Parity space-based fault diagnosis of CCBII braking system

Fault diagnosis is a key issue of the CCBII (computer controlled brake II) braking system, because the CCBII braking system is very complicated and nonlinear, which may exhibit isolated and multi-component coupled faults. A parity space-based method was proposed for fault diagnosis of CCBII braking systems. Firstly, the mathematical models were established according to three function modules of CCBII braking systems where the air fluid theory was utilized. Then, parity vector and threshold function were designed for each output of the system so as to identify more system faults. Fault character matrix was built based on the causal relationship between the output and the fault according to the system function and internal structure. Finally, fault detection and isolation can be realized by the comparison of the observed system output and the fault character matrix. Simulation results show that the proposed method is entirely feasible and effective.

[1]  Marcel Staroswiecki,et al.  Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems , 2001, Autom..

[2]  Huajing Fang,et al.  Takagi-sugeno fuzzy-model-based fault detection for networked control systems with Markov delays , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  Hao Ye,et al.  A new parity space approach for fault detection based on stationary wavelet transform , 2004, IEEE Transactions on Automatic Control.

[4]  Jian-Da Wu,et al.  An expert system for fault diagnosis in internal combustion engines using wavelet packet transform and neural network , 2009, Expert Syst. Appl..

[5]  Sarah K. Spurgeon,et al.  Sliding mode observers for fault detection and isolation , 2000, Autom..

[6]  J. Gertler.  Fault detection and isolation using parity relations , 1997 .

[7]  Qing-Long Han,et al.  Parity Space-Based Fault Estimation for Linear Discrete Time-Varying Systems , 2010, IEEE Transactions on Automatic Control.

[8]  Qinghua Zhang,et al.  Nonlinear system fault diagnosis based on adaptive estimation , 2004, Autom..

[9]  Ilhem Slama-Belkhodja,et al.  Parity space approach for current sensor fault detection and isolation in electrical systems , 2011, Eighth International Multi-Conference on Systems, Signals & Devices.

[10]  P. D. McFadden,et al.  APPLICATION OF WAVELETS TO GEARBOX VIBRATION SIGNALS FOR FAULT DETECTION , 1996 .

[11]  Rolf Isermann.  Model-based fault-detection and diagnosis - status and applications § , 2004 .

[12]  H. Henao,et al.  Diagnosis of Broken Bar Fault in Induction Machines Using Discrete Wavelet Transform without Slip Estimation , 2007, 2007 IEEE Industry Applications Annual Meeting.

[13]  S.X. Ding,et al.  Parity space based FDI-scheme for vehicle lateral dynamics , 2005, Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..

[14]  P. Frank,et al.  Survey of robust residual generation and evaluation methods in observer-based fault detection systems , 1997 .

[15]  Raghunathan Rengaswamy,et al.  A syntactic pattern-recognition approach for process monitoring and fault diagnosis , 1995 .

[16]  B. Samanta,et al.  ARTIFICIAL NEURAL NETWORK BASED FAULT DIAGNOSTICS OF ROLLING ELEMENT BEARINGS USING TIME-DOMAIN FEATURES , 2003 .

[17]  Inseok Hwang,et al.  A Survey of Fault Detection, Isolation, and Reconfiguration Methods , 2010, IEEE Transactions on Control Systems Technology.

[18]  Umberto Meneghetti,et al.  Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings , 2001 .

[19]  Zhang Jia-jie.  Fault Diagnosis of Faiveley Braking System Based on Analytical Redundancy Relations , 2013 .