| List of Symbols | p. XIII |
| Introduction | p. 1 |
| Process automation and process supervision/condition monitoring | p. 1 |
| Product life cycles and fault management (asset management) | p. 3 |
| Contents | p. 5 |
| Supervision, fault-Detection and diagnosis | |
| Supervision, fault-detection and diagnosis methods - a short introduction | p. 11 |
| Basic tasks of supervision | p. 11 |
| Terminology | p. 17 |
| Faults, failures, malfunctions | p. 17 |
| Reliability, availability, safety | p. 19 |
| Fault tolerance and redundancy | p. 21 |
| Knowledge-based fault detection and diagnosis | p. 22 |
| Analytic symptom generation | p. 22 |
| Heuristic symptom generation | p. 23 |
| Fault diagnosis | p. 24 |
| Signal-based fault-detection methods | p. 24 |
| Limit checking of absolute values | p. 25 |
| Trend checking | p. 25 |
| Change detection with binary thresholds | p. 26 |
| Adaptive thresholds | p. 27 |
| Plausibility checks | p. 28 |
| Signal-analysis methods | p. 29 |
| Process-model-based fault-detection methods | p. 30 |
| Process models and fault modeling | p. 32 |
| Fault detection with parameter estimation | p. 34 |
| Fault detection with state observers and state estimation | p. 35 |
| Fault detection with parity equations | p. 37 |
| Direct reconstruction of non-measurable variables | p. 38 |
| Fault-diagnosis methods | p. 39 |
| Classification methods | p. 39 |
| Inference methods | p. 41 |
| Fault detection and diagnosis in closed loop | p. 41 |
| Data flow structure for supervision (condition monitoring) | p. 43 |
| Drives and Actuators | |
| Fault diagnosis of electrical drives | p. 49 |
| Direct-current motor (DC) | p. 49 |
| Structure and models of a DC motor | p. 49 |
| Fault detection with parity equations | p. 52 |
| Fault detection with parameter estimation | p. 54 |
| Experimental results for fault detection (SELECT) | p. 55 |
| Experimental results for fault diagnosis with a learning fault-symptom tree | p. 57 |
| Conclusions | p. 63 |
| Alternating-current motor (AC) | p. 63 |
| Structure and models of induction motors (asynchronous motors) | p. 64 |
| Signal-based fault detection of the power electronics | p. 66 |
| Model-based fault detection of the AC motor | p. 71 |
| Conclusions | p. 80 |
| Fault diagnosis of electrical actuators | p. 81 |
| Electromagnetic actuator | p. 81 |
| Position control | p. 83 |
| Fault detection with parameter estimation | p. 85 |
| Electrical automotive throttle valve actuator | p. 87 |
| Structure and models of the actuator | p. 88 |
| Input test cycle for quality control | p. 89 |
| Fault detection with parameter estimation | p. 91 |
| Fault detection with parity equation | p. 94 |
| Fault diagnosis | p. 95 |
| Fault-diagnosis equipment | p. 96 |
| Conclusions | p. 98 |
| Brushless DC motor and aircraft cabin pressure valve | p. 98 |
| Structure and models | p. 98 |
| Fault detection with parameter estimation | p. 101 |
| Fault detection with parity equations | p. 102 |
| Conclusions | p. 104 |
| Fault diagnosis of fluidic actuators | p. 105 |
| Hydraulic servo axis | p. 105 |
| Hydraulic servo axis structure | p. 106 |
| Faults of hydraulic servo axes | p. 106 |
| Models of spool valve and cylinder | p. 111 |
| Fault detection and diagnosis of valve and cylinder | p. 115 |
| Conclusions | p. 121 |
| Pneumatic actuators | p. 121 |
| Pneumatic-actuator construction | p. 122 |
| Faults of pneumatic valves | p. 124 |
| Models of pneumatic valves | p. 125 |
| Fault detection with valve characteristics | p. 128 |
| Fault detection of flow valves with pneumatic position controller | p. 130 |
| Fault detection of flow valves with electronic position controller | p. 138 |
| Conclusions | p. 139 |
| Machines and Plants | |
| Fault diagnosis of pumps | p. 143 |
| Centrifugal pumps | p. 143 |
| State of the art in pump supervision and fault detection | p. 143 |
| Models of centrifugal pumps and pipe systems | p. 146 |
| Fault detection with parameter estimation | p. 149 |
| Fault detection with nonlinear parity equations and parameter estimation | p. 156 |
| Fault detection with vibration sensors | p. 165 |
| Conclusions | p. 169 |
| Reciprocating pumps | p. 170 |
| Structure of a diaphragm pump | p. 171 |
| Models of a diaphragm pump | p. 172 |
| Fault detection and fault diagnosis of the hydraulic pump | p. 172 |
| Fault detection of the pump drive | p. 177 |
| Conclusions | p. 178 |
| Leak detection of pipelines | p. 181 |
| State of the art in pipeline supervision | p. 181 |
| Models of pipelines | p. 182 |
| Model-based leak detection | p. 187 |
| Leak detection with state observers | p. 188 |
| Leak detection with mass balance and correlation analysis for liquid pipelines | p. 190 |
| Leak detection for gas pipelines | p. 195 |
| Experimental results | p. 201 |
| Gasoline pipeline | p. 201 |
| Gas pipeline | p. 202 |
| Conclusions | p. 204 |
| Fault diagnosis of industrial robots | p. 205 |
| Structure of a six-axis robot | p. 205 |
| Model of a robot axis and parameter estimation | p. 206 |
| Analytic and heuristic diagnosis knowledge | p. 208 |
| Symptom representation | p. 208 |
| Diagnosis knowledge representation | p. 209 |
| Faults, heuristic symptoms and events of the robot | p. 210 |
| Experimental results | p. 211 |
| Fault diagnosis with analytical knowledge | p. 212 |
| Fault diagnosis with analytical and heuristic knowledge | p. 213 |
| Conclusions | p. 215 |
| Fault diagnosis of machine tools | p. 217 |
| Structures of machine tools | p. 217 |
| Status of machine tools supervision | p. 219 |
| Main drive | p. 221 |
| Two-mass model | p. 221 |
| Parameter estimation | p. 223 |
| Fault detection with parameter estimation | p. 225 |
| Feed drives | p. 226 |
| Two- and three-mass model | p. 226 |
| Identification of a feed drive | p. 229 |
| Fault detection of a feed drive test rig | p. 229 |
| Drilling machines | p. 234 |
| Models of the drilling process | p. 234 |
| Fault detection of drilling | p. 237 |
| Milling machine | p. 239 |
| Models for the milling process | p. 239 |
| Fault detection of the cutter | p. 245 |
| Grinding machines | p. 251 |
| Grinding-process models | p. 252 |
| Fault detection with parameter estimation | p. 254 |
| Fault detection with signal-analysis methods | p. 256 |
| Conclusions | p. 256 |
| Fault detection of heat exchangers | p. 259 |
| Heat exchangers and their models | p. 259 |
| Heat exchanger types | p. 259 |
| Heat exchanger models for stationary behavior | p. 262 |
| Dynamic models of heated tubes | p. 264 |
| Fault detection for static behavior | p. 270 |
| Static models of heat exchangers | p. 270 |
| Fault-detection methods | p. 271 |
| Fault detection for a steam/water heat exchanger with dynamic models and parameter estimation | p. 274 |
| Fault detection with linear dynamic models and parameter estimation | p. 274 |
| Fault detection with parameter variable local linear dynamic models | p. 278 |
| Conclusions | p. 281 |
| Fault-tolerant Systems | |
| Fault-tolerant systems - a short introduction | p. 285 |
| Basic redundant structures | p. 285 |
| Degradation steps | p. 287 |
| Examples of fault-tolerant systems | p. 291 |
| A fault-tolerant control system | p. 291 |
| Fault-tolerant electrical drives | p. 294 |
| A fault-tolerant duplex AC motor | p. 294 |
| Fault-tolerant frequency converter | p. 298 |
| Multi-phase motors | p. 301 |
| Fault-tolerant actuators | p. 301 |
| Fault-tolerant hydraulic actuators | p. 302 |
| Fault-tolerant DC actuator | p. 306 |
| Fault-tolerant sensors | p. 308 |
| Hardware sensor redundancy | p. 308 |
| Analytical sensor redundancy | p. 308 |
| Steering angle sensor | p. 311 |
| Fault-tolerant flow sensor | p. 313 |
| Electronic throttle | p. 314 |
| Virtual drive dynamic sensors by model based analytical redundancy | p. 314 |
| Appendix | |
| Terminology in fault detection and diagnosis | p. 321 |
| Concluding remarks | p. 325 |
| References | p. 329 |
| Index | p. 351 |
| Table of Contents provided by Ingram. All Rights Reserved. |
