Segmentation of the pipeline leakage signals by means of wavelet-analysis

Authors

  • Віктор Олександрович Строганов Sevastopol National Technical University Universitetskaya str, 33, Sevastopol, 99053, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2013.12750

Keywords:

Segmentation, wavelet-transform, pipeline leaks

Abstract

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 experiment

Author Biography

Віктор Олександрович Строганов, Sevastopol National Technical University Universitetskaya str, 33, Sevastopol, 99053

Department of Information systems

References

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Published

2013-04-25

How to Cite

Строганов, В. О. (2013). Segmentation of the pipeline leakage signals by means of wavelet-analysis. Eastern-European Journal of Enterprise Technologies, 2(10(62), 32–35. https://doi.org/10.15587/1729-4061.2013.12750

Issue

Vol. 2 No. 10(62) (2013): Applied information technologies

Section

Applied Information Technology

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Copyright (c) 2014 Віктор Олександрович Строганов

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