation
signal analyzing method is utilized for carrying out low-frequency analyzing on the signals after the hardware filtering, one
wavelet filter set is adaptively selected according to
Fourier spectrum characteristics of the signals so as to extract different AM-FM components of the signals, then Hilbert conversion is carried out on each experience
modal function, and meaningful instantaneous
signal characteristics are obtained. By adopting the method, the more precise
welding seam tracking signals are extracted, and the information of other low-frequency interference signals are obtained simultaneously.