Evolving Design Model Synchronization for System Health Management Using Laplace Approximation

Abstract

Lifecycle health management plays an increasingly important role in realizing resilience of aging complex engineered systems since it detects, diagnoses, and predicts system-wide effects of adverse events, therefore enables a proactive approach to deal with system failures. To address an increasing demand to develop high-reliability low-cost systems, this paper presents a new platform for operational stage system health management, referred to as Evolving Design Model Synchronization (EDMS), which enables health management of aging engineered systems by efficiently synchronizing system design models with degrading health conditions of actual physical system in operation. A Laplace approximation approach is employed for the design model updating, which can incorporate heterogeneous operating stage information from multiple sources to update the system design model based on the information theory, thereby increases the updating accuracy compared with traditionally used Bayesian updating methodology. The design models synchronized over time using sensory data acquired from the system in operation can thus reflect system health degradation with evolvingly updated design model parameters, which enables the application of failure prognosis for system health management. One case study is used to demonstrate the efficacy of the proposed approach for system health management.