As electrical and electronic systems (EES) steadfastly increase their functional complexity and connectedness, they pose ever-growing challenges in fault analysis and prevention. Many EES faults are intermittent, emerging (new faults), or cascading, and cannot be addressed by the traditional component-level diagnostic design. Leveraging the latest advancements in Network Science, we take the holistic approach to model and analyze the highly interrelated in-vehicle EES as layered sub-networks of hardware components, software components, and communication links. We develop multi-partite, multi-attribute betweenness centrality measures to quantify the complexity and maintainability of the layered EES network. We then use the betweenness centrality distribution to identify fault analysis monitoring points and fault-mitigation strategies. The promising results obtained by our initial empirical study of an example in-vehicle EES presents a first step toward network-theory based IVHM.
How to Cite
fault detection, betweenness centrality, network-theory based IVHM
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