A Belief Rule-Based Safety Evaluation Approach for Complex Systems

Plenty of hazards underlie complex systems, which have negative effects on the normal functionality of engineering events. To minimize the uncertainty, a comprehensive preevent checkout is necessarily required to judge if the engineering events will be carried out successfully under current circumstance, through which further improvements can be made. A generic belief rule-based safety evaluation approach for large-scale complex systems is proposed. The overall system is firstly decomposed and filtered into the measurable attributes that may potentially contribute to uncertainty. Belief structure is then applied to measure the uncertainty of vagueness and incompleteness and represent heterologous information in a unified scheme. With this scheme, a rule base is established with all antecedents, consequents, and attributes presented in belief degrees, which is used to determine the relationship between attributes, aggregate the influences, and generate the final inference with evidential reasoning algorithm. In the end, an estimation of uncertainty is achieved in the representation of distribution. It describes how the systems perform with given conditions and sources. A numeric case in aerospace program is provided for feasibility illustration.