杨启明, 张力明. 基于D-S证据理论的管道多传感器数据融合[J]. 油气储运, 2014, 33(3): 252-254. DOI: 10.6047/j.issn.1000-8241.2014.03.006
引用本文: 杨启明, 张力明. 基于D-S证据理论的管道多传感器数据融合[J]. 油气储运, 2014, 33(3): 252-254. DOI: 10.6047/j.issn.1000-8241.2014.03.006
YANG Qiming, ZHANG Liming. Pipeline multi-sensor data integration based on D-S evidence theory[J]. Oil & Gas Storage and Transportation, 2014, 33(3): 252-254. DOI: 10.6047/j.issn.1000-8241.2014.03.006
Citation: YANG Qiming, ZHANG Liming. Pipeline multi-sensor data integration based on D-S evidence theory[J]. Oil & Gas Storage and Transportation, 2014, 33(3): 252-254. DOI: 10.6047/j.issn.1000-8241.2014.03.006

基于D-S证据理论的管道多传感器数据融合

Pipeline multi-sensor data integration based on D-S evidence theory

  • 摘要: 为了保证管道检测的准确度与可信度,通常需要采用多种检测技术即多传感器对同一部位进行检测,但检测的数据量大繁冗,需要进行融合与处理。利用D-S(Dempster-Shafer)证据理论,建立了应用于管道多传感器数据融合的流程模型,阐明了数据的融合流程。算例中根据各个不同传感器对不同缺陷的检测置信度,利用D-S证据理论对检测数据进行有效融合,最后根据D-S规则对缺陷类型进行判定。结果表明:在检测过程中利用D-S进行数据融合,保留置信度高的数据,可以得到更明确的判决结果,舍弃干扰数据,节省存储空间,有利于数据存储,实现长距离智能检测。

     

    Abstract: In order to ensure the accuracy and credibility of pipeline detection, multiple detection techniques i.e. multi-sensor 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.

     

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