Reliability Assurance Methodology Incorporating Advanced Diagnostics and Prognostics

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Today’s society depends on the reliable, uninterrupted operation of colossal engineering systems such as power grids, telecommunication networks, pipelines, and air, ground, and water transportation systems. Despite important advancements in reliability assurance methodologies over the past 70 years, accidents and major service disruptions affecting millions of people still occur frequently. The fact that deterioration occurs as a device is used and inherent uncertainty exists in material properties and degradation behaviors makes traditional time-based reliability assurance methods inadequate. Recent thrusts of the reliability research community are to incorporate condition monitoring and advanced diagnostics and prognostics into online reliability assurance of sophisticated engineering systems. This research program aims to develop effective health indicators of equipment deterioration by conducting dynamic simulation and laboratory experiments on a gearbox test rig, develop information fusion approaches to make inferences on the hidden health state of the equipment, estimate the remaining useful life distribution of a running system utilizing information on health indicators and inferred health states, evaluate system health state distribution based on component state distributions and dependency relationships among components, and develop dynamic maintenance optimization approaches to ensure safe, reliable and cost-effective operation of engineering systems. The proposed research will generate fundamental theorems, efficient algorithms, and practical models for detection and identification of impending failure modes, for reliability evaluation of multi-state systems, for prediction of the remaining useful life of running equipment, and for dynamic operation and maintenance decision making of engineering systems. The results to be generated have excellent potential for applications in design, manufacture, and operation of modern engineering systems such as pipelines, petro-chemical refineries, power generators, telecommunication networks, power grids, and transportation vehicles. The results of this research can be applied in industrial settings to benefit the Canadian industries directly. Highly qualified personnel will be trained for the Canadian industries.