TY - GEN
T1 - A fault propagation modeling and analysis method based on model checking
AU - Chen, Lu
AU - Jiao, Jian
AU - Fan, Jiping
AU - Ren, Fuchun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/5
Y1 - 2016/4/5
N2 - Fault propagation identification is an indispensable task in complex system safety analysis. With the growing of system scale and complexity, it is hard for the traditional safety analysis techniques, which depend mainly on analysts' personal skills and experiences, to keep completeness and timeliness; moreover, some failure modes may be neglected and failure effects misjudged during the analysis. Formal science provides a new way to solve this problem, where formal verification method such as model checking can automatically validate whether the system design satisfies the given safety requirements, which can reduce an analysts' repetitive work and design cost, and improve the efficiency and quality of safety analysis. However, there is lack of a deliberate and reasonable way to build system models because of the diversity and flexibility of languages used for model checking, which results in that it is difficult to specify and model system quickly and accurately, and leads to some deviation in model checking. In this paper, a system modeling and safety property specifying approach using symbolic language SMV is proposed, including guidance on the mapping relationships between the formal language elements and system functions, architecture and failure modes; moreover, how to define system specifications and safety requirements using temporal logic formulas is discussed as well. Finally, a case study about airborne system safety analysis is provided, in which the counter-examples that do not meet system specifications can be identified automatically using model checker NuSMV to find out fault events and their propagation that can result in accidents.
AB - Fault propagation identification is an indispensable task in complex system safety analysis. With the growing of system scale and complexity, it is hard for the traditional safety analysis techniques, which depend mainly on analysts' personal skills and experiences, to keep completeness and timeliness; moreover, some failure modes may be neglected and failure effects misjudged during the analysis. Formal science provides a new way to solve this problem, where formal verification method such as model checking can automatically validate whether the system design satisfies the given safety requirements, which can reduce an analysts' repetitive work and design cost, and improve the efficiency and quality of safety analysis. However, there is lack of a deliberate and reasonable way to build system models because of the diversity and flexibility of languages used for model checking, which results in that it is difficult to specify and model system quickly and accurately, and leads to some deviation in model checking. In this paper, a system modeling and safety property specifying approach using symbolic language SMV is proposed, including guidance on the mapping relationships between the formal language elements and system functions, architecture and failure modes; moreover, how to define system specifications and safety requirements using temporal logic formulas is discussed as well. Finally, a case study about airborne system safety analysis is provided, in which the counter-examples that do not meet system specifications can be identified automatically using model checker NuSMV to find out fault events and their propagation that can result in accidents.
KW - NuSMV
KW - complex system
KW - fault propagation
KW - model checking
KW - safety analysis
UR - https://www.scopus.com/pages/publications/84968867612
U2 - 10.1109/RAMS.2016.7447978
DO - 10.1109/RAMS.2016.7447978
M3 - 会议稿件
AN - SCOPUS:84968867612
T3 - Proceedings - Annual Reliability and Maintainability Symposium
BT - Annual Reliability and Maintainability Symposium, RAMS 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Annual Reliability and Maintainability Symposium, RAMS 2016
Y2 - 25 January 2016 through 28 January 2016
ER -