Fault-Diagnosis Applications: Model-Based Condition Monitoring: Actuators, Drives, Machinery, Plants, Sensors, and Fault-Tolerant Systems

ISBN-13: 9783642434761 / Angielski / Miękka / 2014 / 354 str.

Rolf Isermann

Opis

Supervision, condition-monitoring, fault detection, fault diagnosis and fault management play an increasing role for technical processes and vehicles in order to improve reliability, availability, maintenance and lifetime. For safety-related processes fault-tolerant systems with redundancy are required in order to reach comprehensive system integrity. This book is a sequel of the book "Fault-Diagnosis Systems" published in 2006, where the basic methods were described. After a short introduction into fault-detection and fault-diagnosis methods the book shows how these methods can be applied for a selection of 20 real technical components and processes as examples, such as: Electrical drives (DC, AC)Electrical actuatorsFluidic actuators (hydraulic, pneumatic)Centrifugal and reciprocating pumpsPipelines (leak detection)Industrial robotsMachine tools (main and feed drive, drilling, milling, grinding)Heat exchangers Also realized fault-tolerant systems for electrical drives, actuators and sensors are presented. The book describes why and how the various signal-model-based and process-model-based methods were applied and which experimental results could be achieved. In several cases a combination of different methods was most successful. The book is dedicated to graduate students of electrical, mechanical, chemical engineering and computer science and for engineers.

Spis treści

1. Introduction

1.1 Process automation and supervision

1.2 Product life cycle and fault management (asset management)

1.3 Contents

I SUPERVISION, FAULT DETECTION AND DIAGNOSIS

2. Supervision, fault detection and fault diagnosis methods

2.1 Basic tasks of supervision

2.2 Terminology

2.2.1 Faults, failures, malfunctions

2.2.2 Reliability, availability, safety

2.2.3 Fault tolerance and redundancy

2.3 Knowledge based fault detection and diagnosis

2.4 Signal based fault detection methods

2.4.1 Limit checking

2.4.2 Trend checking

2.4.3 Change detection

2.4.4 Adaptive thresholds

2.4.5 Plausibility checks

2.4.6 Signal analysis methods

2.5 Processmodel based fault detection methods

2.5.1 Process models and fault modeling

2.5.2 Fault detection with parameter estimation

2.5.3 Fault detection with state observers and state estimation

2.5.4 Fault detection with parity equations

2.5.5 Direct reconstruction of not measurable variables

2.6 Fault diagnosis methods

2.6.1 Classification methods

2.6.2 Inference methods

2.7 Fault detection in closed loops

2.8 Data flow structure for supervision

II DRIVES AND ACTUATORS

3. Fault diagnosis of electrical drives

3.1 Direct current motor (DC)

3.1.1 Structure and models of the DC motor

3.1.2 Fault detection with parity equations

3.1.3 Fault detection with parameter estimation

3.1.4 Experimental results for fault detection

3.1.5 Experimental results for fault diagnosis with SELECT

3.1.6 Conclusions

3.2 Alternating current motor (AC)

3.2.1 Structure and models of induction motors

3.2.2 Signal based fault detection of power electronics

3.2.3 Model based fault detection of an AC motor

3.2.4 Concusions

4. Fault diagnosis of electrical actuators

4.1 Electromagnetic actuator

4.1.1 Position control

4.1.2 Fault detection with parameter estimation

4.2 Electromagnetic automotive throttle valve actuator

4.2.1 Structure and models of the actuator

4.2.2 Input test cycle for quality control

4.2.3 Fault detection with parameter estimation

4.2.4 Fault detection with parity equations

4.2.5 Fault diagnosis

4.2.6 Fault diagnosis equipment

4.2.7 Conclusions

4.3 Brushless DC motor actuator and aircraft cabin pressure valve

4.3.1 Structure and models

4.3.2 Fault detection with parameter estimation

4.3.3 Fault detection with parity equations

4.3.4 Conclusions

5. Fault diagnosis of fluidic actuators

5.1 Hydraulic servo axis

5.1.1 Hydraulic servo axis structure

5.1.2 Faults of hydraulic servo axes

5.1.3 Models of the spool valve and cylinder

5.1.4 Fault detection and diagnosis of the valve and cylinder

5.1.5 Fault diagnosis

5.1.6 Conclusions

5.2 Pneumatic actuators

5.2.1 Pneumatic flow valve structure and modeling

5.2.2 Fault detection and diagnosis with local linear models

5.2.3 Experimental results

5.2.4 Conclusions

III MACHINES AND PLANTS

6. Fault diagnosis of pumps

6.1 Centrifugal pumps

6.1.1 Status of pump supervision and fault detection

6.1.2 Models of a centrifugal pump and pipe system

6.1.3 Fault detection with parameter estimation

6.1.4 Fault detection with nonlinear parity equations and parameter estimation

6.1.5 Conclusions

6.2 Reciprocating pumps

6.2.1 Structure of a diaphragm pump

6.2.2 Models of a diaphragm pump

6.2.3 Fault detection and diagnosis of the hydraulic part

6.2.4 Fault detection of the pump drive

6.2.5 Conclusions

7. Leak diagnosis of pipelines

7.1. Status of pipeline supervision

7.2 Mathematical models of pipelines

7.3 Model based leak detection

7.3.1 Leak detection with state observers

7.3.2 Leak detection with mass balance and correlation analysis for liquid pipelines

7.3.3 Leak detection for gas pipelines

7.4 Experimental results

7.4.1 Gasoline pipeline

7.4.2 Gas pipeline

7.4.3 Conclusions

8. Fault diagnosis of industrial robots

8.1 Structure of a 6-axis robot

8.2 Model af a robot axis

8.3 Fault detection and diagnosis with parameter estimation

8.4 Experimental results

8.5 Conclusions

9. Fault diagnosis of machine tools

9.1 Structure of machine tools

9.2 Status of machine tool supervision

9.3 Main drive

9.4 Feed drive

9.5 Drilling machine

9.3.1 Models of the drilling process

9.3.2 Fault detection of drilling

9.6 Milling machine

9.6.1 Models of the milling process

9.6.2 Fault detection of the cutter

9.7 Grinding machine

9.7.1 Grinding process and models

9.7.2 Fault detection with parameter estimation

9.7.3 Fault detection with signal analysis methods

9.8 Conclusions

10. Fault detection of heat exchangers

10.1 Heat exchangers and their models

10.1.1 Heat exchanger types

10.1.2 Heat exchanger models for stationary behavior

10.1.3 Dynamic models of heated tubes

10.2 Fault detection from static behaviour

10.2.1 Static models of heat exchangers

10.2.2 Fault detection methods

10.3 Fault detection of a steam/water heat exchanger with dynamic models and parameter estimation

10.4 Fault detection for a double heat exchanger plant with local linear neuro-fuzzy models

10.4.1 Steam-water heat exchanger with local linear identification

10.4.2 Heat exchanger plant

10.4.3 Fault detection with multiple local linear parameter estimation

10.5 Conclusions

IV FAULT TOLERANT SYSTEMS

11. Fault-tolerant systems – a short introduction

11.1 Basic redundant structures

11.2 Degradation steps

12. Examples of fault-tolerant systems

12.1 A fault-tolerant control system

12.2 Fault-tolerant electrical drives

12.3 Fault-tolerant actuators

12.4 Fault-tolerant sensors

V APPENDIX

13. Terminology for fault detection and diagnosis

 References

Index

O autorze

Rolf Isermann Rolf Isermann studied Mechanical Engineering and obtained the Dr.-Ing. degree in 1965 from the University of Stuttgart. In 1968 he became "Privatdozent" for Automatic Control and since 1972 Professor in Control Engineering at the University of Stuttgart. From 1977-2006 he was Professor for Control Systems and Process Automation at the Institute of Automatic Control of the Darmstadt University of Technology. Since 2006 he is Professor emeritus and is head of the Research Group of Control Systems and Process Automation. R. Isermann received the Dr. h.c. (honoris causa) from L'Université Libre de Bruxelles and from the Polytechnic University in Bucharest. In 1996 he was awarded the “VDE-Ehrenring”, and in 2007 the “VDI-Ehrenmitglied”. The MIT Technology Review Magazine awarded him in 2003 to the Top Ten representatives of emerging Technologies for the field of Mechatronics. R. Isermann has published books on Modeling of Technical Processes, Process Identification, Digital Control Systems, Adaptive Control Systems, Mechatronic Systems, Fault Diagnosis Systems, Engine Control and Vehicle Drive Dynamics Control. Current research concentrates on the fields of identification and digital control of nonlinear systems, intelligent control and model-based methods of process fault diagnosis with applications to servo systems, fault-tolerant systems, combustion engines, automobiles and mechatronic systems. The research group on combustion engines works on multivariable engine modeling, HiL-simulation, combustion pressure control and fault diagnosis of both, CR-Diesel engines and FSI-gasoline engines. In the vehicle dynamics group present topics are parameter estimation for drive dynamics control, fault detection of sensors, suspensions, tires and brake systems and the development of collision avoidance systems with surrounding sensing and active braking and steering. The first books on system identification were published in German and date back to 1971, 1974, 1988, and 1992. Since 1975, R. Isermann held several chair positions of IFAC-Technical Committees (International Federation of Automatic Control). In 1996, he was elected as Vice-President of IFAC until 2002. From 2002 to 2008, he was member of the IFAC-Council. R. Isermann organized several national and international conferences like the 5th IFAC Symposium on Identification in Darmstadt in 1979, the 10th IFAC-World-Congress in Munich 1987, the 1st IFAC-Symposium SAFEPROCESS, Baden-Baden, 1991 and the 1st IFAC-Conference on Mechatronic Systems, Darmstadt, 2000. He also organized the biannual VDI/VDE-Conference AUTOREG (control of vehicles and power trains) from 2002 to 2008.