Study On Ultrasonic Signal Technology In Defects Of Coal Mine Machinery Based On Independent Component Analysis

In ultrasonic nondestructive testing, ultrasonic testing signal noise cancellation is of greatsignificance for the detection and identification of defects. Ultrasonic signal hasnon-stationary characteristics, so the choice of noise reduction method is particularlyimportant, which have a direct impact on the defects in quantitative and positioning analysis.Independent Component Analysis (ICA) is one of the emerging technologies of the currentsignal processing, and its purpose is to find a linear transformation matrix, the transformedcomponents as soon as possible independent of each other, so as to achieve the goal ofeliminating noise signals.This thesis puts forward its own solutions from the two aspects of the simulation ofultrasonic signal and the measured ultrasonic detection signal through the experiments toverify the feasibility and effectiveness of the method. The main research content and resultsare as follows:(1) This thesis has been analyzed and studied the principle of Independent ComponentAnalysis and other algorithms’ implementation method, and described each algorithm’snature.(2) The simulation model of the FastICA algorithm, JADE algorithm and Informaxalgorithm has been established, and their separation performance has been completed, andtheir validities have been verified.(3) By the characteristics of the ultrasonic signal and noise signal of the phase space, thephase space matrix has been established and independent component analysis has beenexacted. The most optimal algorithm has been obtained by experiment.(4) Considering the defects of the traditional optimization algorithm, suc h as, the slow convergence, easy to fall into local optimum, affecting the signal separation performance, animproved particle swarm optimization algorithm and independent component analysis arecombined through ultrasound simulation signal and measured signal to verify the feasibilityand the superiority.The simulation results show that the ICA algorithm is a effectiveness and feasibilitymethod. At the same time, the thesis has summarized independent component analysis ofsignal processing in ultrasonic testing on the basis of the study, and pointed out the feasibilityof the weak signal extraction method in ultrasonic testing as well as the problems, andsummarized the further research directions.