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《Technical Acoustics》 2015-05
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Feature analysis of pipeline leakage acoustic signals for leak identification

FENG Xue-song;WEN Yu-mei;ZHEN Jin-peng;ZHANG Xue-yuan;LI Ping;WEN Jing;Research Center of Sensors and Instruments, School of Opto-electronic Engineering, Chongqing University;  
Leakage acoustic signal of pipelines is originated from the concurrent events during leaking. This physical fact suggests that only by combining multiple features of the signal can a leak be uniquely identified. Reasonable selection and appropriate application of features is the key to develop a valid leak recognizing pattern. According to the mechanism of leaking, the characteristics of randomness and frequency distribution are chosen as leak features. Since the randomness and frequency distribution can be described with various characteristics, a single characteristic and the combination of multiple characteristics from the same or different classes are compared for identifying leaks based on abundant acoustic signal samples collected from practical water-supplied pipelines.The Support Vector Machine is used for recognition. The recognition effect with two characteristics is better than that with a single characteristic, particularly the combination of sample entropy and power spectral distribution obtains the highest correct rate of 93%. However, more characteristics fail to produce further improvement in the correct rate of recognition. With the selected features, common noise and mimicked leakage sound can also be identified correctly.
【Fund】: 国家自然科学基金资助项目(61174017)
【CateGory Index】: TU991.38;TN911.6
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