@inproceedings{53895855d0f642e8b65cfbc021a7aceb,
title = "A spatial statistical approach for risk-based inspection of sewer network",
abstract = "In this paper, a developed risk-based methodology for optimizing the different inspected regions of pipeline networks is proposed to provide the reasonable and quantitative risk information for decision makers. This method established a novel risk model, which combines spatial statistical technology and risk assessment model to simulate the risk level of all parts of pipeline network, so as to give priority to pipeline network inspection. The risk in different regions of the pipeline network is derived from the product of failure probability and failure severity in our approach. As a case study, the inspection priority of a city's sewer network is carried out according to our method and, consequently, the feasibility of this method is verified.",
keywords = "Poisson process, Risk-assessment, Risk-based inspection, Risk-based optimization",
author = "Yangjie Zhang and Huina Mu and Xiaojian Yi",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019 ; Conference date: 15-08-2019 Through 17-08-2019",
year = "2019",
month = aug,
doi = "10.1109/SDPC.2019.00171",
language = "English",
series = "Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "898--903",
editor = "Chuan Li and Shaohui Zhang and Jianyu Long and Diego Cabrera and Ping Ding",
booktitle = "Proceedings - 2019 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2019",
address = "United States",
}