Creation of LIVE Digital Twin for Prognostics and Predictive Maintenance of Rotating Machineries (LIVE for 2PM)

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Due to the pandemic, the regular in-person inspection of the critical Rotating Machineries (RM) in hydropower, wind energy, and transportation were interrupted. Unfortunately, RM typically deteriorate their balance condition dynamically, due to wear, thermal bending, dirt collection, insulation failure, partial discharge, fault currents, thermal stress due to overloading, etc., and gradually develop concerning vibratory unbalance responses affecting RM performance and lifespan. Failure of RM in applications such as turbomachines, electromotors, generators, pumps, jet fans, etc. creates enormous unscheduled repair costs and more importantly may put human life in danger. This project aims to develop methodologies required to employ the concept of LIVE Digital Twin for Prognostics and Predictive Maintenance (LIVE for 2PM) of RM highly critical assets. The term "LIVE" refers to the first letters of the four phases in the methodology, i.e. Learn, Identify, Verify, and Extend. The key feature in LIVE digital Twins is multi-physics simulation solutions developed in alternative levels and modes, which are supported by artificial neural network and deep learning tools. LIVE Digital Twin allows Learning the behavioral patterns of individual RM considering their specifications, environment and customized factors. It Identifies the locations and types of sensors and the sensing procedures to Verify the possibilities for progressively increasing defects. It Extends the life of RM by advising predictive maintenance avoiding its failure. Implementation of LIVE Digital Twin not only reduces the needs for in-person inspection during the pandemic, but also can result in significant improvement in asset management of the critical Canadian infrastructures for energy and transportation sectors with predictive maintenance, reduced cost of repair, reduced frequency in replacing parts, shorter down-time of the corresponding highly critical infrastructures, reduced waste, and increased life-span of critical machines. All of these result in significant economic growth for a chain of industries and also a noticeable welfare of the society.