Although typical Health and Usage Monitoring Systems (HUMS) have the potential to support the goal of transitioning from time based part replacement decisions to performing maintenance upon evidence of need, their ability to diagnose component faults in their early stages in vehicle drive systems is limited, and, consequently, the task of prognosis in Condition Based Maintenance (CBM) programs is often underrepresented in the field.

Accurate and reliable fault diagnosis and prognosis of safety or mission critical components/ subsystems in complex engineering systems present major challenges to the Condition-Based Maintenance (CBM) or Prognostic and Health Management (PHM) designer. A crucial step in the development of CBM/PHM strategies relates to the designer’s ability to understand and model the incipient failure or fault modes and mechanisms. A single fault growth model might not be often capable to capture a sequence of fault behaviors.