WAVELETS APPLICATION ON ACOUSTIC EMISSION SIGNAL DETECTION IN PIPELINE

As a popular non-destructive test, acoustic emission (AE) 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 time or frequency domain, while local information are lost. Although the short-time Fourier transform (STFT) is developed to analyze time and frequency details simultaneously, it can only achieve a limited precision. Wavelet Transform (WT) is a time-scale-frequency technique with adaptable precision, which does better features extraction and details detection. This paper is an application of wavelet transform in acoustic emission signal detection where strong noise exists. Developing for industrial applications, the techniques presented are both accurate and computationally implemental for embedded systems. In addition, STFT is compared with wavelets to show the advantages of wavelet transforms in this particular application field.