A Framework for Model-Based Diagnostics and Prognostics of Switched-Mode Power Supplies

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Published Sep 29, 2014
Honglei Li Xuerong Ye Cen Chen George Vachtsevanos

Abstract

With electrical power supplies playing an important role in the operation of aircraft systems and sub-systems, flight and ground crews need health state awareness and prediction tools that accurately diagnose faults, predict failures, and project remaining life of these onboard power supplies. Among onboard power supplies, switch-mode power supplies are commonly used where their weight, size, and efficiency make them preferable to conventional transformer-based power supplies. In this paper, we present a framework of diagnostics and prognostics methodology based on an equivalent circuit system simulation model developed from a commercially available switch-mode power supply, and empirical component degradation models. In industrial applications, case-specified modifications can be made according to specific experimental or service conditions of different commercial products. First, the developed simulation model is validated through experimental testing. Then, a series of data are collected from simulation to build the baseline and fault databases under a fixed load profile. Next, promising features are extracted from sensed parameters, and further data analysis are conducted to estimate the current health condition and to predict the remaining useful life of the target system. Some highlights of the work are included but not only limited to the following aspects: first, the methodology is based on electronic system simulation instead of traditional accelerated testing by employing a high-fidelity system simulation model and empirical critical component degradation models; second, efforts are made in this preliminary work to adapt proven prognostics and health management techniques from machinery to electronic health management, with the goal of expanding the realm of electronic diagnostics and prognostics.

How to Cite

Li , H. ., Ye, X. ., Chen, C. ., & Vachtsevanos, G. . (2014). A Framework for Model-Based Diagnostics and Prognostics of Switched-Mode Power Supplies. Annual Conference of the PHM Society, 6(1). https://doi.org/10.36001/phmconf.2014.v6i1.2335
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Keywords

electronics PHM, fault detection, fault diagnosis, failure prognosis, particle filter, model-based diagnosis and prognosis

References
Brown, D. W., Kalgren, P. W., & Roemer, M. J. (2007). Electronic Prognostics – A Case Study Using Switched- Mode Power Supplies (SMPS). IEEE Instrumentation and Measurement Magazine, vol. 10(4), pp. 20-26.

Brown, D. W., Abbas, M., Ginart, A., Ali, I.N., Kalgren, P. W., & Vachtsevanos, G. J. (2012). Turn-Off Time as an Early Indicator of Insulated Gate Bipolar Transistor Latch-up, IEEE Transactions on Power Electronics, vol. 27(2), pp. 479-89.

Goodman, D., Hofmeister, J., & Judkins, J. (2007). Electronic Prognostics for Switched Mode Power Supplies. Microelectronics Reliability, vol. 47(12), pp. 1902-6.

Li, D., & Li, X. (2012). Study of Degradation in Switching Mode Power Supply Based on the Theory of PoF. International Conference on Computer Science and Service System, Aug. 2012, pp. 1976-1980.

Luo, J., Pattipati, K.R., Qiao, L., & Chigusa, S., (2008). Model-based Prognostic Techniques Applied to a Suspension System. IEEE Transactions on System, Man and Cybernetics, vol. 38(5), pp. 1156-1168.

MIL-HDBK-217F, Reliability Prediction of Electronic Equipment (1991). Department of Defense. Washington D.C..

Orchard, M. E., & Vachtsevanos, G. J., (2007). A Particle Filtering Approach for On-line Failure Prognosis in A Planetary Carrier Plate. International Journal of Fuzzy Logic and
Intelligent Systems, vol. 7(4), pp. 221-227.

Orsagh, R., Brown, D. W., Roemer, M., Dabvey, T., & Hess, A. (2005). Prognostic Health Management for Avionics System Power Supplies. 2005 IEEE Aerospace Conference (IEEE Cat. No. 05TH8788), pp. 3585-91.

Zhang, H., Kang, R., Luo, M. & Pecht, M. (2009). Precursor Parameter Identification for Power Supply Prognostics and Health Management. IEEE 8th International Conference on Reliability, Maintainability and Safety, Jul. 2009, pp. 883–887.

Zhai, G., Zhou, Y., & Ye, X. (2013). A Tolerance Design Method for Electronic Circuits Based on Performance Degradation. Quality and Reliability Engineering International. DOI: 10.1002/qre.1621.
Section
Poster Presentations

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