Feature Extraction of the Small Leakage Diagnosis of Oil Pipeline Based on Acoustic Signal

Jiang Zhao; Meng Shang; Jing Tian

doi:10.4028/www.scientific.net/AMM.511-512.389

Paper Titles

Error Processing Techniques of Integral Velocity Based on Frequency Spectrum Forecasting
p.370

FH-FSK Underwater Acoustic Control and Communication System Based on LDPC Code
p.375

Monitoring System for Plant Growth Environment Based on Zigbee/RS485
p.381

Query Recommendation Based on Document Content User Focuses on
p.385

Feature Extraction of the Small Leakage Diagnosis of Oil Pipeline Based on Acoustic Signal
p.389

Pseudo Two-Hop Distributed Consensus with Noise
p.393

Research on MWD Mud Pulse Signal Waveform Identification Algorithm
p.397

Ultralow Frequency Standard Vibration Calibration System Based on DSP
p.402

Analysis on Graduate Employment Based on Data Warehouse
p.406

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 511-512Feature Extraction of the Small Leakage Diagnosis...

Feature Extraction of the Small Leakage Diagnosis of Oil Pipeline Based on Acoustic Signal

Abstract:

This paper introduces the related theory of sound waves , we collect the data through the acoustic wave sensors of the pipeline fault diagnosis system platform, decompose the signals to five layers by Mallat algorithm and wavelet function db4, compare the normal waves and leakage acoustic signal spectrum, and then get the power spectrum estimation for the decomposed signal at each level, we can see the signals energy feature in different frequency band. Feature extraction method based on wavelet transform can make the category of signal characteristics fully displayed in the different resolution band, it has a good application prospect in the field of acoustic signal processing.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 511-512)

Pages:

389-392

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.511-512.389

Citation:

Cite this paper

Online since:

February 2014

Authors:

Jiang Zhao, Meng Shang, Jing Tian

Keywords:

Acoustic Signal, Fault Diagnosis, Feature Extraction, Pipeline Leakage, Wavelet Transform (WT)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Lu Wei, Wen Yumei. Leakage noise and its propagation in water pipeline [J]. Technical Acoustics, 2007, 26(5): 871- 872.

Google Scholar

[2] LEI Lin-yuan. Detection and waste detection of urban underground pipeline [M]. Beijing: Metallurgical Industry Press, 2003: 126- 128.

Google Scholar

[3] Yu Kaiping, Yang Bingyuan. Time-frequency analysis and wavelet transform[J]. Journal of Harbin institute of technology university, 2000, 32(2): 36-39.

Google Scholar

[4] Li Lun, Li Zhihua. A Method for Fault Diagnosis of Analog Circuits Based on Wavelet Multi-resolution Feature Extraction. Hohai University, 2012, 09, 046.

Google Scholar

[5] Zhu Daqi. Theory and practice of fault diagnosis for electronic equipment[M]. Beijing: Publishing House of Electronics Industry, (2004).

Google Scholar

[6] Misiunas D, Vitkovsky J, Olsson G，et al. Pipeline Break Detection Using Pressure Transient Monitoring[J]. Journal of Water Resources Planning and Management, 2005, 131( 4) : 316-325.

DOI: 10.1061/(asce)0733-9496(2005)131:4(316)

Google Scholar