Dynamic Modeling of Failure Events in Preventative Pipe Maintenance

IEEE Access

Hao Wu¹  Chao Zhang¹  Rashid Mehmood¹  Rongfang Bie¹  Anton Kos² 

[1] College of Information Science and Technology, Beijing Normal University, Beijing, China;Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia;

关键词: Point process;    pipe failure prediction;    event series modeling;   

DOI  :  10.1109/ACCESS.2018.2806340

来源: DOAJ

【 摘 要 】

Urban water supply network is ubiquitous and indispensable to city dwellers, especially in the era of global urbanization. Preventative maintenance of water pipes, especially in urban-scale networks, thus becomes a vital importance. To achieve this goal, failure prediction that aims to pro-actively pinpoint those “most-risky-to-fail”pipes becomes critical and has been attracting wide attention from government, academia, and industry. Different from classification-, regression-, or ranking-based methods, this paper adopts a point process-based framework that incorporates both the past failure event data and individual pipe-specific profile including physical, environmental, and operational covariants. In particular, based on a common wisdom of previous work that the failure event sequences typically exhibit temporal clustering distribution, we use mutual-exciting point process to model such triggering effects for different failure types. Our system is deployed as a platform commissioned by the water agency in a metropolitan city in Asia, and achieves state-of-the-art performance on an urban-scale pipe network. Our model is generic and thus can be applied to other industrial scenarios for event prediction..

【 授权许可】

Unknown