On fault detection in coupled liquid three tank system using subspace aided data driven design

The paper deals with parity based data driven design of the fault detection (FD) systems. The main idea is to extract the process model from test data using subspace system identification (SIM) methods. The identified system model is thenused to develop parity relation for detecting actuator and sensor faults. The application of the technique is shown by simulation study of coupled liquid three tank system.

[1]  M. Abid.  Fuzzy Logic Control of Coupled Liquid Tank System , 2005, 2005 International Conference on Information and Communication Technologies.

[2]  Michel Kinnaert,et al.  Diagnosis and Fault-Tolerant Control , 2006 .

[3]  Steven X. Ding,et al.  Model-based fault diagnosis in technical processes , 2000 .

[4]  Bart De Moor,et al.  N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..

[5]  Wallace E. Larimore,et al.  Canonical variate analysis in identification, filtering, and adaptive control , 1990, 29th IEEE Conference on Decision and Control.

[6]  Paul M. Frank,et al.  Issues of Fault Diagnosis for Dynamic Systems , 2010, Springer London.

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

[8]  B. Moor,et al.  Subspace identification for linear systems , 1996 .

[9]  B. Moor,et al.  Subspace state space system identification for industrial processes , 1998 .

[10]  Si-Zhao Joe Qin,et al.  An overview of subspace identification , 2006, Comput. Chem. Eng..

[11]  Torsten Jeinsch,et al.  A characterization of parity space and its application to robust fault detection , 1999, IEEE Trans. Autom. Control..

[12]  X. Ding,et al.  Model Based Diagnosis of Sensor Faults for ESP-Systems , 2000 .

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

[14]  Patrick Dewilde,et al.  Subspace model identification Part 1. The output-error state-space model identification class of algorithms , 1992 .

[15]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[16]  Raghunathan Rengaswamy,et al.  A review of process fault detection and diagnosis: Part I: Quantitative model-based methods , 2003, Comput. Chem. Eng..

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