An Adaptive Particle Filtering-based Framework for Real-time Fault Diagnosis and Failure Prognosis of Environmental Control Systems



Published Sep 25, 2011
Ioannis A. Raptis George Vachtsevanos


Maintenance of critical or/complex systems has recently moved from traditional preventive maintenance to Condition Based Maintenance (CBM) exploiting the advances both in hardware (sensors / DAQ cards, etc.) and in software (sophisticated algorithms blending together the state of the art in signal processing and pattern analysis). Along this path, Environmental Control Systems and other critical systems/processes can be improved based on concepts of anomaly detection, fault diagnosis and failure prognosis. The enabling technologies borrow from the fields of modeling, data processing, Bayesian estimation theory and in particular a technique called particle filtering. The efficiency of the diagnostic approach is demonstrated via simulation results.

How to Cite

A. Raptis, I. ., & Vachtsevanos, G. . (2011). An Adaptive Particle Filtering-based Framework for Real-time Fault Diagnosis and Failure Prognosis of Environmental Control Systems. Annual Conference of the PHM Society, 3(1).
Abstract 351 | PDF Downloads 139



fault detection, particle filtering, failure prognosis, Environmental Control Systems

Braun, J. (2003). Automated Fault Detection and Diagnostics for Vapor Compression Cooling Equipment. Transaction of the ASME, 125, 266-274.

Breuker, M., & Braun, J. (1998). Common faults and their impacts for rooftop air conditioners. International Journal of HVAC&R Reserach, 4, 303-318.

Chen, C., Brown, D., Sconyers, C., Vachtsevanos, G., & Zhang, B. (2010). A .NET framework for an integrated fault diagnosis and failure prognosis architecture. In IEEE AUTOTESTCON.

Chen, C., Vachtsevanos, G., & Orchard, M. (2010). Machine remaining useful life prediction based on adaptive neuro-fuzzy and high-order particle filtering. In Annual Conference of the Prognostics and Health Management Society.

Chen, C., Zhang, B., & Vachtsevanos, G. (n.d.). Prediction of machine health condition using neuro-fuzzy and Bayesian algorithms. (To be published in IEEE Transactions on Instrumentation and Measurement)

Cheng, T., He, X.-D., & Asada, H. (2004). Nonlin- ear observer design for two-phase flow heat exchangers of air conditioning systems. In Ameri- can Control Conference, 2004. Proceedings of the 2004 (Vol. 2, p. 1534 - 1539 vol.2).

Comstock, M., Braun, J., & Groll, E. (2002). A survey of common faults for chillers. ASHRAE Transactions, 108, 819-825.

Grald, E. W., & MacArthur, J. (1992). A moving-boundary formulation for modeling time- dependent two-phase flows. International Journal of Heat and Fluid Flow, 13(3), 266 - 272.

He, X. (1996). Dynamic Modeling and Multivariable Control of Vapor Compression Cycles in Air Conditioning Systems. Unpublished doctoral dissertation, Massachusetts Institute of Technology.

He, X.-D., & Asada, H. (2003). A new feedback linearization approach to advanced control of multi- unit HVAC systems. In American Control Conference, 2003. Proceedings of the 2003 (Vol. 3, p. 2311 - 2316 vol.3).

Li, H., & Braun, J. (2003). An Improved Method for Fault Detection and Diagnosis Applied to Packaged Air Conditioners. American Society of Heating, Refrigerating and Air Conditioning Engineers, 109, 683-692.

Merritt, H. (1967). Hydraulic Control Systems. John Wiley & Sons.

Navarro-Esbri, J., Torrella, E., & Cabello, R. (2006). A vapour compression chiller fault detection technique based on adaptative algorithms. Application to on-line refrigerant leakage detection. International Journal of Refrigeration, 29, 716-723.

Orchard, M., & Vachtsevanos, G. (2007). A particle filtering-based framework for real-time fault diagnosis and failure prognosis in a turbine engine. In Control Automation, 2007. MED ’07. Mediterranean Conference on (p. 1 -6).

Orchard, M., & Vachtsevanos, G. (2009). A particle- filtering approach for on-line fault diagnosis and failure prognosis. Transactions of the Institute of Measurment and Control, 31, 221-246.

Rasmussen, B. (2005). Dynamic Modeling and Advanced Control of Air Conditioning and Refrigeration Systems. Unpublished doctoral dissertation, University of Illinois.

Rossi, T., & Braun, J. (1997). A statistical, rule-based fault detection and diagnostic method for vapor compression air conditioners. International Journal of HVAC&R Reserach, 3, 19-37.
Stylianou, M., & Nikanpour, D. (1996). Performance monitoring, fault detection, and diagnosis of reciprocating chillers. ASHRAE Transactions, 102, 615-627.

Wedekind, G., Bhatt, B., & Beck, B. (1978). A System Mean void Fraction Model For Predicting Various Transient Phenomena Associated with Two-Phase Evaporating and Condensing Flows. International journal of Multiphase Flow, 4, 97-114.
Technical Research Papers

Most read articles by the same author(s)

1 2 > >>