A survey of fault diagnosis and fault-tolerant techniques-part I: Fault diagnosis with model-based and signal-based approaches

IEEE Transactions on Industrial Electronics

Volumn 62, Issue 6, 2015, Pages 3757-3767

  Gao, Zhiwei ^a   Cecati, Carlo ^b,c   Ding, Steven X ^d  

^a NORTHUMBRIA UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF L'AQUILA   (Italy)

^c HARBIN INSTITUTE OF TECHNOLOGY   (China)

^d UNIVERSITY OF DUISBURG ESSEN   (Germany)

Author keywords

Analytical redundancy; Fault tolerance; Model based fault diagnosis; Real time monitoring; Signalbased fault diagnosis

Indexed keywords

ACCIDENT PREVENTION; CONTINUOUS TIME SYSTEMS; FAULT TOLERANCE; REAL TIME SYSTEMS; SURVEYS;

ANALYTICAL REDUNDANCY; FAULT TOLERANT CONTROL; FAULT TOLERANT OPERATIONS; FAULT TOLERANT TECHNIQUE; MODEL-BASED FAULT DIAGNOSIS; PERFORMANCE DEGRADATION; REAL TIME MONITORING; REAL-TIME FAULT DIAGNOSIS;

FAULT DETECTION;

EID: 84929376682     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2015.2417501     Document Type: Review

References (167)

1. D. Schrick, "Remarks on terminology in the field of supervision, fault detection and diagnosis", in Proc. IFAC Symp. Fault Detection, Supervision Safety Techn. Process, Hull, U. K., Aug. 1997, pp. 959-964.
2. A. Willsky, "A survey of design methods for failure detection in dynamic systems", Automatica, vol. 12, no. 6, pp. 601-611, Nov. 1976.
3. R. Isermann, "Process fault detection based on modelling and estimation methods: A survey", Automatica, vol. 20, no. 4, pp. 387-304, Jul. 1984.
4. J. Gertler, "Survey of model-based failure detection and isolation in complex plants", IEEE Control Syst. Mag., vol. 8, no. 6, pp. 3-11, Dec. 1988.
5. P. Frank, "Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy-A survey and some new results", Automatica, vol. 26, no. 3, pp. 459-474, May 1990.
6. E. Garcia and P. Frank, "Deterministic nonlinear observer-based approaches to fault diagnosis: A survey", Control Eng. Pract., vol. 5, no. 5, pp. 663-670, May 1997.
7. R. Isermann, "Trends in the application of model-based fault detection and diagnosis of technical processes", Control Eng. Pract., vol. 5, no. 5, pp. 709-719, May 1997.
8. P. Frank and X. Ding, "Survey for robust residual generation and evaluation methods in observer-based fault detection systems", J. Process Control, vol. 7, no. 6, pp. 403-424, Dec. 1997.
9. R. Isermann, "Model-based fault-detection and diagnosis-Status and applications", Annu. Rev. Control, vol. 29, no. 1, pp. 71-85, Jan. 2005.
10. V. Venkatasubramanian, R. Rengaswamy, K. Yin, and S. Kavuri, "A review of process fault detection and diagnosis-Part I: Quantitative model-based methods", Comput. Chem. Eng., vol. 27, no. 3, pp. 293-311, Mar. 2003.
11. V. Venkatasubramanian, R. Rengaswamy, and S. Kavuri, "A review of process fault detection and diagnosis-Part II: Qualitative models and search strategies", Comput. Chem. Eng., vol. 27, no. 3, pp. 313-326, Mar. 2003.
12. V. Venkatasubramanian, R. Rengaswamy, S. Kavuri, and K. Yin "A review of process fault detection and diagnosis-Part III: Process history based methods", Comput. Chem. Eng., vol. 27, no. 3, pp. 313-326, Mar. 2003.
13. V. Chandola, A. Banerjee, and V. Kumar, "Anomaly detection: A survey", ACM Comput. Survey, vol. 41, no. 3, pp. 1-58, Jul. 2009.
14. C. Angeli and A. Chatzinkolaou, "On-line fault detection techniques for technical systems: A survey", Int. J. Comput. Sci. Appl., vol. 1, no. 1, pp. 12-30, 2004.
15. X. Dai and Z. Gao, "From model, signal to knowledge: A data-driven perspective of fault detection and diagnosis", IEEE Trans. Ind. Informat., vol. 9, no. 4, pp. 2226-2238, Nov. 2013.
16. S. Yin, S. Ding, X. Xie, and H. Luo, "A review on basic data-driven approaches for industrial process monitoring", IEEE Trans. Ind. Electron., vol. 61, no. 11, pp. 6418-6428, Nov. 2014.
17. H. Dong, Z. Wang, S. Ding, and H. Gao, "A survey on distributed filtering and fault detection for sensor networks", Math. Probl. Eng., vol. 2014, 2014, Art. ID. 858624.
18. J. Sottile Jr. and L. Holloway, "An overview of fault monitoring and diagnosis in mining equipment", IEEE Trans. Ind. Appl., vol. 30, no. 5, pp. 1326-1332, Oct. 1994.
19. M. Benbouzid, "A review of induction motor signature analysis as a medium for faults detection", IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 984-993, Oct. 2000.
20. S. Nandi, H. Toliyat, and X. Li, "Condition monitoring and fault diagnosis of electric motors-A review", IEEE Trans. Energy Convers., vol. 20, no. 4, vol. 20, no. 4, pp. 719-725, Dec. 2005.
21. S. Mortazavizadeh and M. Mousavi, "A review on condition monitoring and diagnostic techniques of rotating electric machines", Phys. Sci. Int. J., vol. 4, no. 3, pp. 310-338, May 2014.
22. S. Katipamula and M. Brambley, "Methods for fault detection, diagnostics and prognostics for building systems-A review, Part I", HVAC & R Res., vol. 11, no. 1, pp. 3-25, Jan. 2005.
23. S. Katipamula and M. Brambley, "Methods for fault detection, diagnostics and prognostics for building systems-A review, Part II", HVAC & R Res., vol. 11, no. 2, pp. 169-187, Apr. 2005.
24. A. Widodo and B. Yang, "Support vector machine in machine condition monitoring and fault diagnosis", Mech. Syst. Signal Process., vol. 21, no. 6, pp. 2560-2574, Aug. 2007.
25. Z. Feng, M. Liang, and F. Chu, "Recent advances in time-frequency analysis methods for machinery fault diagnosis: A review with application examples", Mech. Syst. Signal Process., vol. 38, no. 1, pp. 165-205, Jul. 2013.
26. L. Qin, X. He, and D. Zhou, "A survey of fault diagnosis for swarm systems", Syst. Sci. Control Eng., vol. 2, no. 1, pp. 13-23, Jan. 2014.
27. R. Stengel, "Intelligent failure-tolerant control", IEEE Control Syst. Mag., vol. 11, no. 4, pp. 14-23, Jun. 1991.
28. M. Blanke, R. Izadi-Zamanabadi, S. Bogh, and C. Lunau, "Fault-tolerant control systems-A holistic view", Control Eng. Pract., vol. 5, no. 5, pp. 693-702, May 1997.
29. R. Patton, "Fault-tolerant control systems: The 1997 situation", in Proc. IFAC Symp. Fault Detect., Supervision Safety Techn. Process, Hull, U. K., Aug. 1997, pp. 1033-1054.
30. J. Jiang, "Fault-tolerant control systems-An introductory overview", Acta Autom. Sinica, vol. 31, no. 1, pp. 161-174, Jan. 2005.
31. J. Lunze and J. Richter, "Reconfigurable fault-tolerant control: A tutorial introduction", Eur. J. Control, vol. 14, no. 5, pp. 359-386, 2008.
32. Y. Zhang and J. Jiang, "Bibliographical review and reconfigurable fault-tolerant control systems", Annu. Rev. Control, vol. 32, no. 2, pp. 229-252, Dec. 2008.
33. M. Benosman, "A survey of some recent results on nonlinear fault tolerant control", Math. Probl. Eng., vol. 2010, 2010, Art. ID. 586 169.
34. H. Wang, T. Chai, J. Ding, and B. Martin, "Data driven fault diagnosis and fault tolerant control: Some advances and possible new directions", Acta Autom. Sinica, vol. 35, no. 6, pp. 739-747, Jun. 2009.
35. I. Hwang, S. Kim, Y. Kim, and C. Seah, "A survey of fault detection, isolation, and reconfiguration methods", IEEE Trans. Control Syst. Technol., vol. 18, no. 3, pp. 636-653, May 2010.
36. D. Campos-Delgado, D. Espinoza-Trejo, and E. Palacios, "Fault-tolerant control in variable speed drives: A survey", IET Elect. Power Appl., vol. 2, no. 2, pp. 121-134, Apr. 2008.
37. Y. Song and B. Wang, "Survey of reliability of power electronic systems", IEEE Trans. Power Electron., vol. 28, no. 1, pp. 591-604, Jan. 2013.
38. B. Mirafzal, "Survey of fault-tolerance techniques for three-phase voltage source inverters", IEEE Trans. Ind. Electron., vol. 61, no. 10, pp. 5192-5202, Oct. 2014.
39. R. Beard, "Failure accommodation in linear system through self reorganization", Ph. D. dissertation, MIT, Cambridge, MA, USA, 1971.
40. J. Chen and R. Patton, Robust Model-Based Fault Diagnosis for Dynamic Systems. Boston, MA, USA: Kluwer, 1999.
41. S. Ding, Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools. Berlin, Germany: Springer-Verlag, 2008.
42. R. Patton, S. Willcox, and S. Winter, "A parameter insensitive techniques for aircraft sensor fault analysis", J. Guid. Control Dyn., vol. 10, no. 3, pp. 359-367, Jul. 1987.
43. R. Patton and J. Chen, "On eigenstructure assignment for robust fault diagnosis", Int. J. Adaptive Control Sig. Process., vol. 10, no. 14, pp. 1193-1208, Dec. 2000.
44. L. Xu and H. Tseng, "Robust model-based fault detection for a roll stability control system", IEEE Trans. Control Syst. Technol., vol. 15, no. 3, pp. 519-528, May 2007.
45. X. Dai, Z. Gao, T. Breikin, and H. Wang, "Disturbance attenuation in fault detection of gas turbine engines: A discrete robust observer design", IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 39, no. 2, pp. 234-239, Mar. 2009.
46. R. Fonod, D. Henry, C. Charbonnel, and E. Bornschlegl, "Robust thruster fault diagnosis: Application to the rendezvous phase of the Mars sample return mission", in Proc. 2nd CEAS Spec. Conf. Guid., Navig. Control, Delft, The Netherlands, Apr. 2013, pp. 1496-1510.
47. Y. Zhu and Z. Gao, "Robust observer-based fault detection via evolutionary optimization with applications to wind turbine systems", in Proc. IEEE 9th Conf. Ind. Electron. Appl., Hangzhou, China, Jun. 2014, pp. 1627-1632.
48. A. Pertew, H. Marquez, and Q. Zhao, "LMI-based sensor fault diagnosis for nonlinear Lipschitz systems" Automatica, vol. 43, no. 8, pp. 1464-1469, Aug. 2007.
49. D. Zhang, H. Wang, B. Lu, and Z. Wang, "LMI-based fault detection fuzzy observer design with multiple performance constraints for a class of nonlinear systems: Comparative study", Int. J. Innov. Comput. Inf. Control, vol. 8, no. 1, pp. 633-645, Jan. 2012.
50. ∞fault detection observer design for Takagi-Sugeno fuzzy systems with unmeasurable premise variables: Descriptor approach", Int. J. Adapt. Signal Process., vol. 27, no. 12, pp. 1031-1042, Dec. 2013.
51. H. Karimi, M. Zapateiro, and N. Luo, "A linear matrix inequality approach to robust fault detection filter design of linear systems with mixed time-varying delays and nonlinear perturbations", J. Franklin Inst., vol. 347, no. 6, pp. 957-973, Aug. 2010.
52. D. Wang, P. Shi, and W. Wang, "Robust fault detection for continuoustime switched delay systems: An linear matrix inequality approach", IET Control Theory Appl., vol. 4, no. 1, pp. 100-108, Jan. 2010.
53. ∞structural damage detection filter design using an iterative linear matrix inequality approach", Smart Mater. Struct., vol. 17, no. 3, pp. 1-9, Apr. 2008.
54. Z. Kulesza, J. Sawicki, and A. Gyekenyesi, "Robust fault detection filter using linear matrix inequalities' approach for shaft crack diagnosis", J. Vib. Control, vol. 19, no. 9, pp. 1421-1440, Jul. 2013.
55. X. Zhang, M. Polycarpou, and T. Parisini, "Fault diagnosis of a class of nonlinear systems with Lipschitz nonlinearities using adaptive estimation", Automatica, vol. 46, no. 2, pp. 290-299, Feb. 2010.
56. M. Du and P. Mhaskar, "Isolation and handling of sensor faults in nonlinear systems", Automatica, vol. 50, no. 4, pp. 1066-1074, Apr. 2014.
57. X. Zhang, L. Tang, and J. Decastro, "Robust fault diagnosis of aircraft engines: A nonlinear adaptive estimation-based approach", IEEE Trans. Control Syst. Technol., vol. 21, no. 3, pp. 861-868, May 2013.
58. F. Caccavale, A. Marino, G. Muscio, and F. Pierri, "Discrete-time framework for fault diagnosis in robotic manipulators", IEEE Trans. Control Syst. Technol., vol. 21, no. 5, pp. 1858-1873, Sep. 2013.
59. W. Chen, W. T. Chen, M. Saif, M. Li, and H. Wu, "Simultaneous fault isolation and estimation of lithium-ion batteries via synthesized design of Luenberger and learning observers", IEEE Trans. Control Syst. Technol., vol. 22, no. 1, pp. 290-298, Jan. 2014.
60. J. Chen and H. Zhang, "Robust fault detection of faulty actuators via unknown input observers", Int. J. Syst. Sci., vol. 22, no. 10, pp. 1829-1839, Oct. 1991.
61. W. Chen and M. Saif, "Fuzzy nonlinear unknown input observer design with fault diagnosis applications", J. Vib. Control, vol. 16, no. 3, pp. 377-401, Mar. 2010.
62. J. Zarei and E. Shokri, "Robust sensor fault detection based on nonlinear unknown input observer", Measurement, vol. 48, no. 2, pp. 355-367, Feb. 2014.
63. D. Wang and K. Lum, "Adaptive unknown input observer approach for aircraft actuator fault detection and isolation", Int. J. Adapt. Control Signal Process., vol. 21, no. 1, pp. 31-48, Mar. 2007.
64. K. Gaeid and H. Ping, "Induction motor fault detection and isolation through unknown input observer", Sci. Res. Essays, vol. 5, no. 20, pp. 3152-3159, Oct. 2010.
65. S. Methnani 1, F. Lafont, J. Gauthier, T. Damak, and A. Toumi, "Actuator and sensor fault detection, isolation and identification in nonlinear dynamical systems, with an application to a waste water treatment plant", J. Comput. Eng. Informat., vol. 1, no. 4, pp. 112-125, Oct. 2013.
66. Z. Gao, "Discrete-time proportional and integral observer and observerbased controller for systems with both unknown input and output disturbances", Opt. Control Appl. Methods, vol. 29, no. 3, pp. 171-189, May 2008.
67. K. Zhang, B. Jiang, V. Cocquempot, and H. Zhang, "A framework of robust fault estimation observer design for continuous-time/discrete-time systems", Opt. Control Appl. Methods, vol. 34, no. 4, pp. 442-457, Aug. 2013.
68. Z. Gao and D. Ho, "Proportional multiple-integral observer design for descriptor systems with measurement output disturbances", Proc. Inst. Elect. Eng.-Control Theory Appl., vol. 151, no. 3, pp. 279-288, May 2004.
69. D. Koenig, "Unknown input proportional multiple-integral observer design for linear descriptor systems: Application to state and fault estimation", IEEE Trans. Autom. Control, vol. 50, no. 2, pp. 212-217, Feb. 2005.
70. Z. Gao, S. Ding, and Y. Ma, "Robust fault estimation approach and its application in vehicle lateral dynamic systems", Opt. Control Appl. Methods, vol. 28, no. 3, pp. 143-156, May 2007.
71. Q. Zhang and G. Besancon, "An adaptive observer for sensor fault estimation in a class of uniformly observable nonlinear systems", Int. J. Model. Identification Control, vol. 4, no. 1, pp. 37-43, Jan. 2008.
72. K. Zhang, B. Jiang, and V. Cocquempot, "Adaptive observer-based fast fault estimation", Int. J. Control Autom. Syst., vol. 6, no. 3, pp. 320-326, Jun. 2008.
73. M. Gholizadeh and F. Salmasi, "Estimation of state of charge, unknown nonlinearities, and state of health of a lithium-ion battery based on a comprehensive unobservable model", IEEE Trans. Ind. Electron., vol. 61, no. 3, pp. 1335-1344, Mar. 2014.
74. H. Alwi and C. Edwards, "Robust fault reconstruction for linear parameter varying systems using sliding mode observers", Int. J. Robust Nonlin. Control, vol. 24, no. 14, pp. 1947-1968, Sep. 2014.
75. X. Han, F. Emilia, and S. Sarah, "Sampled-data sliding mode observer for robust fault reconstruction: A time-delay approach", J. Franklin Inst., vol. 351, no. 4, pp. 2125-2142, Jun. 2014.
76. Z. Gao and H. Wang, "Descriptor observer approaches for multivariable systems with measurement noises and application in fault detection and diagnosis", Syst. Control Lett., vol. 55, no. 4, pp. 304-313, Apr. 2006.
77. Z. Gao, X. Shi, and S. Ding, "Fuzzy state/disturbance observer design for T-S fuzzy systems with application to sensor fault estimation", IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 38, no. 3, pp. 875-880, Jun. 2008.
78. J. Zhang, A. Swain, and S. Nguang, "Robust sensor fault estimation scheme for satellite attitude control systems", J. Franklin Inst., vol. 350, no. 9, pp. 2581-2604, Nov. 2013.
79. Z. Gao, X. Dai, T. Breikin, and H. Wang, "Novel parameter identification by using a high-gain observer with application to a gas turbine engine", IEEE Trans. Ind. Informat., vol. 4, no. 4, pp. 271-279, Nov. 2008.
80. L. Mironovski, "Functional diagnosis of linear dynamic systems", Autom. Remote Control, vol. 40, no. 8, pp. 1198-1205, Aug. 1980.
81. E. Chow and A. Willsky, "Analytical redundancy and the design of robust detection systems", IEEE Trans. Autom. Control, vol. 29, no. 7, pp. 603-614, Jul. 1984.
82. J. Gertler, Fault Detection and Diagnosis in Engineering Systems. New York, NY, USA: Marcel Dekker, 1998.
83. S. Nguang, P. Zhang, and S. Ding, "Parity relation based fault estimation for nonlinear systems: An LMI approach", Int. J. Autom. Comput., vol. 4, no. 2, pp. 164-168, Apr. 2007.
84. Z. Zhang, J. Hu, and H. Hu, "Parity space approach to fault detection based on fuzzy tree model", Int. J. Adv. Comput. Technol., vol. 5, no. 2, pp. 657-665, Jan. 2013.
85. H. Odendaal and T. Jones, "Actuator fault detection and isolation: An optimized parity space approach", Control Eng. Pract., vol. 26, no. 5, pp. 222-232, May 2014.
86. W. Huang and K. Huh, "Fault detection and estimation for electromechanical brake systems using parity space approach", J. Dyn. Syst., Meas., Control, vol. 137, no. 1, Aug. 2014, Art. ID. 014504.
87. N. Viswanadham, J. Taylor, and E. Luce, "A frequency-domain approach to failure detection and isolation with application to GE-21 turbine engine control systems", Control, Theory Adv. Technol., vol. 3, no. 1, pp. 45-72, Mar. 1987.
88. X. Ding and P. Frank, "Fault detection via factorization approach", Syst. Control Lett., vol. 14, no. 5, pp. 431-436, Jun. 1990.
89. M. Abid, A. Khan, W. Chen, and S. Ding, "Optimal residual evaluation for nonlinear systems using post filter and threshold", Int. J. Control, vol. 84, no. 3, pp. 526-539, Mar. 2011.
90. J. Hu and M. Tsai, "Design of robust stabilization and fault diagnosis for an auto-balancing two-wheeled cart", Adv. Robot., vol. 22, no. 2, pp. 319-338, Mar. 2008.
91. M. Deng, I. Akira, and E. Kazunori, "Fault detection system design for actuator of a thermal process using operator based approach", Acta Autom. Sinica, vol. 36, no. 4, pp. 580-585, Apr. 2010.
92. R. Mehra and J. Peschon, "An innovation approach to fault detection and diagnosis in dynamic systems", Automatica, vol. 7, no. 5, pp. 637-640, Sep. 1971.
93. A. Willsky and H. Jones, "A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems", IEEE Trans. Autom. Control, vol. 21, no. 1, pp. 108-121, Feb. 1976.
94. R. Da and C. Lin, "Sensitivity analysis algorithm for the state chi-square test", J. Guid. Control Dyn., vol. 19, no. 1, pp. 219-222, Jan. 1996.
95. I. Nikiforov, V. Varavva, and V. Kireichikov, "Application of statistical fault-detection algorithms to navigation system monitoring", Automatica, vol. 29, no. 5, pp. 1275-1290, Sep. 1993.
96. S. Bogh, "Multiple hypothesis-testing approach to FDI for the industrial actuator benchmark", Control Eng. Pract., vol. 3, no. 12, pp. 1763-1768, Dec. 1995.
97. R. Li and J. Olson, "Fault detection and diagnosis in a closed-loop nonlinear distillation process: Application of extended Kalman filters", Ind. Eng. Chem. Res., vol. 30, no. 5, pp. 898-908, May 1991.
98. H. Liu, D. Liu, C. Lu, and X. Wang, "Fault diagnosis of hydraulic servo system using the unscented Kalman filter", Asian J. Control, vol. 16, no. 6, pp. 1713-1725, Nov. 2014.
99. M. Laila, N. Naveen, and K. Vishakh, "Comparison of estimation capabilities of extended and unscented Kalman filter in an RLV", Int. J. Adv. Res. Elect. Electron. Instrum. Eng., vol. 2, no. 7, pp. 3480-3488, Jul. 2013.
100. C. Hajiyev and H. Soken, "Robust adaptive Kalman filter for estimation of UAV dynamics in the presence of sensor/actuator faults", Aerosp. Sci. Technol., vol. 28, no. 1, pp. 376-383, Jul. 2013.
101. A. Izadian, "Self-tuning fault diagnosis of MEMS", Mechatronics, vol. 23, no. 8, pp. 1094-1099, Dec. 2013.
102. F. Hmida, K. Khemiri, J. Ragot, and M. Goss, "Three-stage Kalman filter for state and fault estimation of linear stochastic systems with unknown inputs", J. Franklin Inst., vol. 349, no. 7, pp. 2369-2388, Sep. 2012.
103. S. Helm, M. Kozek, and S. Jakubek, "Combustion torque estimation and misfire detection for calibration of combustion engines by parametric Kalman filtering", IEEE Trans. Ind. Electron., vol. 59, no. 12, pp. 4326-4337, Nov. 2012.
104. P. Lall, R. Lowe, and K. Goebel, "Prognostics health management of electronic systems under mechanical shock and vibration using Kalman filter models and metrics", IEEE Trans. Ind. Electron., vol. 59, no. 11, pp. 4301-4314, Nov. 2012.
105. G. Foo, X. Zhang, and D. Vilathgamuwa, "A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter", IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3485-3495, Aug. 2013.
106. C. Bakiotis, J. Raymond, and A. Pault, "Parameter and discriminant analysis for jet engine mechanical state diagnosis", in Proc. Conf. Decision Control, Fort Lauderdale, FL, USA, Dec. 1979, pp. 648-650.
107. S. Simani, C. Fantuzzi, and R. Patton, Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques. Berlin, Germany: Springer-Verlag, 2002.
108. R. Doraiswami, C. Diduch, and J. Tang, "A new diagnostic for identifying parametric faults", IEEE Trans. Control Syst. Technol., vol. 18, no. 3, pp. 533-544, May 2010.
109. M. Dohler and L. Mevel, "Subspace-based fault detection robust to changes in the noise covariances", Automatica, vol. 49, no. 9, pp. 2734-2743, Sep. 2013.
110. A. Akhenak, E. Duviella, L. Bakoa, and S. Lecoeuchea, "Online fault diagnosis using recursive subspace identification: Application to a damgallery open channel system", Control Eng. Pract., vol. 21, no. 6, pp. 797-806, Jun. 2013.
111. H. Wang and W. Lin, "Applying observer based FDI techniques to detect faults in dynamic and bounded stochastic distributions", Int. J. Control, vol. 73, no. 15, pp. 1424-1436, Aug. 2000.
112. Z. Gao, H. Wang, and T. Chai, "A robust fault detection filtering for stochastic distribution systems via descriptor estimator and parametric gain design", IET Control Theory Appl., vol. 1, no. 5, pp. 1286-1293, Jan. 2007.
113. S. Cao, Y. Yi, and L. Guo, "Anti-disturbance fault diagnosis for non-Gaussian stochastic distribution systems with multiple disturbances", Neurocomputing, vol. 136, no. 20, pp. 315-320, Jul. 2014.
114. L. Wu and D. Ho, "Fuzzy filter design for Itô stochastic systems with application to sensor fault detection", IEEE Trans. Fuzzy Syst., vol. 17, no. 1, pp. 233-242, Feb. 2009.
115. M. Liu, X. Cao, and P. Shi, "Fault estimation and tolerant control for fuzzy stochastic systems", IEEE Trans. Fuzzy Syst., vol. 21, no. 2, pp. 221-229, Apr. 2012.
116. H. Dong, Z. Wang, and H. Gao, "Fault detection for Markovian jump systems with sensor saturations and randomly varying nonlinearities", IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 59, no. 10, pp. 2354-2362, Oct. 2012.
117. M. Sampath, R. Sengupta, S. Lafortune, K. Sinnamohideen, and D. Teneketzis, "Diagnosability of discrete-event systems", IEEE Trans. Autom. Control, vol. 40, no. 9, pp. 1555-1575, Sep. 1995.
118. L. Carvalho, M. Moreira, J. Basilio, and S. Lafortune, "Robust diagnosis of discrete-event systems against permanent loss of observations", Automatica, vol. 49, no. 1, pp. 223-231, Jan. 2013.
119. Y. Pencole and M. Cordier, "A formal framework for the decentralized diagnosis of large scale discrete event systems and its application to telecommunication network", Artif. Intell., vol. 164, no. 2, pp. 121-170, May 2005.
120. A. Shumann, Y. Pencole, and S. Thiebaux, "A spectrum of symbolic online diagnosis approaches", in Proc. 19th Nat. Conf. Artif. Intell., 2007, pp. 335-340.
121. A. Grastien and A. Anbulagan, "Diagnosis of discrete event systems using satisfiability algorithms: A theoretical and empirical study", IEEE Trans. Autom. Control, vol. 58, no. 12, pp. 3070-3083, Dec. 2013.
122. M. Cabasino, A. Giua, and C. Seatzu, "Fault detection for discrete event systems using Petri nets with unobservable transitions", Automatica, vol. 46, no. 9, pp. 1531-1539, Sep. 2010.
123. M. Dotoli, M. Fanti, A. Mangini, and W. Ukovich, "On-line fault detection in discrete event systems by Petri nets and integer linear programming", Automatica, vol. 45, no. 11, pp. 2665-2672, Nov. 2009.
124. D. Lefebvre, "On-line fault diagnosis with partially observed Petri nets", IEEE Trans. Autom. Control, vol. 59, no. 7, pp. 1919-1924, Jul. 2014.
125. N. Meskin, K. Khorasani, and C. Rabbath, "A hybrid fault detection and isolation strategy for a network of unmanned vehicles in presence of large environmental disturbances", IEEE Trans. Control Syst. Technol., vol. 18, no. 6, pp. 1422-1429, Nov. 2010.
126. M. Daigle, X. Koutsoukos, and G. Biswas, "A qualitative event-based approach to continuous systems diagnosis", IEEE Trans. Control Syst. Technol., vol. 17, no. 4, pp. 780-793, Jul. 2009.
127. F. Zhao, K. Koutsoukos, H. Haussecker, J. Reich, and P. Cheung, "Monitoring and fault diagnosis of hybrid systems", IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 35, no. 6, pp. 1225-1240, Dec. 2005.
128. J. Guo, D. Ji, S. Du, S. Zeng, and B. Sun, "Fault diagnosis of hybrid systems using particle filter based hybrid estimation algorithm", Chem. Eng. Trans., vol. 33, no. 1, pp. 145-150, Sep. 2013.
129. S. Arogeti, D. Wang, C. Low, and M. Yu, "Fault detection isolation and estimation in a vehicle steering system", IEEE Trans. Ind. Electron., vol. 59, no. 12, pp. 4810-4820, Dec. 2012.
130. M. Yu and D. Wang, "Model-based health monitoring for a vehicle steering system with multiple faults of unknown types", IEEE Trans. Ind. Electron., vol. 61, no. 7, pp. 3574-3586, Jul. 2014.
131. P. Levy, S. Arogeti, and D. Wang, "An integrated approach to model tracking and diagnosis of hybrid systems", IEEE Trans. Ind. Electron, vol. 61, no. 4, pp. 1024-1040, Apr. 2014.
132. M. Yu, D. Wang, and M. Luo, "Model-based prognosis for hybrid systems with mode-dependent degradation behaviors", IEEE Trans. Ind. Electron, vol. 61, no. 1, pp. 546-554, Jan. 2014.
133. G. Walsh, H. Ye, and L. Bushnell, "Stability analysis of networked control systems", IEEE Trans. Control Syst. Technol., vol. 10, no. 3, pp. 438-446, May 2002.
134. D. Zhou, X. He, Z. Wang, G. Liu, and Y. Ji, "Leakage fault diagnosis for an Internet-based three-tank system: An experimental study", IEEE Trans. Control Syst. Technol., vol. 20, no. 4, pp. 857-870, Jul. 2012.
135. X. He, Z. Wang, and D. Zhou, "Robust fault detection for networked systems with communication delay and data missing", Automatica, vol. 45, no. 11, pp. 2634-2639, Nov. 2009.
136. X. He, Z. Wang, Y. Liu, and D. Zhou, "Least-square fault detection and diagnosis for networked sensing systems using a direct state estimation approach", IEEE Trans. Ind. Informat., vol. 9, no. 3, pp. 1670-1679, Aug. 2013.
137. S. Alavi and M. Saif, "Fault detection in nonlinear stable systems over lossy networks", IEEE Trans. Control Syst. Technol., vol. 21, no. 6, pp. 2129-2142, Nov. 2013.
138. S. Rahme, Y. Labit, F. Gouaisbaut, and T. Floquet, "Second order sliding mode observer for anomaly detection in TCP networks: From theory to practice", in Proc. Conf. Decision Control, Atlanta, GA, USA, Dec. 2010, pp. 5120-5125.
139. S. Rahme, Y. Labit, F. Gouaisbaut, and T. Floquet, "Sliding modes for anomaly observation in TCP networks: From theory to practice", IEEE Trans. Control Syst. Technol., vol. 21, no. 3, pp. 1031-1038, May 2013.
140. Y. Lei, Y. Yuan, and J. Zhao, "Model-based detection and monitoring of the intermittent connections for CAN networks", IEEE Trans. Ind. Electron., vol. 61, no. 6, pp. 2912-2921, Jun. 2014.
141. S. Kelkar and R. Kamal, "Adaptive fault diagnosis algorithm for controller area network", IEEE Trans. Ind. Electron, vol. 61, no. 10, pp. 5527-5537, Oct. 2014.
142. S. Stankovic, M. Stankovic, and D. Stipanovic, "Consensus based overlapping decentralized estimation with missing observation and communication faults", Automatica, vol. 45, no. 6, pp. 1397-1406, Jun. 2009.
143. C. Keliris, M. Polycarpou, and T. Parisini, "A distributed fault detection filtering approach for a class of interconnected continuoustime nonlinear systems", IEEE Trans. Autom. Control, vol. 58, no. 8, pp. 2032-2047, Aug. 2013.
144. P. Menon and C. Edwards, "Robust fault estimation using relative information in linear multi-agent networks", IEEE Trans. Autom. Control, vol. 59, no. 2, pp. 477-482, Feb. 2014.
145. N. Lechvin and C. Rabbath, "Decentralized detection of a class of nonabrupt faults with application to formations of unmanned airships", IEEE Trans. Control Syst. Technol., vol. 17, no. 2, pp. 484-493, Mar. 2009.
146. A. El-Zonkoly, "Fault diagnosis in distribution networks with distributed generation", Elect. Power Syst. Res., vol. 81, no. 7, pp. 1482-1490, Jul. 2011.
147. H. Chen and S. Lu, "Fault diagnosis digital method for power transistors in power converters of switched reluctance motors", IEEE Trans. Ind. Electron., vol. 60, no. 2, pp. 749-763, Feb. 2013.
148. N. Freire, J. Estima, and A. Cardoso, "Open-circuit fault diagnosis in PMSG drives for wind turbine applications", IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 3957-3967, Sep. 2013.
149. M. Shahbazi, E. Jamshidpour, P. Poure, S. Saadate, and M. Zolghadri, "Open and short-circuit switch fault diagnosis for nonisolated dc-dc converters using field programmable gate array", IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 4136-4145, Sep. 2013.
150. J. Estima and A. Cardoso, "A new algorithm for real-time multiple open-circuit fault diagnosis in voltage-fed PWM motor drives by the reference current errors", IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3496-3505, Aug. 2013.
151. M. Bouzid and G. Champenois, "New expression of symmetrical components of the inductor motor under stator faults", IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 4093-4102, Sep. 2013.
152. P. Samara, G. Fouskitakis, J. Sakellariou, and S. Fassois, "A statistical method for the detection of sensor abrupt faults in aircraft control systems", IEEE Trans. Control Syst. Technol., vol. 16, no. 4, pp. 789-798, Jul. 2008.
153. L. Hong and J. Dhupia, "A time domain approach to diagnose gearbox fault based on measured vibration signals", J. Sound Vib., vol. 333, no. 7, pp. 2164-2180, Mar. 2014.
154. V. Do and U. Chong, "Signal model-based fault detection and diagnosis for induction motors using features of vibration signal in two-dimension domain", J. Mech. Eng., vol. 57, no. 9, pp. 655-666, Sep. 2011.
155. M. Shahriar, T. Ahsan, and U. Chong, "Fault diagnosis of induction motors utilizing local binary pattern-based texture analysis", EURASIP J. Image Video Process., vol. 2013, no. 1, pp. 1-11, May 2013.
156. G. Joksimovic, J. Riger, T. Wolbank, N. Peric, and M. Vasak, "Stator-current spectrum signature of healthy cage rotor induction machines", IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 4025-4033, Sep. 2013.
157. X. Gong and W. Qiao, "Bearing fault diagnosis for direct-drive wind turbines via current-demodulated signals", IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3419-3428, Aug. 2013.
158. N. Pan, X. Wu, Y. Chi, X. Liu, and C. Liu, "Combined failure acoustical diagnosis based on improved frequency domain blind deconvolution", J. Phys., Conf. Ser., vol. 364, no. 1, pp. 1-7, Jan. 2012.
159. Z. Feng and M. Zuo, "Fault diagnosis of planetary gearboxes via torsional vibration signal analysis", Mech. Syst. Process., vol. 36, no. 2, pp. 401-421, Apr. 2013.
160. S. Nandi, T. Ilamparithi, S. Lee, and D. Hyun, "Detection of eccentricity faults in induction machines based on nameplate parameters", IEEE Trans. Ind. Electron., vol. 58, no. 5, pp. 1673-1683, May 2011.
161. Y. Gritli et al., "Advanced diagnosis of electrical faults in woundrotor induction machines", IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 4012-4024, Sep. 2013.
162. E. Cabal-Yepez, A. Garcia-Ramirez, R. Romero-Troncoso, A. Garcia-Perez, and R. Osornio-Rios, "Reconfigurable monitoring system for time-frequency analysis on industrial equipment through STFT and DWT", IEEE Trans. Ind. Informat., vol. 9, no. 2, pp. 760-771, May 2013.
163. R. Yan and R. Gao, "Hilbert-Huang transform-based vibration signal analysis for machine health monitoring", IEEE Trans. Instrum. Meas., vol. 55, no. 6, pp. 2320-2329, Dec. 2006.
164. R. Burnett, J. Watson, and S. Elder, "The application of modern signal processing techniques for use in rotor fault detection and location within three-phase induction motors", Signal Process., vol. 49, no. 1, pp. 57-70, Feb. 1996.
165. B. Tang, W. Liu, and T. Song, "Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution", Renew. Energy, vol. 35, no. 12, pp. 2862-2866, Dec. 2010.
166. V. Climente-Alarcon, J. Antonino-Daviu, M. Riera-Guasp, and M. Vlcek, "Induction motor diagnosis by advanced notch FIR filters and the Wigner-Ville distribution", IEEE Trans. Ind. Electron., vol. 61, no. 8, pp. 4217-4227, Aug. 2014.
167. L. Xiang and X. Yan, "A self-adaptive time-frequency analysis method based on local mean decomposition and its application in defect diagnosis", J. Vib. Control, to be published. DOI: 10.1177/1077546314538992.