Abstract
The fundamental concepts and methods of fault detection and diagnosis are reviewed. Faults are defined and classified as additive or multiplicative. The model-free approach of alarm systems is described and critiqued. Residual generation, using the mathematical model of the plant, is introduced. The propagation of additive and multiplicative faults to the residuals is discussed, followed by a review of the effect of disturbances, noise, and model errors. Enhanced residuals (structured and directional) are introduced. The main residual generation techniques are briefly described, including direct consistency relations, parity space, and diagnostic observers. Principal component analysis and its application to fault detection and diagnosis are outlined. The entry closes with some thoughts about future directions.
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Bibliography
Blanke M, Kinnaert M, Lunze J, Staroswiecki M (2016) Diagnosis and fault tolerant control, 3rd edn. Springer, Berlin/Heidelberg
Chen J, Patton RJ (1999) Robust model-based fault diagnosis for dynamic systems. Kluwer, Boston/Dordrecht/Amsterdam
Chow EJ, Willsky AS (1984) Analytical redundancy and the design of robust failure detection systems. IEEE Trans Autom Control AC-29:603–614
Edelmayer A, Bokor J, Keviczky L (1994) An H-infinity filtering approach to robust detection of failures in dynamic systems. In: 33rd IEEE conference on decision and control, Lake Buena Vista
Fang H, Ye H, Zhang M (2007) Fault diagnosis of networked control systems. Annu Rev Control 31:55–68
Frank PM, Wunnenberg J (1989) Robust fault diagnosis using unknown input observer schemes. In: Patton R, Frank P, Clark R (eds) Fault diagnosis in dynamic systems. Prentice Hall, Upper Saddle River
Gertler J (1991) A survey of analytical redundancy methods in fault detection and isolation. Plenary paper, IFAC safeprocess symposium, Baden-Baden
Gertler J (1998) Fault detection and diagnosis in engineering systems. Marcel Dekker, New York
Gertler J, Li W, Huang Y, McAvoy T (1999) Isolation enhanced principal component analysis. AICHE J 45:323–334
Isermann R (1984) Process fault detection based on modeling and estimation methods. Automatica 20:387–404
Isermann R (2010) Diagnosis methods for electronic controlled vehicles. Int J Veh Dyn Mobil 36:77–117
Kresta JV, MacGregor JF, Marlin TE (1991) Multivariate statistical monitoring of processes. Can J Chem Eng 69:35
Puig V, Ocampo-Martinez C, Perez R, Cembrano G, Quevedo J, Escobet T (eds) (2017) Real-time monitoring and operational control of drinking water systems. Springer, Cham
Sename O, Gaspar P, Bokor J (eds) (2013) Robust control and parameter varying approaches. Springer, Berlin/Heidelberg
Simani S, Castaldi P (2019) Fault diagnosis techniques for a wind turbine system. IntechOpen. https://doi.org/10.5772/intechopen.83810
White JE, Speyer JL (1987) Detection filter design: spectral theory and algorithm. IEEE Trans Autom Control AC-32:593–603
Willsky AS (1976) A survey of design methods for failure detection in dynamic systems. Automatica 12:601–611
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Gertler, J. (2021). Fault Detection and Diagnosis. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, Cham. https://doi.org/10.1007/978-3-030-44184-5_223
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DOI: https://doi.org/10.1007/978-3-030-44184-5_223
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