Two Prognostics Center of Excellence groups won awards for their papers at the annual Conference of the Prognostics and Health Management Society, 2011, held in Montreal, Canada, from September 25th - 29th, 2011. Matthew Daigle, Kai Goebel, Sriram Narasimhan, Indranil Roychoudhury, Bhaskar Saha, and Sankalita Saha won the best theoretical paper award for their paper, “Investigating the Effect of Damage Progression Model Choice on Prognostics Performance.” Gautam Biswas, José R. Celaya, Kai Goebel, Chetan Kulkarni, and Sankalita Saha won the best application paper award for their paper, “A Model-Based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging.”
BACKGROUND: Within the SSAT project, health management techniques and, specifically, fault prognostics techniques, are explored for components, subsystems, and systems in aeronautics. The paper, “Investigating the Effect of Damage Progression Model Choice on Prognostics Performance,” explores the relationship between the quality of prognostics models and prognostics algorithm performance for model-based approaches. The success of model-based approaches to systems health management depends largely on the quality of the underlying models. In model-based prognostics, it is particularly the quality of the damage progression models, i.e., the models describing how damage evolves as the system operates, that determines the accuracy and precision of remaining useful life predictions. Several common forms of these models are generally assumed in the literature, but are often not supported by physical evidence or physics-based analysis. Using a centrifugal pump as a case study, different damage progression models are developed and simulation experiments are used to investigate how model changes influence prognostics performance. The results demonstrated that, in some cases, simple damage progression models are sufficient even when the underlying damage progression is more complex. But, in general, the results show a clear need for damage progression models that are accurate over long time horizons under varied loading conditions.
The paper, “A Model-Based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging,” presents a prognostics methodology for electrolytic capacitors. Electrolytic capacitors are known for their high failure rate in switched-mode power supplies and power electronics for motor controls. The methodology presented is based on long-term accelerated aging experiments applying electrical overstress to a set of capacitors. In particular, in-situ measurements from the aging test are used to create an empirical degradation model, which in turn is used in a Bayesian tracking framework to estimate the state of health of the capacitors and then to predict time to failure. A Kalman filter is used considering static degradation model parameters. The objective of this work is twofold; first, to further the PHM research at the component level for electrolytic capacitors, and second, to use the capacitor prognostics as a case study on validation of previously proposed model-based approaches for prognostics.
NASA PROGRAM FUNDING: This work was funded under the System-wide Safety and Assurance Technologies (SSAT) Project of the Aviation Safety Program for ARMD.
DEVELOPMENT TEAM: José R. Celaya (SGT), Matthew Daigle (UARC), Kai Goebel (NASA), Sriram Narasimhan (UARC), Indranil Roychoudhury (SGT), Bhaskar Saha (MCT), and Sankalita Saha (MCT)
COLLABORATORS: Gautam Biswas (Vanderbilt University) and Chetan Kulkarni (Vanderbilt University)
Contact: José R. Celaya, Matthew Daigle