Research On The De-noising And Compression Of MFL Signals Of Working Pipes

Iron magnetic pipe is widely used in all the sectors of the industry. As the harsh work conditions, pipes are easily destroyed. The destroyed pipes have brought a great loss to both production and life. So the periodic detection is of great importance for the security of the production and life. Usually, the noise signal is mixed into detecting signal in the detecting process. We need to deal with detecting signal by reducing noise signal. Detecting signals should be stored on the storage materials which belong to detecting systems. Concerning the storage room, the signals need to be compressed. Noise reduction and signal compression performance are two research problems that should be solved.This paper has mainly discussed the method of reducing noise and compressing signal in the process of detecting working pipes. Firstly, we give a brief introduction of the principles and advantages of wavelet threshold in reducing noise. Here we prefer the wavelet threshold method and make some improvements of the original method. Adaptive compromise algorithm between soft-thresholding and hard-thresholding yield good performance in reducing noise. As far as signal compression is concerned, we deploy the combination of EZW coding and entropy coding. The bit flow produced by EZW coding, to further improve compressing efficiency, we use arithmetic coding to compress the signal and produce the final output data flow.