Recommended Reading

During PHM’09, Steve Engel suggested that I compile a “Serdar’s reading list” for PHM. A year later, I got around to doing it. I also asked a few colleagues for their favorite references. Here is a brief list of articles and books that should be of interest to the general PHM community (in no particular order).

Books

• Intelligent Fault Diagnosis and Prognosis for Engineering Systems by Vachtsevanos, Lewis, Roemer, Hess, and Wu (2006): a great reference book for diagnostic, prognostics, PHM, and condition-based monitoring technologies.
• System Health Management by Johnson, Kessler, Patterson-HIne, Gormley, et al. (2011): an upcoming reference volume covering the state-of-the-art in systems health engineering and management for aerospace systems.
• Pattern Classification by Duda, Hart, and Stork (2000): the reference textbook for analyzing and understanding complex multidimensional data sets.
• Beyond the Kalman Filter: Particle Filters for Tracking Applications by Ristic, Arulampalam, and Gordon (2004): great reference for particle filters, one of the most robust methods for RUL estimation applications.
• Sequential Monte Carlo Methods in Practice by Doucet, de Freitas, and Gordon (2001): useful background on statistical methods often used in on-line data analysis.

Technical Reports

• Space Shuttle Operations and Infrastructure A Systems Analysis of Design Root Causes and Effects by Carey McCleskey: fascinating NASA Technical Report discussing the impact of early design-stage decisions on total lifecycle costs (and operational availability) for the Space Shuttle – recommended read for all system engineers.
• Columbia Accident Investigation Board Final Report: another must-read for all system engineers – beginners and veterans alike.

Articles

• Metrics for Offline Evaluation of Prognostic Performance by Saxena et al.: the first comprehensive article that proposes a set of reference metrics that can be used to understand and compare the performance of prognostic approaches.
• Challenges, issues, and lessons learned chasing the “Big P”. Real predictive prognostics. Part 1 by Hess, Calvello, and Frith: a good summary of the PHM approach for Joint Strike Fighter and the implications of PHM on system lifecycle costs. Unfortunately, the full article is not available for download without a paid subscription to IEEE’s archives.
• Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework by Saha and Goebel (Proceedings of the Annual Conference of the PHM Society 2009): a reference article that establishes the state-of-the-art in Li-ion battery prognostics.
• A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking by Arulampalam, Maskell, Gordon, and Clapp (IEEE Transactions on Signal Processing, vol. 50, no. 2, pp. 174–188, 2002) another good reference for the use of particle filters for on-line data analysis. Once again, the full article is NOT available online in an unrestricted fashion.