Title :
Improving Digital System Diagnostics Through Prognostic and Health Management (PHM) Technology
Author :
Baybutt, M. ; Baybutt, M. ; Minnella, C. ; Ginart, A.E. ; Kalgren, P.W. ; Roemer, M.J. ; Roemer, M.J.
Abstract :
This paper presents work on the development of a robust online digital electronic health management system. The presented technical approach integrates collaborative diagnostic and prognostic techniques from engineering disciplines, including statistical reliability, damage accumulation modeling, physics-of-failure modeling, signal processing and feature extraction, and automated reasoning algorithms. The prognostic and health management (PHM) approach is based on a paradigm of minimally invasive onboard monitoring paired with model-based estimates to deliver timely and accurate health assessments.
Keywords :
failure analysis; fault diagnosis; feature extraction; life testing; semiconductor device reliability; semiconductor device testing; signal processing; PHM technology; accelerated aging tests; automated reasoning algorithm; damage accumulation modeling; digital system diagnostics; feature extraction; health assessment; online digital electronic health management system; physics-of-failure modeling; prognostics; semiconductor device failure; signal processing; statistical reliability; Accelerated aging; automated reasoning algorithms; digital system fault diagnosis; digital system testing; microprocessors diagnostics; physics-of-failure (PoF) modeling; prognostic and health management (PHM);
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2008.2005966
