多传感器输油管道检测数据融合技术

Data fusion research in multi-sensor pipeline detection

结合输油管道所处的特殊环境下的完全链接的模糊推理系统(F-CONFIS)和D-S证据理论,将多传感器网络的数据融合技术应用到海底输油管道的腐蚀检测上,提出了一种基于F-CONFIS和D-S证据理论的多传感器网络数据融合的海底输油管道腐蚀检测系统。该系统可提高对输油管道腐蚀程度的识别精度。

A novel algorithm for the corrosion detection of undersea pipeline is proposed. The model of the algorithm is established by using the fully connected neural fuzzy inference system model （F-CON- FIS） and Dempster-Shafer （DS） theory on the information fusion of a multi-sensor network. An undersea pipeline corrosion detection system based on the algorithm is proposed and can improve the identifying accuracy of the corrosion extent.