Fault prediction for nonlinear stochastic system with incipient faults based on particle filter and nonlinear regression.

This paper is concerned with the fault prediction for the nonlinear stochastic system with incipient faults. Based on the particle filter and the reasonable assumption about the incipient faults, the modified fault estimation algorithm is proposed, and the system state is estimated simultaneously. According to the modified fault estimation, an intuitive fault detection strategy is introduced. Once each of the incipient fault is detected, the parameters of which are identified by a nonlinear regression method. Then, based on the estimated parameters, the future fault signal can be predicted. Finally, the effectiveness of the proposed method is verified by the simulations of the Three-tank system.

[1]  Donghua Zhou,et al.  A New Real-Time Reliability Prediction Method for Dynamic Systems Based on On-Line Fault Prediction , 2009, IEEE Transactions on Reliability.

[2]  Peng Shi,et al.  Multi-constrained fault estimation observer design with finite frequency specifications for continuous-time systems , 2014, Int. J. Control.

[3]  Bo Ding,et al.  Multi-faults detection and estimation for nonlinear stochastic system based on particle filter and hypothesis test , 2016, Int. J. Syst. Sci..

[4]  Steven X. Ding,et al.  A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches , 2015, IEEE Transactions on Industrial Electronics.

[5]  Steven X. Ding,et al.  Model-based Fault Diagnosis Techniques: Design Schemes, Algorithms, and Tools , 2008 .

[6]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..

[7]  Dionisio Bernal,et al.  A Modified Whiteness Test for Damage Detection Using Kalman Filter Innovations , 2011 .

[8]  Huajing Fang,et al.  Fault Detection for Nonlinear Systems with Unknown Input , 2013 .

[9]  Marios M. Polycarpou,et al.  Incipient fault diagnosis of dynamical systems using online approximators , 1998 .

[10]  D. Simon Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[11]  Douglas M. Bates,et al.  Nonlinear Regression Analysis and Its Applications , 1988 .

[12]  Marios M. Polycarpou,et al.  A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems , 2002, IEEE Trans. Autom. Control..

[13]  J. Y. KELLER,et al.  Generalized likelihood ratio approach for fault detection in linear dynamic stochastic systems with unknown inputs , 1996, Int. J. Syst. Sci..

[14]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[15]  Donghua Zhou,et al.  Robust state estimation and fault diagnosis for uncertain hybrid nonlinear systems , 2007 .

[16]  Bin Jiang,et al.  Fault estimation observer design for discrete‐time systems in finite‐frequency domain , 2015 .

[17]  Donghua Zhou,et al.  Real-time Reliability Prediction for a Dynamic System Based on the Hidden Degradation Process Identification , 2008, IEEE Transactions on Reliability.

[18]  Ke Zhang,et al.  Incipient Fault Detection Using an Associated Adaptive and Sliding-Mode Observer for Quadrotor Helicopter Attitude Control Systems , 2016, Circuits Syst. Signal Process..

[19]  Enrico Zio,et al.  Interacting multiple-models, state augmented Particle Filtering for fault diagnostics , 2015 .

[20]  Ke Zhang,et al.  Observer-Based Fault Estimation and Accomodation for Dynamic Systems , 2012 .

[21]  Halim Alwi,et al.  Sliding mode estimation schemes for incipient sensor faults , 2009, Autom..

[22]  Visakan Kadirkamanathan,et al.  Fault detection and isolation in non-linear stochastic systems—A combined adaptive Monte Carlo filtering and likelihood ratio approach , 2004 .

[23]  Sarangapani Jagannathan,et al.  A Model-Based Fault Detection and Prognostics Scheme for Takagi–Sugeno Fuzzy Systems , 2014, IEEE Transactions on Fuzzy Systems.

[24]  Akshya Swain,et al.  Detection and isolation of incipient sensor faults for a class of uncertain non-linear systems , 2012 .