A research team led by Professor Wang Shaoping from the School of Automation Science and Electrical Engineering at Beihang University has made significant progress in addressing the reliability modeling and importance assessment of complex aviation hydraulic systems. Their research results, titled “Component uncertainty importance measure in complex multi-state system considering epistemic uncertainties”, have been published in Chinese Journal of Aeronautics.
Importance measures can be used to identify the vulnerable components in an aviation system at the early design stage. However, due to lack of knowledge or less available information on the component or system, the epistemic uncertainties may be one of the challenging issues in importance evaluation. In addition, the properties of the aircraft system, which are the fundamentals of the component importance measure, including the hierarchy, dependency, randomness, and uncertainty, should be taken into consideration.
To tackle these challenges, the team proposed the component Uncertainty Integrated Importance Measure (component UIIM), which considers multi-state epistemic uncertainties in complex multi-state systems. The degradation process for the components is described by a Markov model, and the system reliability model is developed using the Markov Hierarchal Evidential Network (MHEN). This network integrates evidence theory with interval-valued Markov models to quantify cognitive uncertainties during component degradation, providing probabilities for each possible state at any given time.
Fig.1 Flowchart of uncertainty importance measures evaluation procedure
The concept of integrated importance measure is then extended into component UIIM to evaluate the component criticality rather than the component state change criticality, from the perspective of system performance. A case study on displacement compensation hydraulic system is presented to show the effectiveness of the proposed uncertainty importance measure. The results show that the component UIIM can be an effective method for evaluating the component criticality from system performance perspective at the system early design.
Fig.2 Component reliability and system reliability curves
Fig.3 Component UIIM and UCIM varying with time
The research not only contributes significantly to aerospace engineering but also sets a new benchmark for reliability analysis in complex multi-state systems across various industries. By considering multiple uncertainties, it offers practical guidance for enhancing system robustness and safety, supporting more informed decision-making in the early stages of system design.
Editor: Han Xu, Lyu Xingyun
