Abstract
Oils are mainly transported by pipe in long distance for its high efficiency. While oil pipe leakage will cause serious social and environmental consequences, e.g. fire even life lost, water and soil pollution. Thus it is important to recognize pipe leakage at initial stage in engineering practice. In this research, a negative pressure wave based detection method was established for pipeline leakage recognition. Suitable parameters of negative pressure wave signals with significant difference for different working conditions were selected. Principal Component Analysis (PCA) method was conducted to reduce the dimensions of the negative pressure wave vector. Self-organizing map (SOM) Neural network was finally adopted to identify the signals for different working conditions. The proposed method was validated by experimental data, which shows that the methodology gives a high recognition rate, which can be referenced in pipe monitoring in engineering practice.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
