Pipeline leak detection is an important part of pipeline safety, which is usually carried out by extracting featurevectors of leakage signal. However, the complexity of the leakage acoustic emission signal makes the extraction of featurevectors very difficult. To solve this problem, the authors propose an improved wavelet packet algorithm to extract the featurevectors which are constituted by five time-frequency domain parameters: time-domain energy, frequency-domain energy,frequency-domain peak, kurtosis coefficient and variance. Many experiments have been performed to extract featurevectors based on the proposed algorithm, with the results showing the proposed algorithm to be efficient enough to overcomethe mixing effects caused by traditional wavelet packet when reconstructing the single sub-band signal. Thus, theproposed algorithm can accurately extract the feature vectors. The study of this article provides a good foundation for thesubsequent work such as pipeline leak detection and positioning analysis.
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