The Application Of Acoustic Emission Technology In Non-destructive Testing

When material partial energy drastically release, it has acoustic mission (AE) signal production, AE signal contains important characteristic information of the related AE source. Production and development of material flaws can be monitored dynamically through collecting and analyzing AE signal. The AE examination technology has the significant realistic value in equipment status monitoring and warning, which is widely used in a number of fields, such as petrochemical industry, aerospace industry, materialtest, and transportation. The AE signal processing plays key role in the research of the AE measurement. But as a result of complexity of AE signal, it is very difficult to analyze collect and extract AE source characteristic parameter. So the AE signal processing technology research is key question in AE technology fundamental research and project application.Noise sources in acoustic detection and processing methods have been analyzed. The detecting signal is often disturbed by various noises in the process of the application of structural non-destructive testing. The signal that is disturbed by noises maybe processed for the accurate results. In the thesis, the fundamental theory and method of the signal de-noise based on wavelet transform is explained. Wavelet analysis is such tool that obtains signal's detail characteristics both in time and frequency. Coefficients can be obtained through self-adapting decomposing of AE signals in wavelet multilevel analysis, the frequency, time, energy and other information of AE signal can be observed directly from coefficients energy image in phaseplane. Meanwhile, it also provides a theoretical basis for wavelet AE signal reconstruction. On the Basis of this theory, the constructed AE signal which has been excluded most interference of other signal and shown AE source information must clearly. This method would be more significant for AE sources analysis.The experiment including the selection of acoustic emission sources, collecting acoustic emission signals, audio conversion, signal processing, the results of analysis. It is testified by the analysis of the simulated signal and experimental signal, the signal's noise is effectively eliminated by wavelet de-noise technology and the signal's original information including the signal's singular points is retained. The Fourier and the wavelet algorithms used in noise elimination have been compared. The mechanism of FFT and its de-noising process are analyzed. The mechanism of wavelet noise elimination and its several methods of threshold determination also have been described. Two modified threshold function based on the wavelet multi-resolution analysis threshold de-noising method was proposed, and applied on defect signal de-noising. The wavelet analysis technique has been proved that it is more suitably used in noise de-noising for acoustic emission detection via de-noising processing the emitting signal of a breaking pencil.