On-Line Fault Detection Techniques for Technical Systems: A Survey

On-line fault detection and isolation techniques have been developed for automated processes during the last few years. These methods include numerical methods, artificial intelligence methods or combinations of the two methodologies. This paper includes a reference to recent research work on numerical methods, an extensive presentation of artificial intelligence methods used for the fault detection process in technical systems and relevant survey material. Special reference is made to the on-line expert systems development where specific resent research work is illustrated.

[1]  M. J. Fuente,et al.  A Comparative Study of Neural Networks Based Approach for Fault Detection , 1997 .

[2]  Kenneth D. Forbus Qualitative Process Theory , 1984, Artif. Intell..

[3]  Bruce D'Ambrosio,et al.  Real-Time Process Management for Materials Composition in Chemical Manufacturing , 1987, IEEE Expert.

[4]  P. Frank Robust Model-Based Fault Detection in Dynamic Systems , 1992 .

[5]  Sylviane Gentil,et al.  FCC Diagnosis Using Several Causal and Knowledge Based Models , 2003 .

[6]  D. Bobrow Qualitative Reasoning about Physical Systems , 1985 .

[7]  Brian Surgenor,et al.  Thermal Fault Analysis and the Diagnostic Model Processor , 1992 .

[8]  Ron J. Patton,et al.  Robustness in Model-Based Fault Diagnosis: The 1995 Situation , 1995 .

[9]  Heikki N. Koivo,et al.  Artificial neural networks in fault diagnosis and control , 1994 .

[10]  Luis J. de Miguel,et al.  A SOM and Expert System Based Scheme for Fault Detection and Isolation in a Hydroelectric Power Station , 2003 .

[11]  N.V.L. Addanki,et al.  On Line Diagnosis of Water Chemistry in Thermal Power Plant , 1992 .

[12]  Barr and Feigenbaum Edward A. Avron The Handbook of Artificial Intelligence , 1981 .

[13]  P. A. Sachs,et al.  Escort — an expert system for complex operations in real time , 1986 .

[14]  Mattias Krysander,et al.  Combining AI, FDI, and Statistical Hypothesis-Testing in a Framework for Diagnosis , 2003 .

[15]  Benjamin J. Kaipers,et al.  Qualitative Simulation , 1989, Artif. Intell..

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

[17]  L. F. Pau,et al.  Survey of expert systems for fault detection, test generation and maintenance , 1986 .

[18]  Mark A. Kramer,et al.  Diagnosis using backpropagation neural networks—analysis and criticism , 1990 .

[19]  Pau-Lo Hsu,et al.  An intelligent supervision system for the ion implementation in IC fabrication processes , 1997 .

[20]  P. S. Dhurjati,et al.  On-line fault detection and supervision in the chemical process industries : selected papers from the IFAC Symposium, Newark, Delaware, USA, 22-24 April 1992 , 1993 .

[21]  Alex Bykat,et al.  Intelligent monitoring and diagnosis systems: A survey , 1991, Appl. Artif. Intell..

[22]  Toshiomi Yoshida,et al.  A Method for On-Line Reasoning about the Time-Profiles of Process Variables , 1992 .

[23]  Ali Cinar,et al.  Intelligent process monitoring by interfacing knowledge-based systems and multivariate statistical monitoring , 2000 .

[24]  Rolf Isermann,et al.  Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..

[25]  Hirokazu Nishitani,et al.  Failure Detection by Auto-Associative Neural Networks , 1995 .

[26]  George Stephanopoulos,et al.  On-line fault detection and supervision in the chemical process industries 2001 (CHEMFAS-4) : a proceedings volume from the 4th IFAC Workshop, Jejudo Island, Korea, 7-8 June 2001 , 2001 .

[27]  Spyros G. Tzafestas,et al.  Knowledge Engineering Approach to System Modelling, Diagnosis, Supervision and Control , 1987 .

[28]  Cheng-Ching Yu,et al.  Identification of Nonlinear Dynamic Systems using Hybrid Neural Networks , 1995 .

[29]  Benjamin Kuipers,et al.  Qualitative Simulation , 1986, Artificial Intelligence.

[30]  Jacky Montmain,et al.  Dynamic Model and Causal Knowledge-Based Fault Detection and Isolation , 1997 .

[31]  Ali Cinar,et al.  Intelligent Process Monitoring by Interfacing Knowledge-Based Systems and Multivariate SPC Tools , 1997 .

[32]  Gianfranco Lamperti,et al.  Preventive Diagnosis: A Task for Predicting Faults , 1997 .

[33]  David Williams,et al.  Diagnosing Faults at Different Process Operating Points Using Neural Networks , 1997 .

[34]  Paul M. Frank,et al.  Fault Diagnosis in Dynamic Systems , 1993, Robotics, Mechatronics and Manufacturing Systems.

[35]  M. S. Goodman,et al.  Applications of Neural Networks in Automotive Engine Management Systems , 1997 .

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

[37]  F. E. Finch,et al.  A robust event-oriented methodology for diagnosis of dynamic process systems , 1990 .

[38]  M. R. Herbert,et al.  An initial evaluation of the detection and diagnosis of power plant faults using a deep knowledge representation of physical behaviour , 1987 .

[39]  Michèle Basseville,et al.  Detecting changes in signals and systems - A survey , 1988, Autom..

[40]  Chelsea C. White,et al.  A Survey of Expert Systems for Equipment Maintenance and Diagnostics , 1989 .

[41]  C. McGreavy,et al.  Operational Support System for On-Line Faults Monitoring in Chemical Manufacturing , 1997 .

[42]  Yuchun Lee,et al.  Handwritten Digit Recognition Using K Nearest-Neighbor, Radial-Basis Function, and Backpropagation Neural Networks , 1991, Neural Computation.

[43]  Brian Surgenor,et al.  Plant-Wide Feedback Control Performance Assessment using an Expert System Framework , 1995 .

[44]  Paul M. Frank,et al.  Analytical and Qualitative Model-based Fault Diagnosis - A Survey and Some New Results , 1996, Eur. J. Control.

[45]  Kourosh Danai,et al.  Fault Diagnosis With a Model-Based Recurrent Neural Network , 2000, Dynamic Systems and Control: Volume 1.

[46]  Paul M. Frank,et al.  Recurrent Neural Networks for Nonlinear System Modelling in Fault Detection , 1997 .

[47]  Prasad Dhurjati,et al.  An Expert System for Crude Unit Process Supervision , 1995 .

[48]  Jan Maciej Kościelny,et al.  Fuzzy Logic Application to Diagnostics of Industrial Processes , 2003 .

[49]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[50]  W. Schmitt,et al.  A Neural Network Approach for Acoustic Leak Monitoring at Pressurized Plants with Complicated Topology , 1995 .

[51]  A. N. Boudaoud,et al.  On-Line Adaptive Fuzzy Diagnosis System: Fusion and Supervision , 1997 .

[52]  J. B. Gomm,et al.  Diagnosing Sensor Faults in a Chemical Process Via RBF Networks , 1997 .

[53]  J. B. Gomm Process Fault Diagnosis using a Self-Adaptive Neural Network with On-Line Learning Capabilities , 1995 .

[54]  Paul M. Frank,et al.  Physical Parameter Estimation Based FDI with Neural Networks , 1997 .

[55]  P. M. Lister,et al.  Sensor Fusion for Cutting Tool State Identification in Metal Turning Through the Application of Perceptron Neural Networks , 1997 .

[56]  Spyros G. Tzafestas Second Generation Diagnostic Expert Systems: Requirements, Architectures and Prospects , 1991 .

[57]  Hartmut Freitag Bericht über den First International Workshop on Principles of Diagnosis , 1990, Künstliche Intell..

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

[59]  Ilse S. Li,et al.  Prediction and Prevention of Sheetbreak Using PLS and an Expert System , 1997 .

[60]  Michel Kinnaert,et al.  Fault diagnosis based on analytical models for linear and nonlinear systems - a tutorial , 2003 .

[61]  Eric J. Manders,et al.  FDI of abrupt faults with combined statistical detection and estimation and qualitative fault isolation , 2003 .

[62]  A Chatzinikolaou,et al.  Prediction and diagnosis of faults in hydraulic systems , 2002 .

[63]  Yasuhiko Dote,et al.  Novel “On-Line” Identification Procedure using Artificial Neural Network , 1995 .

[64]  M. La Cava,et al.  An Approach to Fault Diagnosis for Non Linear Dynamic Systems Using Neural Networks , 1997 .

[65]  J.J. Gertler,et al.  Survey of model-based failure detection and isolation in complex plants , 1988, IEEE Control Systems Magazine.

[66]  Jan Lunze,et al.  Parallel Knowledge-Based Process Diagnosis Applied to a Local Power Station Plant , 1997 .

[67]  Chrissanthi Angeli,et al.  A Model-Based Method for an Online Diagnostic Knowledge-Based System , 2001, Expert Syst. J. Knowl. Eng..

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

[69]  Giorgio Rizzoni,et al.  Diagnosis of an automotive emission control system using fuzzy inference , 1997 .

[70]  Józef Korbicz,et al.  A Knowledge-Based System with Embedded Estimation Components for Fault Detection and Isolation in Process Plants , 1992 .

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

[72]  Venkat Venkatasubramanian,et al.  A neural network methodology for process fault diagnosis , 1989 .

[73]  Henk B. Verbruggen,et al.  A Real-Time Fuzzy, Deep-knowledge Based Fault-diagnosis System for a CSTR , 1992 .

[74]  Ron J. Patton,et al.  Fault detection and diagnosis in aerospace systems using analytical redundancy , 1991 .

[75]  C. McGreavy,et al.  Soft Sensor Based Fault Diagnosis of Industrial Fluid Catalytic Cracking Reactor , 1997 .

[76]  Spyros G. Tzafestas SECOND GENERATION DIAGNOSTIC EXPERT SYSTEMS: REQUIREMENTS, ARCHITECTURES AND PROSPECTS , 1992 .

[77]  Rolf Isermann Experiences with Process Fault Detection Methods via Parameter Estimation , 1987 .

[78]  Raghunathan Rengaswamy,et al.  An Integrated Framework for Process Monitoring, Diagnosis, and Control using Knowledge-Based Systems and Neural Networks , 1992 .

[79]  Paul M. Frank,et al.  Fault Detection and Isolation with Qualitative Models , 1997 .

[80]  DvorakDaniel,et al.  Process Monitoring and Diagnosis , 1991 .

[81]  Ron J. Patton,et al.  Information Fusion in Fault Diagnosis Based on B-Spline Networks , 1997 .

[82]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[83]  Thomas J. Laffey,et al.  Real-Time Knowledge-Based Systems , 1988, AI Mag..

[84]  Michèle Basseville,et al.  Model-based statistical signal processing and decision theoretic approaches to monitoring , 2003 .

[85]  Herbert Kay Robust Identification Using Semiquantitative Methods , 1997 .

[86]  Spyros G. Tzafestas,et al.  System Fault Diagnostics, Reliability and Related Knowledge-Based Approaches , 1987, Springer Netherlands.

[87]  Brian Falkenhainer,et al.  Self-Explanatory Simulations: An Integration of Qualitative and Quantitative Knowledge , 1990, AAAI.

[88]  Michał Syfert,et al.  On-Line Actuator Diagnosis Based on Neural Models and Fuzzy Reasoning: The DAMADICS Benchmark Study , 2003 .

[89]  Johan de Kleer,et al.  Readings in qualitative reasoning about physical systems , 1990 .

[90]  Peter D. Roberts,et al.  Fault diagnosis of a mixing process using deep qualitative knowledge representation of physical behaviour , 1990, J. Intell. Robotic Syst..

[91]  E. A. Woods,et al.  Fault detection, supervision and safety for technical processes , 1993 .

[92]  David M. Himmelblau Use of Artificial Neural Networks to Monitor Faults and for Troubleshooting in the Process Industries , 1992 .

[93]  Stuart Bennett,et al.  Dynamic System Fault Diagnosis Based on Neural Network Modelling , 1997 .

[94]  Jie Zhang,et al.  Knowledge-Based Gross Error Detection and Data Reconciliation for PET Optimal Control , 1997 .

[95]  Thomas Parisini,et al.  Direct Model-Based Fault Diagnosis Using Neural Filters , 1997 .

[96]  Tor Arne Johansen,et al.  An Integrated Approach to On-line Fault Detection and Diagnosis - Including Artificial Neural Networks with Local Basis-Functions , 1992 .

[97]  Y. Lee Handwritten digit recognition using k nearest neighbour radial-basis function, and backpropagation , 1991 .

[98]  Lyle H. Ungar,et al.  Fault Detection and Diagnosis using Qualitative Modelling and Interpretation , 1992 .

[99]  Mike J. Chantler,et al.  Towards Model Switching for Diagnosis of Dynamic Systems , 1997 .

[100]  Robert Milne,et al.  Model Based Aspects of the TIGER Gas Turbine Condition Monitoring System , 1997 .

[101]  P. D. Roberts,et al.  Fault Detection and Diagnosis Based on Fuzzy Qualitative Reasoning , 1997 .

[102]  Johan de Kleer,et al.  A Qualitative Physics Based on Confluences , 1984, Artif. Intell..

[103]  Heikki N. Koivo,et al.  Application of artificial neural networks in process fault diagnosis , 1991, Autom..

[104]  Józef Korbicz,et al.  Neural Networks and their Application in Fault Detection and Diagnosis , 1997 .

[105]  Visakan Kadirkamanathan,et al.  Autonomously Learning Fault Detection System for Gas Turbine Engines , 1997 .

[106]  Ron J. Patton,et al.  Fault-Tolerant Control: The 1997 Situation , 1997 .

[107]  Cheng-Ching Yu,et al.  Fault diagnosis based on qualitative/quantitative process knowledge , 1991 .

[108]  Franz Barachini Advances in Real-Time Expert System Technologies - Workshop Report , 1993, AI Mag..

[109]  J. Gertler Structured Residuals for Fault Isolation, Disturbance Decoupling and Modelling Error Robustness , 1992 .

[110]  Arthur L. Dexter,et al.  On-Line Fault Detection and Diagnosis using Fuzzy Models , 1995 .

[111]  Giorgio Rizzoni,et al.  Diagnosis of Automotive Emission Control System Using Fuzzy Inference , 1997 .

[112]  H. Penny Nii,et al.  The Handbook of Artificial Intelligence , 1982 .

[113]  Thomas Parisini,et al.  Fault Detection in Mechanical Systems with Friction Phenomena: An On-Line Neural Approximation Approach , 2003 .

[114]  Ramaswamy Vaidyanathan,et al.  Process fault detection and diagnosis using neural networks , 1990 .

[115]  Rolf Isermann,et al.  Trends in the Application of Model Based Fault Detection and Diagnosis of Technical Processes , 1996 .

[116]  Jie Zhang,et al.  On-line process fault diagnosis using fuzzy neural networks , 1994 .

[117]  Johan de Kleer,et al.  Fundamentals of model-based diagnosis , 2003 .

[118]  Rolf Isermann,et al.  Process Fault Detection Based on Modeling and Estimation Methods , 1982 .