Expert Systems in Engineering Applications - Brossura

Brossura

ISBN 10: 3642840507 ISBN 13: 9783642840500

Casa editrice: Springer, 2011

Riassunto

Expert system technology is receiving increasing popularity and acceptance in the engineering community. This book provides a balanced state-of-the-art presentation of te design principles of engineering expert systems, and a representative picture of their capabilities to assist efficiently the design, diagnosis and operation of complex industrial plants.

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Contenuti

I General Issues.- 1 An Overview of Expert Systems.- 1.1 Introduction.- 1.2 Foundations of Expert Systems.- 1.3 Expert System Architecture.- 1.4 Knowledge Representation in Expert Systems.- 1.4.1 Rule-Based Systems.- 1.4.2 Frame-Based Systems.- 1.4.3 Associative Networks.- 1.4.4 Logic-Based Systems.- 1.4.5 Object-Oriented Systems.- 1.4.6 Attribute Grammar Systems.- 1.5 Comparison of Knowledge Representation Methods.- 1.6 Knowledge Representation in Engineering-Based Expert Systems.- 1.7 Conclusion.- 1.8 Bibliography.- 2 Knowledge Acquisition for Expert System Design.- 2.1 Introduction.- 2.2 Human Experts and Expert Systems.- 2.2.1 Human Experts.- 2.2.2 Expert Systems.- 2.3 The Knowledge Acquisition Problem.- 2.3.1 General Issues.- 2.3.2 The Knowledge Engineer.- 2.4 Knowledge Acquisition Techniques.- 2.4.1 Introductory Aspects.- 2.4.2 The Interview Technique.- 2.4.3 Focused Meetings and Discussions.- 2.4.4 Other Techniques.- 2.5 Application Examples.- 2.5.1 Knowledge Acquisition in Industrial Diagnostic Systems.- 2.5.2 Control Algorithm Acquisition.- 2.5.3 Knowledge Acquisition for a Budgetary Expert System.- 2.6 Conclusions.- 2.7 Bibliography.- 3 Synergy of Expert Systems, CAD, and Logic Programming.- 3.1 Introduction.- 3.1.1 A Circuit Pack Troubleshooting Expert System.- 3.1.2 CAD in Expert Systems.- 3.1.3 AI in CAD.- 3.1.4 Outline.- 3.2 Computers-Aided Design of Circuit Pack Troubleshooting Knowledge Bases.- 3.2.1 Previous Works.- 3.2.2 Graphical Interaction.- 3.2.3 The Graphic Interface.- 3.3 Heuristic Search in the Computer-Aided Design of Diagnostic Expert Systems.- 3.3.1 Previous Works.- 3.3.2 Goal Selection.- 3.4 Reification of Expert Systems.- 3.4.1 Automated Programming Systems.- 3.4.2 Reifying = Instantiation + Inference + Translation.- 3.4.3 ESR Architecture.- 3.4.4 Parse Tree.- 3.5 Summary.- 3.6 Bibliography.- II Expert Systems in Engineering Domains.- 4 Expert Systems for Automatic Hardware Synthesis.- 4.1 Introduction.- 4.2 Selected Expert Systems.- 4.3 A Prototype Expert System.- 4.3.1 The Knowledge Base (KB).- 4.3.2 Implementation.- 4.3.3 Results.- 4.4 Extensions.- 4.4.1 AST to IEI Translator.- 4.4.2 The Knowledge Base.- 4.4.3 The Inference Engine.- 4.5 Summary.- 4.6 Bibliography.- 4.7 Appendix.- 5 Expert System of Image Processing and its Application to LANDSAT Image Analysis.- 5.1 Introduction.- 5.2 Knowledge for Image Processing Expert Systems.- 5.3 Overview of ELIA.- 5.3.1 Features of LANDSAT TM Images.- 5.3.2 Configuration of ELIA.- 5.4 Expert System Modules.- 5.4.1 Initial Segmentation.- 5.4.2 Extraction of Waters.- 5.4.3 Road Extraction.- 5.5 Description of Analyzed Data.- 5.5.1 Basic Concept.- 5.5.2 Graph Modification Rules.- 5.6 Experimental Result.- 5.7 Concluding Remarks.- 5.8 Bibliography.- 6 Self-Learning Expert System for Computer Communication Design.- 6.1 Introduction.- 6.2 Notations and Definitions.- 6.2.1 A Graph.- 6.2.2 Non-Oriented Graph.- 6.2.3 Degree of a Graph.- 6.2.4 Network.- 6.2.5 Disjoint Paths Between Nodes.- 6.2.6 Connectivity of the Nodes.- 6.3 The Design Problem.- 6.3.1 Formulation of the Problem.- 6.3.2 Nature and Complexity of the Problem.- 6.3.3 Classical Methods of Resolution.- 6.4 Artificial Intelligence Approach.- 6.4.1 The Architecture of an Expert System.- 6.4.2 Knowledge Representation.- 6.4.3 Knowledge Acquisition and Self-Learning Mechanisms.- 6.5 Design of the Problem-Solving System.- 6.5.1 Principles of the Proposed Method.- 6.5.2 General Organization of the Proposed System.- 6.5.3 Feasibility and Goodness of Solutions.- 6.6 Bibliography.- 7 Application of Artificial Intelligence and Expert Systems in Power Engineering.- 7.1 Introduction.- 7.2 Fault Diagnosis.- 7.2.1 High-Voltage Network Systems.- 7.2.2 Distribution Network Systems.- 7.2.3 Turbine Generators.- 7.3 Power System Control.- 7.3.1 Reactive Power and Voltage Control.- 7.3.2 Blackout Restoration.- 7.3.3 Determination of Load Block Composition in Under-Frequency Load-Shedding Schemes.- 7.3.4 Generator Scheduling.- 7.4 Load and Circuit Allocations.- 7.4.1 Load Allocation in Distribution Substations.- 7.4.2 Circuit Allocation in Subtransmission Switching Substations.- 7.5 Power System Planning.- 7.5.1 Load Flow Planning.- 7.5.2 Generation Expansion Planning.- 7.5.3 Distribution Expansion Planning.- 7.6 Summary and Conclusions.- 7.6.1 Summary of Work to Date.- 7.6.2 Current and Future Trends.- 7.6.3 Future Research and Development Themes.- 7.7 Bibliography.- 8 A Knowledge-Based Approach to Verification and Improvement of Industrial Plan Layout Design.- 8.1 Introduction.- 8.2 Verification Method.- 8.2.1 Problem Definition.- 8.2.2 Configuration of Method.- 8.3 Improvement Method.- 8.3.1 Problem Definition.- 8.3.2 Configuration of Method.- 8.3.3 Optimal Placement.- 8.4 Results and Evaluations.- 8.5 Conclusions.- 8.6 Bibliography.- III Expert Systems in Fault Diagnosis and Process Control.- 9 EXACT ― an Expert System for Automobile Air-Conditioner Compressor Troubleshooting.- 9.1 Introduction.- 9.2 Expert Systems for Troubleshooting.- 9.3 System Development.- 9.3.1 Development of the Knowledge Base.- 9.3.2 Development of the Data Base.- 9.3.3 Development of the Inference Engine.- 9.3.4 Development of the Explanation Module.- 9.4 System Configuration.- 9.5 System Performance Validation.- 9.5.1 Validation Procedure.- 9.5.2 Performance Validation Results.- 9.6 Conclusion.- 9.7 Bibliography.- 9.8 Appendix: An Example of Case Study of EXACT.- 10 Using Prototypical Knowledge in Classification-Based Expert Systems.- 10.1 Introduction.- 10.2 Vibration-Based Monitoring.- 10.3 Overview of DIVA.- 10.3.1 The Situation Recognition Task.- 10.3.2 The Diagnosis Task.- 10.3.3 The Information Retrieval and Data Abstraction Task.- 10.4 Recognition of Typical Situations.- 10.4.1 Description of a Prototype.- 10.4.2 Establish/Refine.- 10.5 Discussion of the Prototype Model.- 10.5.1 Context-Dependent Reasoning.- 10.5.2 System Reliability.- 10.5.3 Knowledge Acquisition.- 10.6 Conclusion.- 10.7 Bibliography.- 11 Combined Control and Diagnosis for Complex Processes: An Intelligent Control Approach.- 11.1 Introduction.- 11.2 Intelligent Control of Complex Processes.- 11.2.1 The Challenge.- 11.2.2 Integrating Control and Diagnosis.- 11.2.3 The Shallow Knowledge Approach: Structure and a Prototype.- 11.2.4 Towards Deep Knowledge: Qualitative Simulation.- 11.2.5 The Semantic Control Approach.- 11.3 An Implementation.- 11.3.1 Program Structure.- 11.3.2 Programming the Finite Automaton in Logic.- 11.3.3 Object-oriented Implementation of the Forward Chainer.- 11.4 Discussion.- 11.5 Bibliography.- 12 Knowledge-Based Adaptive Identification for Process Control and Modelling.- 12.1 Introduction.- 12.2 Quantitative Identification.- 12.3 Intelligent Adaptive Identification.- 12.3.1 Qualitative Identification.- 12.3.2 Intelligent Adaptive Identification.- 12.4 Implementation and Discussion.- 12.5 On-Going Study and Conclusion.- 12.5.1 Real Time Intelligent Control.- 12.5.2 Large-Scale Integrated Intelligent Control.- 12.6 Bibliography.- IV Expert Systems in Robotics and Manufacturing.- 13 Knowledge Based (Expert) Systems for Intelligent Control Applications.- 13.1 Introduction.- 13.2 Knowledge Representation Techniques.- 13.3 Expert Systems in Intelligent Robotics.- 13.4 Expert Systems in Control.- 13.5 Conclusion.- 13.6 Bibliography.- 14 Learning Expert System for Robot Skills.- 14.1 Introduction.- 14.2 EARSA: A Paradigm for Robot Skill Acquisition.- 14.3 Robot Fine Motion Skills.- 14.4 Skill Transfer.- 14.4.1 Encoding of Expert Skills.- 14.4.2 Representation of Robot Skills.- 14.4.3 Interpretation and Operationalization.- 14.5 Robot Self-Learning of Fine Motion Skills.- 14.5.1 Critic and Sample Collection.- 14.5.2 Hypothesis Generation.- 14.5.3 Hypothesis and Rule Monitoring.- 14.6 Simulation.- 14.6.1 Model.- 14.6.2 Test Results.- 14.7 Conclusion.- 14.8 Bibliography.- 15 A Knowledge-Based Mechanical Assembly Planning System.- 15.1 Introduction.- 15.2 Planning and Mechanical Assembly.- 15.3 System Overview.- 15.4 Knowledge Base.- 15.4.1 Workpiece Structures.- 15.4.2 Assembly Principles.- 15.4.3 Assembly Operations.- 15.5 Control Structure.- 15.5.1 Structure Analysis.- 15.5.2 Plan Generation.- 15.6 Conclusion.- 15.7 Bibliography.- 16 Expert Systems in Manufacturing.- 16.1 Introduction.- 16.2 The Importance of Topology.- 16.3 Representation of Shape.- 16.4 Language.- 16.5 Form Features.- 16.6 Extraction of Form Features.- 16.7 Design for Quality.- 16.8 Integration of Structure and Robot.- 16.9 Summary.- 16.10 Bibliography.- 17 Artificial Intelligence Concepts and Petri Nets for Modelling Simulation and Control of Flexible Manufacturing Systems.- 17.1 Introduction.- 17.2 Part I: Petri Net in Manufacturing.- 17.2.1 Illustrative Example: A Flexible Manufacturing System.- 17.2.2 Ordinary Petri Nets (PN).- 17.2.3 Structured Petri Nets (SP-N).- 17.2.4 Petri Net Control Model of the Illustrative Example.- 17.2.5 Conclusion Part I.- 17.3 Part II: A.I. Approach: The Need to Obtain an Efficient Description of the Control Model at High Level of Decision and to Describe the Correct Behaviour of the Process.- 17.3.1 A.I. Modelling of the High Level of Control.- 17.3.2 Object-Oriented Description of the Process Model.- 17.4 Bibliography.- 18 Expert Control Architectures for Production Planning and Control.- 18.1 Introduction.- 18.2 The PP-Problem Statement.- 18.3 The PP-Problem Complexity.- 18.4 The APP-Problem Solution.- 18.4.1 Decomposing the APP-Problem.- 18.4.2 Developing the APP-Strategy.- 18.4.3 Organizing the Hybrid PP-Architecture.- 18.5 Discussing a Simple Example.- 18.6 Analyzing the HPP-Architecture Generality.- 18.7 Bibliography.- 19 Distributed Intelligent Control Systems for an Unmanned Manufacturing Cell.- 19.1 Introduction.- 19.2 Control Algorithm.- 19.2.1 States of Control Algorithm.- 19.2.2 State of Robot.- 19.3 The Intelligent Control System.- 19.3.1 System Components.- 19.3.2 Production Rules.- 19.3.3 Simulation.- 19.4 Conclusion.- 19.5 Bibliography.- V Expert Systems Catalogues.- 20 A Survey of Expert System Tools and Engineering-Based Expert Systems.- 20.1 Introduction.- 20.2 An Overview of Expert System Development Tools.- 20.2.1 General Purpose Programming Languages.- 20.2.2 Expert System Shells.- 20.2.3 Expert System Languages.- 20.2.4 Multiple Paradigm Programming Environments.- 20.2.5 Skeletal Systems.- 20.2.6 Additional Modules.- 20.2.7 A Survey of Expert System Development Tools.- 20.3 A Survey on Engineering-Based Expert Systems.- 20.4 Conclusions.- 20.5 Bibliography.

Product Description

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Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 3642840507
• ISBN 13: 9783642840500
• Rilegatura: Copertina flessibile
• Numero di pagine: 404
• Redattore: Tzafestas Spyros
• Contatto del produttore: non disponibile
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