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Informationen zum Autor Dr. Richard J. Fickelscherer is currently a licensed Professional Engineer and is a principal owner of FALCONEER Technologies, LLC. He has developed and implemented programs which provide various supervisory control functions for DuPont, Exxon-Mobile, Merck Pharmaceuticals, Koch Industries, the FMC Corporation and many other client companies. Dr. Daniel L. Chester joined the Department of Computer and Information Sciences at the University of Delaware in 1980, where he soon became one of the principal investigators on the FALCON project. He is currently Associate Chair in the computer science department at the University of Delaware. He has been involved in the creation and development of three companies, one of which is FALCONEER Technologies, LLC. He is also co-inventor in five U.S. patents. Klappentext Tested and proven strategy to develop optimal automated process fault analyzersProcess fault analyzers monitor process operations in order to identify the underlying causes of operational problems. Several diagnostic strategies exist for automating process fault analysis; however, automated fault analysis is still not widely used within the processing industries due to problems of cost and performance as well as the difficulty of modeling process behavior at needed levels of detail.In response, this book presents the method of minimal evidence (MOME), a model-based diagnostic strategy that facilitates the development and implementation of optimal automated process fault analyzers. MOME was created at the University of Delaware by the researchers who developed the FALCON system, a real-time, online process fault analyzer. The authors demonstrate how MOME is used to diagnose single and multiple fault situations, determine the strategic placement of process sensors, and distribute fault analyzers within large processing systems.Optimal Automated Process Fault Analysis begins by exploring the need to automate process fault analysis. Next, the book examines:* Logic of model-based reasoning as used in MOME* MOME logic for performing single and multiple fault diagnoses* Fuzzy logic algorithms for automating MOME* Distributing process fault analyzers throughout large processing systems* Virtual SPC analysis and its use in FALCONEER(tm) IV* Process state transition logic and its use in FALCONEER(tm) IVThe book concludes with a summary of the lessons learned by employing FALCONEER(tm) IV in actual process applications, including the benefits of "intelligent supervision" of process operations.With this book as their guide, readers have a powerful new tool for ensuring the safety and reliability of any chemical processing system. Zusammenfassung Automated fault analysis is not widely used within chemical processing industries due to problems of cost and performance as well as the difficulty of modeling process behavior at needed levels of detail. Inhaltsverzeichnis Foreword xiii Preface xv Acknowledgments xix 1 Motivations for Automating Process Fault Analysis 1 1.1 Introduction 1 1.2 CPI Trends to Date 1 1.3 The Changing Role of Process Operators in Plant Operations 3 1.4 Methods Currently Used to Perform Process Fault Management 5 1.5 Limitations of Human Operators in Performing Process Fault Management 10 1.6 The Role of Automated Process Fault Analysis 12 1.7 Anticipated Future CPI Trends 13 1.8 Process Fault Analysis Concept Terminology 14 References 16 2 Method of Minimal Evidence: Model-Based Reasoning 21 2.1 Overview 21 2.2 Introduction 22 2.3 Method of Minimal Evidence Overview 23 2.3.1 Process Model and Modeling Assumption Variable Classifications 28 2.3.2 Example of a MOME Primary Model 31 2.3.3 Example of MOME Secondary Models 36 2.3.4 Primary Model Residuals' Normal...
List of contents
Dedication
Table of Contents
Foreword
Preface
Acknowledgements
Chapter 1. Motivations for Automating Process Fault Analysis
1.1 Introduction
1.2 CPI Trends to Date
1.3 The Changing Role for the Process Operators in Plant Operations
1.4 Methods Currently Used to Perform Process Fault Management
1.5 Limitations of Human Operators in Performing Process Fault Management
1.6 The Role of Automated Process Fault Analysis
1.7 Anticipated Future CPI Trends
1.8 Process Fault Analysis Concept Terminology
Chapter 2. Method of Minimal Evidence: Model-Based Reasoning
2.1 Overview
2.2 Introduction
2.3 Method of Minimal Evidence Overview
2.4 Verifying the Validity and Accuracy of the Various Primary Models
2.5 Summary
Chapter 3. Method of Minimal Evidence: Diagnostic Strategy Details
3.1 Overview
3.2 Introduction
3.3 MOME Diagnostic Strategy
3.4 A General Procedure for Developing and Verifying Competent Model-based
3.5 MOME SV & PFA Diagnostic Logic Compiler Motivations
3.6 MOME Diagnostic Strategy Summary
Chapter 4. Method of Minimal Evidence: Fuzzy Logic Algorithm
4.1 Overview
4.2 Introduction
4.3 Fuzzy Logic Overview
4.4 MOME Fuzzy Logic Algorithm
4.5 Certainty Factor Calculation Review
4.6 MOME Fuzzy Logic Algorithm Summary
Chapter 5. Method of Minimal Evidence: Criteria for Shrewdly Distribution Fault Analyzers and Strategic Process Sensor Placement
5.1 Overview
5.2 Criteria for Shrewdly Distributing Process Fault Analyzers
5.3 Criteria for Strategic Process Sensor Placement
Chapter 6. Virtual SPC Analysis and Its Routine Use in Falconeer(TM) IV
6.1 Overview
6.2 Introduction
6.3 EWMA Calculations and Specific Virtual SPC Analysis Configurations
6.4 Virtual SPC Alarm Trigger Summary
6.5 Virtual SPC Analysis Conclusions
Chapter 7. Process State Transistion Logic and Its Routine Use in Falconeer(TM) IV
7.1 Temporal Reasoning Philosophy
7.2 Introduction
7.3 State Identification Analysis Currently Used in Falconeer(TM) IV
7.4 State Identification Analysis Summary
Chapter 8. Conclusions
8.1 Overview
8.2 Summary of the MOME Diagnostic Strategy
8.3 FALCON, FALCONEER and FALCONEER(TM) IV Actual KBS Application Performance Results
8.4 FALCONEER(TM) IV KBS Application Project Procedure
8.5 Optimal Automated Process Fault Analysis Conclusions
Appendix A. Various Diagnostic Strategies for Automating Process Fault Analysis
Appendix B. The Falcon Project
Appendix C. Process State Transition Logic Used by the Original Falconeer KBS
Appendix D. Falconeer(TM) IV Real-Time Suite Process Performance Solutions Demo Description
