<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Prestressed Concrete Cylinder Pipe (PCCP) is a widely used water pipe all over the world. A major cause of PCCP failure is the internal wire break, which will emit acoustic signal. In this paper, a hydrophone-based PCCP real-time monitoring and failure-prediction system was proposed. By applying wavelet energy normalization analysis to signal feature extraction and Support Vector Machine (SVM) to signal recognition, a high prediction accuracy of 98.33% was achieved. The result showed that the hydrophone-based PCCP failure prediction system is much more effective and economic in real application compared with electromagnetic method and acoustic fiber optical.</p></abstract>

Prestressed Concrete Cylinder Pipe (PCCP) is a widely used water pipe all over the world. A major cause of PCCP failure is the internal wire break, which will emit acoustic signal. In this paper, a hydrophone-based PCCP real-time monitoring and failure-prediction system was proposed. By applying wavelet energy normalization analysis to signal feature extraction and Support Vector Machine (SVM) to signal recognition, a high prediction accuracy of 98.33% was achieved. The result showed that the hydrophone-based PCCP failure prediction system is much more effective and economic in real application compared with electromagnetic method and acoustic fiber optical.

Prediction of PCCP Failure Based on Hydrophne Detecting

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Prediction of PCCP Failure Based on Hydrophne Detecting"}

Prestressed Concrete Cylinder Pipe (PCCP) is a widely used water pipe all over the world. A major cause of PCCP failure is the internal wire break, which will...

Prediction of PCCP Failure Based on Hydrophne Detecting

Published Online: Sep 05, 2013

Page range: 1582 - 1598

Received: May 12, 2013

Accepted: Aug 03, 2013

DOI: https://doi.org/10.21307/ijssis-2017-605

© 2013 Yuan Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.