Pipeline multi-sensor data integration based on D-S evidence theory
Qimin Yang · Oil & Gas Storage and Transportation · 2014
In order to ensure the accuracy and credibility of pipeline detection, multiple detection techniques i.e. multisensor are commonly used to detect the same part, but the detected data, miscellaneous and redundant, needs to be integrated and processed. By using D-S(Dempster-Shafer) evidence theory, this paper sets up a process model of multi-sensor data integration for pipeline, and presents the process of data integration. Based on detective credibility of various sensors to different defects, detected data is integrated by using D-S evidence theory, and types of defect are determined according to D-S evidence theory. The results show that by using D-S to integrate data in the testing process, and keeping high credibility data, a clearer decision can be made, abandoning interferential data, saving storage space, good for data storage, and achieving intelligent detection in long distance.