公开(公告)号：US09797799B2

公开(公告)日：2017-10-24

申请号：US14692502

申请日：2015-04-21

Applicant: Northeastern University

Inventor： Huaguang Zhang ,  Dazhong Ma ,  Jian Feng ,  Jinhai Liu ,  Gang Wang ,  Zhenning Wu ,  Qiuye Sun ,  Xiaoyu Li

IPC: G01M3/28 ,  G01M3/24

CPC classification number: G01M3/2807 ,  G01M3/243

Abstract: The present invention relates to an intelligent adaptive system and method for monitoring leakage of oil pipeline networks based on big data. The present invention effectively analyzes a large amount of data collected on site within a reasonable time period and obtains a state of a pipeline network by an intelligent adaptive method, thereby obtaining a topological structure of a pipeline network. The present invention specifically adopts a flow balance method in combination with information conformance theory to analyze whether the pipeline network has leakage; small amount of leakage and slow leakage can be perfectly and accurately alarmed upon detection; as a generalized regression neural network is adopted to locate a leakage of the pipeline network, an accuracy of a result is increased. Therefore, the present invention adopts a policy and intelligent adaptive method based on big data to solve problems of detecting and locating leakage of the pipeline network.