Segmentation of the pipeline leakage signals by means of wavelet-analysis
DOI:
https://doi.org/10.15587/1729-4061.2013.12750Keywords:
Segmentation, wavelet-transform, pipeline leaksAbstract
The methods of underground pipeline signals segmentation based on wavelet neural network and discrete wavelet transform were proposed. Segmentation is a stage, preceding the analysis and classification of signals in order to detect leaks. It is used to highlight areas of the signal containing no external industrial noise. The effectiveness of the proposed methods of segmentation was investigated.
Analysis of the acoustic signal is one of the most promising approaches to the detection of underground pipeline leaks. Signal emitted by the pipe can be read on the ground surface and on the basis of it’s analysis the decision about the presence or absence of a leak can be made. One problem here is the presence of external industrial noise from passing vehicles, working mechanisms, etc.
This work is devoted to developing a pipeline signals segmentation method. The purpose of this method is to separate the signal without noise and the signal influenced by external noise.
Segmentation method based on the wavelet transform of the leakage signal was proposed. “Details” coefficients obtained on a single step of the wavelet decomposition, provide information about the presence or absence of external noise. Decision about the noise presence can be made on the base of the coefficients energy analysis.
Proposed method was tested on the model signals and signals obtained during the experimentReferences
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