A new risk assessment method based on belief rule base and fault tree analysis

Author:

Zhu Hai-Long1,Liu Shan-Shan1ORCID,Qu Yuan-Yuan2,Han Xiao-Xia3,He Wei13,Cao You3

Affiliation:

1. School of Computer Science and Information Engineering, Harbin Normal University, Harbin, China

2. Heilongjiang Agricultural Engineering Vocational College, Harbin, Heilongjiang, China

3. Rocket Force University of Engineering, Xi’an, Shaanxi, China

Abstract

Risk assessment methods are often used in complex industrial systems to avoid risks and reduce losses. The existing methods have not effectively solved the problems of lack of evaluation data and the interpretability of the entire evaluation process. This paper proposes a new risk assessment model based on the belief rule base (BRB) and Fault Tree Analysis (FTA). The FTA algorithm overcomes the difficulties of traditional BRB model in obtaining expert knowledge, clear indicators, and establishing logical relationships. This method establishes FTA rules based on the BRB model and expands the knowledge base through the FTA algorithm. A Bayesian network is applied as a conversion bridge between the FTA and BRB model. In addition, the model is optimized to reduce the uncertainty in the model. The method proposed is described by a case and its effectiveness is verified.

Funder

the Natural Science Foundation of China

the Natural Science Foundation of Heilongjiang Province of China

the Natural Science Foundation of School of Computer Science and Information Engineering, Harbin Normal University

the Ph.D. research start-up Foundation of Harbin Normal University

the Shaanxi Outstanding Youth Science Foundation

Publisher

SAGE Publications

Subject

Safety, Risk, Reliability and Quality

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