Department of Mechanical and Aerospace Engineering

IEEE CASE Best Student Paper Award

System performance tracking, as the integrated result of state identification, diagnosis and prognosis, plays a critical role in the decision-making processes for maintenance and inventory management. The paper presented a new approach to performance degradation tracking based on particle filtering, covering both gradual deterioration and abrupt fault occurrence.  By improving   resampling as part of the particle filtering process, tracking of performance degradation under varying rates has been achieved.

The developed method is demonstrated for automatic fault detection and performance tracking for the heating, ventilation, and air conditioning (HVAC) systems, using heat exchanger as an example. The method can be expanded into other application domains, such as traffic monitoring for vehicles or parking space prediction in building a “smart parking” system.

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