Journal
SENSORS
Volume 16, Issue 12, Pages -Publisher
MDPI AG
DOI: 10.3390/s16122116
Keywords
pipeline small leakage detection; variational mode decomposition; adaptive de-noising method; ambiguity correlation classification
Funding
- National Natural Science Foundation Project of China [61374219]
- Natural Science Foundation Project of Hebei province [E2016203223]
- Tianjin Research Program of Application Foundation and Advanced Technology [14JCZDJC32300]
- Specialized research fund for the doctoral program of higher education [20130032130001]
- National Key Research and Development Program [2016YFC0802103]
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In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.
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