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  • 标题:Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research
  • 本地全文:下载
  • 作者:Lizeth Torres ; Javier Jiménez-Cabas ; Omar González
  • 期刊名称:Journal of Marine Science and Engineering
  • 电子版ISSN:2077-1312
  • 出版年度:2020
  • 卷号:8
  • 期号:3
  • 页码:173
  • DOI:10.3390/jmse8030173
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:The purpose of this paper is to provide a structural review of the progress made on the detection and localization of leaks in pipelines by using approaches based on the Kalman filter. To the best of the author’s knowledge, this is the first review on the topic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, the paper gathers the results from different research groups such that these are presented in a unified fashion. For this reason, a classification of the current approaches based on the Kalman filter is proposed. For each of the existing approaches within this classification, the basic concepts, theoretical results, and relations with the other procedures are discussed in detail. The review starts with a short summary of essential ideas about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, brief discussions of some emerging research problems, such as the leak detection in pipelines transporting heavy oils; the main challenges; and some open issues are addressed.
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