A novel RUL prognosis methodology of multilevel system with cascading failure: Subsea oil and gas transportation systems as a case study. (15th December 2021)

• Record Type: Journal Article
• Authors: Cai, Baoping; Shao, Xiaoyan; Yuan, Xiaobing; Liu, Yonghong; Chen, Guoming; Feng, Qiang; Liu, Yiqi; Ren, Yi
• Is Part Of: Ocean engineering. Volume 242(2021)
• Publication Date: 2021-12-15
• Subjects: Cascading failure -- Multilevel systems -- Dynamic Bayesian network -- Remaining useful life -- Position and function importance; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2021.110141
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Cascading failure has a great negative impact on the operation of multilevel systems. Although the frequency of this kind of failure is lower than that of general failure, it may cause outage and considerable human and economic losses. In this paper, a novel modeling methodology of cascading failure based on position importance and function importance is proposed by using dynamic Bayesian networks, and the remaining useful life (RUL) of multilevel systems considering cascading failure is estimated. By detecting the working state of the nodes, the position and function importance of the nodes are determined, and the performance of the next layer of related nodes is calculated. Through calculating iteratively to the last level, the number of failure nodes is finally determined, and the overall performance of the multilevel systems is evaluated. A subsea transportation system with three-level network and four nodes in each level is used to demonstrate the application of the proposed methodology, and the feasibility of the methodology is analyzed. The results show that the RUL of the systems is significantly reduced when considering the cascading failure, which is quite different from the degradation of the non-cascading failure mode. Highlights: A novel methodology of performance evaluation based on position importance and function importance is proposed. The modeling process of influence relationship for cascading failure of multilevel systems is studied. RUL estimation is conducted by inputting the information that detected by the sensor into the DBNs as evidence.