Information Fusion Technology In The Detection And Location Of Leaks In Water Pipelines,

With the rapid development of economy, the demand of the water for daily life rise day by day, it is a very important task to operate water pipeline in a good condition in the pipeline monitoring. The leakage of the pipeline will occur unavoidably due to some natural or human factors. This will not only result in serious waste of water resources, but also could threaten the safety of human life and property. Therefore, the research of the water pipeline leak detection and location not only has important theoretical significance, but also has great practical value.Single method is used widespreadly in the current pipeline leakage detection and localization research. There are many disadvantages, because it can not give consideration to multi-indexes of system. However, the Multi-Sensor information fusion can do, and many methods can be used through the technology. This paper puts forward a method for pipeline detection and localization based on information fusion technology.On the basis of object-oriented system analysis and design as well as the whole-system analysis of The Wanjiazhai Yellow River Diversion Project (YRDP),starting with the importance of pipeline transportation in economic development, this paper introduce the current methods of oil pipeline leakage detection and localization and analyze their principles, advantages and disadvantages. On base of the use of pressure and flow rate together as detection parameters, propose a technology based on information fusion for pipeline leak detection and location. The wavelet is used to reduce the noises in the signal of pressure and flow rate, and then use wavelet analysis method, correlation analysis method for detecting and localizing leakage point. Finally, the information fusion theory of Dempster-Shafer evidence is used to fuse the results of these two methods to detect and locate leakage point. The results of simulation show that information fusion method has higher precision and more accurate location than those single detection methods.