Fleet Learning: Active learning-assisted semi-supervised learning for fault detection anddiagnostics with imbalanced dataset

Xiaomeng Peng, Xiaoning Jin, Shiming Duan, and Chaitanya Sankavaram   Data-driven Fault Detection and Diagnostics (FDD) methods often assume that sufficient labeled samples are class-balanced and faulty classes in testing are precedent or seen previously during model training. When monitoring a large fleet of assets at scale, these assumptions may be violated:(I) only a limited number…

Stochastically-dependent Multi-component Degradation and Failure

Mengkai Xu, Xiaoning Jin, Sagar Kamarthi, Md. Noor-E-Alam Unexpected component failures in a mechanical system always cause loss of performance and functionality of the entire system. Condition based maintenance decisions for a multi-component mechanical system are challenging because the interdependence of individual components’ degradation is not fully understood and lack of physical models.  An extended…