Fault detection and diagnosis (FDD) has developed into a major area of research, at the intersection of systems and control engineering, artificial intelligence, applied mathematics and statistics, and such application fields as chemical, electrical, mechanical and aerospace engineering. IFAC has recognized the significance of FDD by launching a triennial symposium series dedicated to the subject.
The SAFEPROCESS Symposium is organized every three years since the first symposium held in Baden-Baden in 1991. SAFEPROCESS 2006, the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes was held in Beijing, PR China.
The program included three plenary papers, two semi-plenary papers, two industrial talks by internationally recognized experts and 258 regular papers, which have been selected out of a total of 387 regular and invited papers submitted.
* Discusses the developments and future challenges in all aspects of fault diagnosis and fault tolerant control
* 8 invited and 36 contributed sessions included with a special session on the demonstration of process monitoring and diagnostic software tools
The safe and reliable operation of technical systems is of great significance for the protection of human life and health, the environment, and of the vested economic value. The correct functioning of those systems has a profound impact also on production cost and product quality. The early detection of faults is critical in avoiding performance degradation and damage to the machinery or human life. Accurate diagnosis then helps to make the right decisions on emergency actions and repairs. Fault detection and diagnosis (FDD) has developed into a major area of research, at the intersection of systems and control engineering, artificial intelligence, applied mathematics and statistics, and such application fields as chemical, electrical, mechanical and aerospace engineering. IFAC has recognized the significance of FDD by launching a triennial symposium series dedicated to the subject.The SAFEPROCESS Symposium is organized every three years since the first symposium held in Baden-Baden in 1991. SAFEPROCESS 2006, the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes was held in Beijing, PR China. The program included three plenary papers, two semi-plenary papers, two industrial talks by internationally recognized experts and 258 regular papers, which have been selected out of a total of 387 regular and invited papers submitted.* Discusses the developments and future challenges in all aspects of fault diagnosis and fault tolerant control * 8 invited and 36 contributed sessions included with a special session on the demonstration of process monitoring and diagnostic software tools
Front Cover 1
Fault Detection, Supervision and Safety of Technical Processes 2006 2
Copyright Page 3
Contents 8
Part I: Plenary Session 24
Chapter 1. Fault Diagnosis of Networked Control Systems 24
Chapter 2. Fault-tolerance as a Key Requirement for the Control of Modem Systems 36
Chapter 3. Statistical Signal Processing Approaches to Fault Detection 47
Part II: Nonlinear Systems 65
Chapter 4. The Nonlinear Output Frequency Response Function and its Application to Fault Detection 59
Chapter 5. Fault Diagnosis of a Class of Singular Nonlinear Systems 65
Chapter 6. An Algebraic Method for Nonlinear System Decomposition 71
Chapter 7. A Realization Approach for Residual Expressions 77
Chapter 8. Fault Estimation for Nonlinear Descriptor Systems with Lipschitz Constraints via LMI Approach 83
Chapter 9. An Improved Invariance-like Theorem 89
Part III: Neural Networks 95
Chapter 10. Two Neural Net-learning Methods for Model Based Fault Detection 95
Chapter 11. Component Fault Diagnosis using Wavelet Neural Networks with Local Recurrent Structure 101
Chapter 12. Fault Detection in Catalytic Cracking Converter by Means of Probability Density Approximation 107
Chapter 13. Increasing Effectiveness of Model-based Fault Diagnosis: A Dynamic Bayesian Network Design for Decision Making 113
Part IV: Principal Component Analysis 119
Chapter 14. Nonlinear PCA for Process Monitoring using the Local Approach 119
Chapter 15. Improved Model Predictive Control using PCA 125
Chapter 16. Multivariate Statistical Process Monitoring using Multi-scale Kernel Principal Component Analysis 131
Chapter 17. Influence of Scaling and Unfolding in PCA Based Monitoring of Nutrient Removing Batch Process 137
Chapter 18. Nonlinear Multiscale Fault Detection and Identification 143
Part V: Fault Tolerant Control of Network Systems 149
Chapter 19. Reconfiguration in Networked Control Systems: Fault Tolerant Control and Plug-and-play 149
Chapter 20. Set-points Reconfiguration in Networked Dynamical Systems 155
Chapter 21. Decentralized and Autonomous Design for FDI/FTC of Networked Control Systems 161
Chapter 22. Fault Tolerant Hybrid MPC Applied on Sewer Networks 167
Chapter 23. Coordinated Diagnosis of Nondeterministic Automata Networks 173
Chapter 24. Minimising False Alarms Caused by Communication Delays in Networked Sytems 179
Part VI: Flight Control Systems 185
Chapter 25. Modelling of Vertical Gyroscopes with Consideration of Faults 185
Chapter 26. Modelling of Rate Gyroscopes with Consideration of Faults 191
Chapter 27. Advantages of using µ-synthesis for Fault-tolerant Flight Control System 197
Chapter 28. Application of Fault Diagnosis Methodologies to a General Aviation Aircraft 203
Chapter 29. Differential Flatness and Fault Detection in Flight Guidance Dynamics 209
Part VII: Nonlinear Observers 215
Chapter 30. The Observer Design for Nonlinear System with both Input and Output Unknown Disturbances 215
Chapter 31. An LMI Approach to Designing Observers and Unknown Input Observers for Nonlinear Systems 221
Chapter 32. Particle Filters for Dynamic Data Rectification and Process Change Detection 227
Chapter 33. Disturbance Decouping Sequential Monte Carlo Filtering and Application in Nonlinear Robust FaultDiagnosis 233
Chapter 34. Fault Diagnostic Filtering using Stochastic Distributions in Nonlinear Generalized H8 Setting 239
Part VIII: Neuro-fuzzy Systems 245
Chapter 35. A New Dynamic Neuro-fuzzy System Applied to Fault Diagnosis of an Evaporation Station 245
Chapter 36. Fault Detection by Neuro-fuzzy Identification in a Nonlinear System 251
Chapter 37. Intelligent Fault Diagnosis in Lead-zinc Smelting Process 257
Chapter 38. Robust Fuzzy Fault Detection for Continuous-time Nonlinear Dynamic Systems 263
Chapter 39. Online Fault Detection and Isolation of Nonlinear Systems Based on Neurofuzzy Networks 269
Chapter 40. A Vibration Fault Diagnosis System of HGS Based on FNN 275
Part IX: Statistical Methods 281
Chapter 41. On Line Change Detection with Nuisance Parameters 281
Chapter 42. Condition Monitoring of Model Predictive Control Systems using Markov Models 287
Chapter 43. An Approach to Detect and Isolate Faults for Nonlinear Systems with Periodic Input 293
Chapter 44. The Research of Process Monitoring Based on Data Fusion Theory 299
Chapter 45. Detection Limits for Linear Non-Gaussian State-Space Models 305
Part X: Networked Control Systems Tolerant to Faults 311
Chapter 46. Multi-red Controller for Router Fault Accommodation 311
Chapter 47. Ftc Strategies in Model Predictive Control of a Dearomatisation Process 317
Chapter 48. Robustness against Unknown Networked Induced Delays of Observer based FDI 323
Chapter 49. Observer-based Monitoring of Distributed Networked Control Systems 329
Chapter 50. NetworkCalculus based FDI Approach for Switched Ethernet Architecture 335
Chapter 51. Control Reconfiguration in Networked Control System 341
Part XI: Aeronautics and Aerospace 347
Chapter 52. Application of Diagnostic Techniques to an Experimental Aircratt Fuel Rig 347
Chapter 53. Fault Tolerance Evaluation of a Neural Predictive Flight Control System 353
Chapter 54. Sliding Mode Fault Detection and Isolation in a Satellite Leader/Follower System 359
Chapter 55. Robust Fault Diagnosis of the Microscope Satellite Micro-thrusters 365
Chapter 56. A Unified Failure/damage Approach to Battle Damage Regeneration : Application to Ground Military Systems 371
Chapter 57. On Robust Fault-tolerant Control of Missile Control System 377
Part XII: Parity Relations 383
Chapter 58. Parity Relations for Linear Dynamic Systems with Multiplicative Uncertainties 383
Chapter 59. Parity Relation based Fault Estimation for Nonlinear Systems: An LMI Approach 389
Chapter 60. An Integrated Way to Design FD/FTC Modules via Parity Space and Model Following 395
Chapter 61. Fault Detection of Descriptor Systems 401
Chapter 62. Fault Diagnosis of Sensors in Autonomous Underwater Vehicle: Adaptive Quasi-linear Parity Relations Method 407
Chapter 63. Fuzzy Parity Equation for Fault Detection and Identification of Nonlinear Systems 413
Part XIII: Intelligent Systems 419
Chapter 64. Fault Diagnosis System based in Agents 419
Chapter 65. Regression-based Variable Reconstruction in Multivariate Systems 425
Chapter 66. Surface Roughness and Cutting Tool-wear Diagnosis Based on Bayesian Networks 431
Chapter 67. The Use of Evolutionary Optimization in Fuzzy TSK Model Identification 437
Chapter 68. Adaptive Structural Analysis for FDI Design in Evolving Systems 443
Part XIV: Information Theory and Bayesian Approaches 449
Chapter 69. Robust Fault Detection and Isolation based on the Kullback Divergence 449
Chapter 70. Entropy Optimization Filtering for Fault Isolation of Non-gaussian Systems 455
Chapter 71. A Maximum Entropy based Approach to Fault Diagnosis using Discrete and Continuous Features 461
Chapter 72. Dynamic Bayesian Networks in System Reliability Analysis 467
Chapter 73. A Bayesian Approach to Fault Isolation-Structure Estimation and Inference 473
Chapter 74. Non-logarithmic Probabilistic Rates of the Object Condition's Uncertainty and the Diagnostic Symptoms' Informativity 479
Part XV: On Active Fault Tolerant Control 485
Chapter 75. Active Actuator Fault Tolerant Control Design for Polytopic LPV Systems 485
Chapter 76. Full Vehicle Active Suspension: Sensor Fault Diagnosis and Fault Tolerance 491
Chapter 77. Structural Design of Systems with Safe Behavior Under Single and Multiple Faults 497
Chapter 78. Fault Tolerant Control for Uncertain Systems with Parametric Faults 503
Chapter 79. Development of Fault Tolerant Control System for Condensation Power Turbine 509
Chapter 80. Reconfiguration on Electric Vehicle After Major Actuator Faults 515
Part XVI: Automotive Systems 521
Chapter 81. Fault Diagnosis of an Active Suspension Control System 521
Chapter 82. Determining a Component's Fault Status and the Status' Readiness 527
Chapter 83. Fault Detection of a Steering Wheel Sensor Signal in an Active Front Steering System 533
Chapter 84. Hierarchical Modelling and Diagnosis for Embedded Systems 539
Chapter 85. Fault Detection using Redundant Navigation Modules 545
Part XVII: Linear Observers I 551
Chapter 86. Designing Diagnostic Observers via Entirely-left Eigenstructure Assignment 551
Chapter 87. Fast Rate Fault Detection for Multirate Sampled-data Systems with Time-delays 557
Chapter 88. Observer Gain Effect in Linear Interval Observer-based Fault Detection 563
Chapter 89. A Model-free Fault Detection Approach of Continuous-time Systems from Time Domain Data 569
Chapter 90. Analysis of Observer-based Fault Tolerant Control Systems with Markovian Parameters 575
Chapter 91. Designing FDI Observers by Improved Evolutionary Multi-objective Optimization 580
Part XVIII: Uncertain Systems 586
Chapter 92. Active Fault Diagnosis by Temporary Destabilization 586
Chapter 93. Generation of Set Membership Tests for Fault Diagnosis and Evaluation of their Worst Case Sensitivity 592
Chapter 94. Fault Detection based on Set-membership Inversion 598
Chapter 95. Parameter Uncertainties Characterisation for Linear Models 604
Chapter 96. Active Fault Diagnosis in Closed-loop Uncertain Systems 610
Chapter 97. Multiple Model Weight Estimation for Models with no Common State 616
Part XIX: Sttisticalmethods II 622
Chapter 98. Eliminating the Initial State for the Generalized Likelihood Ratio Test 622
Chapter 99. Local Approach for Fault Detection in Redundant Sensor Configuration 628
Chapter 100. Handling the Temperature Effect in Vibration Monitoring of Civil Structures: A Combined Subspace-based and Nuisance Rejection Approach 634
Chapter 101. Linear or Nonlinear? A Bicoherence Based Metric of Nonlinearity Measure 640
Chapter 102. Real-time Fault Detection and Isolation with Supervised Training 646
Part XX: Demonstration of Process Monitoring and Diagnostic Software Tools 652
Chapter 103. Satool - A Software Tool for Structural Analysis of Complex Automation Systems 652
Chapter 104. Advanced Monitoring and Diagnostic System 'AMandD'. 658
Chapter 105. Fault Monitoring & Fault Tolerant Control in ControlBuild Software Platform
Chapter 106. Software for Supervision System Design in Process Engineering Industry 669
Chapter 107. An Introduction to a Matlab-based FDI-Toolbox 674
Chapter 108. A Toolbox for Design of Diagnosis Systems 680
Part XXI: Power Systems 686
Chapter 109. Fault Diagnosis for a Steam Generator Via Recurrent Neural Networks 686
Chapter 110. Towards Symptoms of Degradation in On-line Thermal and Flow Diagnostics of Power Objects 692
Chapter 111. Monitorability Analysis for a Gas Turbine using Structural Analysis 698
Chapter 112. Neural Networks Based Diagnostic System for Industrial Purifying Fumes Installation 704
Chapter 113. Observer-based and Regression Model-based Detection of Emerging Faults in Coal Mills 710
Part XXII: Linear Observers II 716
Chapter 114. Decentralised Sliding Mode Observer-based FDI 716
Chapter 115. Observer Gain Effect in Linear Observer-based Fault Detection 722
Chapter 116. Fault Detection System Design for a Class of Stochastically Uncertain Systems 728
Chapter 117. Residual Generator Design for Linear Neutral Delay Systems 734
Chapter 118. A Method for Designing FDI Filters for Polytopic LPV Models 740
Chapter 119. An Input Estimation Method for FDI using Multiple Asynchronous Sensors 746
Part XXIII: Fuzzy Model Uncertainty 752
Chapter 120. Fault Detection Under Fuzzy Model Uncertainty 752
Chapter 121. Fault Isolation using Fuzzy Model-based Observers 758
Chapter 122. Robust Fault Detection for Uncertain Takagi-sugeno Fuzzy Systems with Parametric Uncertainty and Process Disturbances 764
Chapter 123. The Issue of Diagnostic Relation Uncertainty and Fault Conditional Isolability 770
Chapter 124. Reliable Memory Feedback Design for a Class of Nonlinear Fuzzy Systems with Time-varying Delay 776
Chapter 125. Optimal Identification of Takagi-sugeno Fuzzy Models for Nonlinear FDI 782
Part XXIII: Reliability and Maintenance I 788
Chapter 130. Including Systematic Faults into Fault Tree Analysis 788
Chapter 131. Operational Reliability Calculations for Critical Systems 794
Chapter 132. Maintenance Modeling and Scheduling in Fault Tolerant Control Systems 800
Chapter 133. 'Odds Algorithm'-based Opportunity-triggered Preventive Maintenance with Production Policy 806
Chapter 134. A Suitable Inspection Policy Definition for System with Two Modes of Degradation 812
Part XXIV: Diagnosis and Fault Tolerance in Flight Control Systems 818
Chapter 135. Model Weight Estimation for FDI using Convex Fault Models 818
Chapter 136. Fault Tolerant Control of a Large Civil Aircraft using a Sliding Mode based Scheme 824
Chapter 137. Fault Tolerant Safe Flight Controller Bank 830
Chapter 138. A Methodology for the Design of Active Fault Tolerant Control Systems 836
Chapter 139. Fault Tolerant Control of the Boeing 747 Short-period Mode using the Admissible Model Matching Technique 842
Chapter 140. Progressive Accommodation of Aircraft Actuator Faults 848
Part XXV: Industrial Applications I 854
Chapter 141. Monitoring and Diagnosis of Large Scale Industrial Systems 854
Chapter 142. Development of Online Monitoring Scheme for Prediction and Diagnosis of Sheet-break in a Pulp and Paper Mill 860
Chapter 143. Actuator Fault Detection, Isolation Method and State Estimator Design for Hot Rolling Mill Monitoring 866
Chapter 144. Fault Tolerant Control Application for Continuous Kraft Pulping Process 872
Chapter 145. Non-contact Working and Non-interfering Safety System for Sliding Table Saws 878
Part XXVI: Fault Diagnosis Strategies 884
Chapter 146. Diagnostic Accuracy of Models 884
Chapter 147. A Concept of Fault Detection in Embedded Control Systems by Monitoring Cells 890
Chapter 148. A Fault Isolation Algorithm for the Case of Multiple Faults and Multiple Fault Types 896
Chapter 149. Integrated Design of Fault Detection System with Multi-objective Optimization 902
Chapter 150. Fault Detection of NCS Based on Eigendecomposition and Pade Approximation 908
Chapter 151. Residual Generator Identification and Design for Linear Multivariable Systems 913
Part XXVII: Sensor Fault 919
Chapter 152. Structural Analysis for the Sensor Location Problem In Fault Detection and Isolation 919
Chapter 153. A Robust Controller Configuration for Multiple Sensor Fault Tolerance 925
Chapter 154. Sensor Fault Identification using Weighted Combined Contribution Plots 931
Chapter 155. Design of Structured Residuals using Interval Models: Application to Multiple Sequential Fault Isolation in Sensor Networks 937
Chapter 156. Sensor and Inverter Fault Tolerant Control in Induction Motors 943
Part XXVIII: Reliability and Maintenance II 949
Chapter 157. Iterative Expert Driven Fault Diagnosis Based on Structural Modeling 949
Chapter 158. An Inspection & Imperfect Maintenance Model for a System with Two Competing Failure Modes
Chapter 159. Agent-based Maintenance Management System for the Distributed Fault Tolerance 961
Chapter 160. Analysis of CRC-polynomials for Safety-critical Communication by Deterministic and Stochastic Automata 967
Chapter 161. A Degradation Measurements Based Real-time Reliability Prediction Method 973
Chapter 162. Supervison of Human Operators using a Situation-operator Modeling Approach 979
Part XXIX: Monitoring and Fault-tolerant Control Design for Hybrid Dynamical Systems 985
Chapter 163. Adaptive Fault Tolerant Strategy for Hybrid Systems with Faults Independently Effecting on Outputs 985
Chapter 164. Stochastic Stability of a Class of Stochastic Bilinear Hybrid Systems: Convex Analysis and Synthesis 991
Chapter 165. Reconfigurability Analysis for a Class of Linear Hybrid Systems 997
Chapter 166. Fault Detection for HDS by Means of Neural Networks: Application to Two Tanks Hydraulic System 1003
Chapter 167. Faults Detection and Isolation for Non Linear Hybrid Systems 1009
Chapter 167. Fault Detection of a Nonlinear Switching System using Finite Memory Observers 1015
Part XXX: Industrial Applications II 1021
Chapter 168. Application of Correlation Dimension in Leak Identification of Transport Pipelines 1021
Chapter 168. Fault Predictive Control of Compact Disk Players 1026
Chapter 169. Computing Decoupled Residuals for Compact Disc Players 1032
Chapter 170. The Electric Actuator's Fault Diagnosis based on Date Fusion Technology 1038
Chapter 171. AKL Networks for Industrial Analyzer Modeling and Fault Detection 1044
Chapter 172. Design Station for Fault Tolerant Control Systems 1050
Part XXXI: Robust Methods I 1056
Chapter 173. A Method for Actuator Fault Diagnosis with Robustness to Sensor Distortion 1056
Chapter 174. Robust Fault Estimation for Vehicle Lateral Dynamic Systems 1062
Chapter 175. Passive Robust Fault Detection using a Forward-backward Test 1067
Chapter 176. Towards a Better Integration of Passive Robust Interval-based FDI Algorithms 1073
Chapter 177. Robust Fault Detection based on Zonotope-based Set-membership Parameter Consistency Test 1079
Chapter 178. A Reference Model based Robust H¥ Filtering Approach to Fault Detection in Uncertain Systems 1085
Part XXXII: Fault Detection of Networked Control Systems 1091
Chapter 179. Dependability Evaluation of Networked Control Systems Under Transmission Faults 1091
Chapter 180. Fault Detection of Networked Control Systems with Limited Communication 1097
Chapter 181. Fault Detection for MIMO Networked Control System 1103
Chapter 182. Reconfigurable Fault Tolerant PID Networked Control for Magnetic Levitation Case Study 1108
Chapter 183. Fuzzy Modeling and Fault Detection for Networked Control Systems 1114
Chapter 184. Detection of Incipient Faults in Post-fault Systems Subject to Adaptive Fault-tolerant Control 1120
Part XXXIII: Signal Analysis 1126
Chapter 185. Wavelet Packet based Detection of Surface Faults on Compact Discs 1126
Chapter 186. A Comparative Study of Feature Extraction Methods for Crack Detection 1132
Chapter 187. Fault Detection based on Wavelets Transform. Application to a Roughing Mill 1138
Chapter 188. PWA Dynamic Identification for Nonlinear Model Fault Detection 1144
Chapter 189. Alarm Filtering in Intensive Care Units using Multivariable Analysis of Physiological Parameters 1150
Part XXXIV: Model-based Fault Analysis During a Systems Entire Life Cycle 1156
Chapter 190. Fault Analysis Across the Life Cycle of Internet Routers 1156
Chapter 191. Integrated Systems Health Management to Achieve Autonomy in Complex Systems 1162
Chapter 192. Sensoring and Diagnosis of Des with Petri Net Models 1168
Chapter 193. Implementing a Layered Approach to Automated Safety Analysis 1174
Chapter 194. A Model-based Methodology for the Integration of Diagnosis and Fault Analysis During the Entire Life Cycle 1180
Chapter 195. Comparing Diagnosability in Cs and Des 1186
Part XXXV: Applications I 1192
Chapter 196. Static-model-based Residue Generation for Hereditary Process Fault Detection 1192
Chapter 197. Unsupervised Fault Detection of Forest Harvester Head Functions 1198
Chapter 198. Estimating Missing and False Data in Flow Meters of a Water Distribution Network 1204
Chapter 199. Active Robust Fault Estimation on a Composite Beam with Integrated Piezoceramics 1210
Chapter 200. Online Control Sensors for Welding Processes based on Optical Recognition 1216
Chapter 201. Fault Diagnosis of Batch Process based on CMPCA using DTW 1221
Part XXXVI: Robust Methods II 1227
Chapter 202. Robust Fault Diagnosis based on Adaptive Estimation and Set-membership Computations 1227
Chapter 203. Robust Fault Detection using Inverse Images of Interval Functions 1233
Chapter 204. Robust Fault Detection using Interval Constraints Satisfaction and Set Computations 1239
Chapter 205. A QMI Approach to the Robust Fault Detection and Isolation Problem 1245
Chapter 506. Robust Fault Detection for Linear Systems with Multiplicative Noise 1251
Chapter 207. Robust Fault Detection with Unknown Input Set-membership State Estimators and Interval Models using Zonotopes 1257
Part XXXVII: Fault Tolerant Control I 1263
Chapter 208. Control Reconfiguration after Actuator Failures: The Generalised Virtual Actuator 1263
Chapter 209. To Achieve Fault-tolerance using a Linear Controller for Bilinear Systems 1269
Chapter 210. Fault Monitoring in the Presence of Fault-tolerant Control 1275
Chapter 211. A Gain-scheduling and Intelligence Fusion Method for Fault-tolerant Control 1281
Chapter 212. Satisfactory Fault-tolerant Controller Design with Variance and Circular Pole Constraints 1287
Part XXXVIII: Discrete Events I 1293
Chapter 213. Diagnosis of Timed Automata based on an Observation Principle 1293
Chapter 214. From Structural to Functional Models of Complex Systems 1299
Chapter 215. On the Diagnosability of a Class of Hierarchical State Machines 1305
Chapter 216. A Discrete Event Model for Situation Awareness Purposes 1311
Chapter 217. Efficient On-line Failure Identification for Discrete-event Systems 1317
Chapter 218. Fault Diagnosis of Constrained Nonlinear Systems using Structured Augmented State Models 1323
Part XXXIX: Fault Tolerant Control and Fault Detection Isolation Design via Reliability Analysis 1329
Chapter 219. Reliability Evaluation of Fault Tolerant Control Systems with a Semi-markov Fdi Model 1329
Chapter 220. Fault Tolerant Control System Design: A Reconfiguratin Strategy based on Reliability Analysis Under Dynamic Behavior Constraints 1335
Chapter 221. A Monte Carlo Analysis and Design for FDI of a Satellite Attitude Control System 1341
Chapter 222. Multiple Fault Diagnosis System Design using Reliability Analysis: Application to Barcelona Rain-gauge Network 1347
Chapter 223. Reliability Evaluation for Fault Diagnosis In Complex Systems 1353
Chapter 224. Effect of Acknowledement on Performance of a Fault-tolerant Wireless Network 1359
Part XL: Applications II 1365
Chapter 225. Using Filter Diagonalization for Fault Detection in Low-speed Rotational Machinery 1365
Chapter 226. Fault Detection of Rotating Machinery from Bicoherence Analysis of Vibration Data 1371
Chapter 227. Incipient Fault Detection of Gearbox Bearings Through Combined Vibration Analysis 1377
Chapter 228. An Algorithm for Detecting Faults in Railway Point Mechanisms 1383
Chapter 229. Neuro-fuzzy Fault Detection and Diagnosis for Railway Track Circuits 1389
Chapter 230. A Study of Fault Diagnosis and Recovery Techniques for Manufacturing Systems 1395
Part XLI: Robust Methods III 1401
Chapter 231. Multiobjective Design of Robust Fault Detection Systems 1401
Chapter 232. Robust Diagnosis using State-set Observation 1407
Chapter 233. Application of the MLP Neural Network to the Robust Fault Detection 1413
Chapter 234. Detection and Isolation of Model-plant Mismatch for Multivariate Dynamic Systems 1419
Chapter 235. A Robust Fault Isolation Method based on DTW 1425
Chapter 236. Robust Fault Detection and Isolation in Mobile Robot 1430
Part XLII: Fault Tolerant Control II 1436
Chapter 237. Actuator Fault Tolerance Evaluation of Constrained Nonlinear MPC using Constraints Satisfaction 1436
Chapter 238. Robust Static Output Feedback H¥ Control of a Class of Stochastic Hybrid Systems in Noisy Environment: LMI Formulation 1442
Chapter 239. Fault Tolerant Control using Fuzzy MPC 1448
Chapter 240. Fuzzy Fault-tolerant Control System Design with Multi-indices Constraints 1454
Chapter 241. Issues on Integration of Fault Diagnosis and Reconfigurable Control in Active Fault-tolerant Control Systems 1460
Chapter 242. Integration of Health Monitoring in the Avionics Maintenance System 1472
Part XLIII: Discrete Events II 1478
Chapter 243. Comparative Study Between the Timed Automata and the Recurrent Radial Basis Function for Discrete Event System Diagnosis 1478
Chapter 244. Predictability in Discrete-event Systems Under Partial Observation 1484
Chapter 245. Remote Diagnosis of Discrete-event Systems with On-board and Off-board Components 1490
Chapter 246. Towards Low-cost Fault Diagnosis in Large Component-based Systems 1496
Chapter 247. Intermittent Fault Detection Through Message Exchanges: A Coherence based Approach 1502
Chapter 248. Monitorability Indexes and Bond Graphs for Fault Tolerance Analysis 1508
Part XLIV: Applications III 1514
Chapter 249. Detection of Information Failures in Marine Navigation Systems and their Reconditioning 1514
Chapter 250. Lyapunov Exponent Analysis to Chaotic Phenomena of Marine Power System 1520
Chapter 251. A Fault Tolerant Multi-sensor Navigation System for an Unmanned Surface Vehicle 1526
Chapter 252. Improving the Determination of Minimal Hitting Sets in Model-based Diagnosis using Constraint Databases 1532
Chapter 253. Active Fault-tolerant Control of a Double Inverted Pendulum 1538
AUTHOR INDEX 1544
Including Systematic Faults into Fault Tree Analysis
Israel Barragan Santiago*,(1)barragan@lurpa.ens-cachan.fr; Jean-Marc Faure(1),(2)faure@lurpa.ens-cachan.fr; Yiannis Papadopoulos(3) (l) LURPA – ENS Cachan – 61, Avenue du President Wilson, 94230 Cachan, France
(2) Institut Supérieur de Mécanique de Paris (SUPMECA) – 3 rue Fernand Hainaut, 93407 Saint-Ouen, France
(3) Department of Computer Science, University of Hull – Hull HU6 7RX, UK
* The Mexican Council of Technology CONACYT finances Israel Barragan.
Abstract
Fault Tree Analysis (FTA) is a technique widely used for fault forecasting of physical systems. Although FTA is considered a well established safety analysis technique, paradoxically classical Fault Trees include only random faults. However, in modem automated systems, undesirable events arise not only from random hardware faults but also from defects in the logic of software controllers that control the physical system. Faults generated by these software controllers are systematic faults caused by coding errors or misinterpretations of control requirements. This paper proposes an extension to the basic Fault Trees construction process which takes into account this category of faults and advocates the use of dynamic and temporal gates to model it. Copyright © 2006 IFAC
Keywords
Controller dependability
Event ordering
Fault tree analysis
Safety analysis
Temporal fault tree
1 INTRODUCTION
Since its development in 1960by Bell Labs, a large volume of technical and scientific work has been reported in the literature about FTA. Today, it is a well-known fault forecasting technique which is widely used in the design of safety critical systems. Fault Trees are commonly used to represent the effect that random hardware faults of components have on a system. One difficulty with applying this technique on modem automated systems is that such systems are the combination of logic controllers and controlled processes where controllers receive and process inputs coming from the processes and generate outputs to the processes (see figure 1). Clearly, therefore, safety analysis of such systems must take into account not only the physical faults of components, including those of controllers, but also any faults caused by errors in the logic of those controllers.
In this paper, we focus on logic controller faults and we develop a method for their representation in FTA. Logic controller faults can be categorized in three classes depending on whether they are caused by:
• Hardware failures of the controller
• Unhanded deviations of controller inputs caused by failures of sensors connected to the controller
• Design flaws in the logic (software) of the controller, either a result of coding errors or misinterpretation of control requirements.
The first two classes of fault are currently considered in a classical FTA. Indeed in the course of such analysis, an erroneous output of a controller is typically attributed to primary and secondary hardware failures of the controller itself or to command failures typically deviations of controller inputs which are in turn caused by failures of connected sensors. The work developed here proposes to extend the FT method to integrate the analysis of the third class of faults in the above categorisation, i.e. those caused by design flaws.
Such faults fall in the general category of systematic faults because they can be reproduced every time the conditions that trigger the error in the control logic are present. These conditions are typically sets of correct inputs which by triggering the embedded error result to a fault manifested as an omission or commission of controller outputs or deviations of outputs from correct timing or value. Identifying these kinds of faults, therefore, requires from analysts to assume that even with correct input information the controller fails, delivering no output or erroneous outputs.
The integration, into the fault tree structure, of controller faults that can potentially be attributed to design flaws can assist the targeted investigation and eventual elimination of such flaws in relevant parts of the control logic. We should point out that although, in general, there may be large numbers of errors in a program, it is only a small portion of those errors that will trigger faults that can contribute to the hazard investigated as a top event in a particular fault tree. It is precisely those critical systematic faults that the proposed extension to FTA aims to identify.
The purpose of identifying faults caused by design errors is to remove those errors. FTA is a simple and widely applied method, familiar to most safety engineers. Extending its application on software controlled systems, therefore, will be beneficial in terms of improved fault forecasting and fault removal in such systems.
The inclusion of controller faults in fault trees requires an extended FTA vocabulary, in which the notions of time and event ordering exist and can be used to describe relationships among input conditions that trigger the fault and output conditions with which the fault is manifested. Managing that goal is an important point discussed here.
This paper is structured as follows. Section 2 recalls fundamentals and standard construction rules of fault trees. Section 3 deals with the extension of FTA to include systematic faults. The use of dynamic and temporal gates to represent temporal relationships between events is developed in section 4. The method is illustrated with a simple example in section 5. Conclusions and prospects are discussed in the last section.
2 FAULT TREE DESIGN
2.1 Fault Tree fundamentals
Fault Tree Analysis aims at identifying all sufficient and necessary combinations of basic events in a system that cause the top event of the fault tree which represents a hazardous system failure. These combinations of basic events are called Minimal Cut Sets. A basic event, typically a component fault, is a leaf node in the tree, i.e. an event that is not developed further in the analysis. The connections between the various identified basic events are carried out by means of logical gates. The two most commonly used gates are the AND-gate and the OR-gate.
Besides gates, several symbols are used to represent the fault events. Rectangles are used to describe intermediate events that result from the conjunction or disjunction of several basic events. Circles describe basic events that require no further development. Diamonds represent undeveloped events, which are conditions not further examined either because they are considered highly unlikely, and thus of no interest, or because information is unavailable. See figure 2.
Several commercial software tools support manual fault tree construction and automate qualitative analysis (i.e. calculation of minimal cut sets) as well as quantitative estimation of system unavailability from probabilities of basic events. Methods for automatic construction of fault trees are described in (Papadopoulos et al., 2001) and (Laengst et al., 2003).
2.2 Fault Tree construction
To provide a systematic way in which the construction of the fault tree may be approached is proposed in the fault tree handbook (US N.R. Commission, 1981). It is generally followed by analysts and has been included into other texts that provide guidance on construction such as (Andrews, 2002). The approach requires events in the fault tree to be classified as state-of-component faults or state-of-system faults. A state-of-component fault is one that can be caused by a single component failure. If a single component failure cannot cause the fault then it is classified as a state-of-system which behaves as an intermediate event.
State-of-component faults, are then developed using the fault tree structure illustrated in figure 2. A primary fault represents the failure of a component due to its internal defects. It occurs in an environment for which the component is qualified. A secondary fault is a fault of a component caused by excessive environmental or operational stress. In other words, a secondary fault represents a situation in which the component fails in conditions that exceed the conditions for which it was designed.
Finally, a command fault describes a situation in which the component has not physically failed but operates in the wrong time or context. In such conditions, the component typically produces no output or incorrect output in response to inappropriate or misleading inputs received either from sensors or controllers that control its operation.
Primary faults represent basic events of the fault tree. On the other hand, secondary faults can be further investigated in which case the causes of any excessive environmental conditions are identified. For example if the condition is unacceptably high temperature, a failure of a cooling subsystem may be identified as a cause. Finally, command faults represent intermediate...
| Erscheint lt. Verlag | 1.3.2007 |
|---|---|
| Sprache | englisch |
| Themenwelt | Recht / Steuern ► Wirtschaftsrecht |
| Technik ► Bauwesen | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Maschinenbau | |
| Wirtschaft ► Betriebswirtschaft / Management ► Logistik / Produktion | |
| Betriebswirtschaft / Management ► Spezielle Betriebswirtschaftslehre ► Versicherungsbetriebslehre | |
| ISBN-10 | 0-08-055539-X / 008055539X |
| ISBN-13 | 978-0-08-055539-3 / 9780080555393 |
| Haben Sie eine Frage zum Produkt? |
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