WAVELETS APPLICATION IN ACOUSTIC EMISSION SIGNAL DETECTION OF WIRE RELATED EVENTS IN PIPELINE

摘要

As a popular nondestructive test, acoustic emission (AE) testing has been widely used in many physical and engineering fields such as leak detection and pipeline inspection. Among those applied AE tests, a common problem is to extract the physical features of the ideal events, so as to detect similar signals. In acoustic signal processing, those features can be represented as joint time-frequency distribution. However, classical signal processing methods only give global information on either time or frequency domain, while local information is lost. Although the short-time Fourier transform (STFT) is developed to analyze time and frequency details simultaneously, it can only achieve limited precision. Wavelet transform is a time-scale-frequency technique with adaptable precision, which makes better feature extraction and detail detection. This paper is an application of wavelet transform in acoustic emission signal detection where strong noise exists. Developed for industrial applications, the techniques presented are both accurate and computationally implemental for embedded systems. In addition, STFT is compared with wavelet transform to show the advantages of wavelet transforms in this particular1 application.