Volume 3, Issue 4, August 2015, Page: 49-55
Review and Application of Model and Spectral Analysis Based Fault Detection and Isolation Scheme in Actuators and Sensors
H. Bal, Department of Industrial Technology, Jordan College of Agricultural Sciences and Technology, California State University, Fresno, California, USA
S. K. Mohanty, Colllege of Engineering, Biju Patnaik University of Technology, Bhubaneswar, Odisha, India
N. P. Mahalik, Department of Industrial Technology, Jordan College of Agricultural Sciences and Technology, California State University, Fresno, California, USA
B. B. Biswal, National Institute of Technology, Rourkela, India
Received: Jun. 15, 2015;       Accepted: Jun. 25, 2015;       Published: Jul. 10, 2015
DOI: 10.11648/j.acis.20150304.11      View  4116      Downloads  105
For condition monitoring of machineries and systems conventional method such as hardware or sensor based error checking scheme were in use. As the automated systems are becoming complex, recently most of the condition-monitoring schemes have been applying sophisticated analytical tools and methods to achieve improved performance. The objective of this paper is to demonstrate model based Fault Detection and Isolation (FDI) schemes for mechatronic systems and devices. First we have reviewed FDI approaches and implementation schemes. Then, we have developed two frameworks: model and spectral signature based for the implementation of FDI schemes. The model based feature estimation and spectral analysis based multiresolution methods are implemented in exemplar devices such as actuators and sensors used in mechatronic systems. Based on the frameworks, the diagnostics and isolation algorithms were developed using MATLAB code. The algorithms are capable of detecting and isolating faults within the systems. The study is comprehensive and the implementation scenarios can be extendible to many types of systems and devices used in the mechatronic domain.
FDI, Model-Based, Spectral Analysis, Multiresolution, ANN, FL
To cite this article
H. Bal, S. K. Mohanty, N. P. Mahalik, B. B. Biswal, Review and Application of Model and Spectral Analysis Based Fault Detection and Isolation Scheme in Actuators and Sensors, Automation, Control and Intelligent Systems. Vol. 3, No. 4, 2015, pp. 49-55. doi: 10.11648/j.acis.20150304.11
Juan Dai, Chen, C.L.P., Xiao-Yan Xu, Peng Hu, Condition monitoring on complex machinery for predictive maintenance and process control, IEEE International Conference on Systems, Man and Cybernetics, 2008. SMC 2008., vol., no., pp.3595,3600, 12-15 Oct. 2008
Dogan Gökhan and Murat Başaran, Condition monitoring of speed controlled induction motors using wavelet packets and discriminant analysis, Journal of Expert Systems with Applications, Volume 38 Issue 7, pp 8079-8086, 2011, Pergamon Press, Inc. Tarrytown, NY, USA
Rolf Isermann, Model-based fault-detection and diagnosis – status and applications, Annual Review in Control, 29 (2005) 71–85
Mohanty, S.K.; Mahalik, N., "Some Studies on FDI in Actuating Systems," Process Automation, Control and Computing (PACC), 2011 International Conference on , vol., no., pp.1,6, 20-22 July 2011, doi: 10.1109/PACC.2011.5979009
Mohanty, S, “Fault Detection in Mechatronic Systems”, PhD Thesis, 2006, Utkal University, India
Nadia Ben Amor, Multifont Arabic Characters Recognition Using Hough Transform and HMM/ANN Classification, Journal of multimedia, vol. 1, no. 2, May 2006
Magdi. A. Koutb, M. Nabila, El-Rabaie, Hamdi. A. Awad, Ibrahim. A. Abd El-Hamid, Neural Fuzzy Fault Detection And Isolation In Greenhouses, IEEE Control System Magazine, pp. 28-47,
Emmanuel Mazars, Imad M. Jaimoukha, and Zhenhai Li, Computation of a Reference Model for Robust Fault Detection and Isolation Residual Generation, Journal of Control Science and Engineering, 2008
H. T. Mok, C. W. Chan, Online fault detection and isolation of nonlinear systems based on neuro-fuzzy networks, Engineering Applications of Artificial Intelligence, Vol. 21, Iss. 2, pp 171-181, 2008
Inseok Hwang, Sungwan Kim, Youdan Kim and Chze Eng Seah, A Survey of Fault Detection, Isolation, and Reconfiguration Methods, IEEE Transaction on Control Systems Technology, Vol 18, No. 3, 2010.
A. Ashokan and D. Sivakumar, Intergration of Fault Detection and Isolation Control In A Multi-Input Multi-Output System, Journal Automation & System Engineering,
D. Füssel and R. Isermann, Hierarchical motor diagnosis utilizing structural knowledge and a self-learning neuro-fuzzy-scheme. IEEE Trans. on Ind. Electronics, Vol. 74, No. 5, pp. 1070-1077, 2000
S.M. El-Shal, A.S. Morris, A fuzzy expert system for fault detection in statistical process control of industrial processes, IEEE Transactions on Applications and Reviews, Systems, Man, and Cybernetics, Part C, Vol. 30, Iss. 2, pp. 281 – 289, 2000
Balle, P.; Isermann, Rolf, "Fault detection and isolation for nonlinear processes based on local linear fuzzy models and parameter estimation," American Control Conference, 1998. Proceedings of the 1998, vol.3, no., pp.1605,1609 vol.3, 21-26 Jun 1998, doi: 10.1109/ACC.1998.707277
Jie Chen and R.J. Patton, “Robust Model-Based Fault Diagnosis for Dynamic Systems”, Book, Springer Science Business Media, New York., 1999
B. Freyermuth, R. Isermann (Ed.), “Fault Detection, Supervision and Safety for Technical Processes” IFAC Symposia Series, 1991.
Harbilas Bal and N. P. Mahalik, “Fault detection (FDI) in actuators, 32nd Annual Central California Research Symposium, California State University, April 6, Fresno, California.
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