Niemi / Jamsa-Jounela Expert Systems in Mineral and Metal Processing

Proceedings of the IFAC Workshop, Espoo, Finland, 26-28 August 1991
1. Auflage 2016
ISBN: 978-1-4832-9829-0
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 220 Seiten, Web PDF

Reihe: IFAC Workshop Series

Within the metal and mining industries, the use of expert systems for monitoring and control is on the increase. The content of each paper had to include both expert systems, neural networks or fuzzy control. The papers were evenly contributed from industry, universities and research institutes, thus this book provides a valuable insight into the theoretical as well as the practical applications currently in use within the industry.

Autoren/Hrsg.

Niemi, A. J.

Jamsa-Jounela, S. L.

Inhaltsverzeichnis

1;Front Cover;1
2;Expert Systems in Mineral and Metal Processing;4
3;Copyright Page
;5
4;Table of Contents;10
5;IFAC WORKSHOP ON EXPERT SYSTEMS INMINERAL AND METAL PROCESSING;6
6;PREFACE;8
7;Opening Address;14
8;Opening Address;16
9;Closing Address;18
10;PART 1: GRINDING AND SEPARATION;20
10.1;CHAPTER 1. AN EXPERT SYSTEM FOR CONTROL OF A SAG/BALL
MILL CIRCUIT;20
10.1.1;INTRODUCTION;20
10.1.2;APPLICATION;21
10.1.3;DEVELOPMENT TOOLS;21
10.1.4;SYSTEM DEVELOPMENT;21
10.1.5;DISCUSSION;23
10.1.6;FURTHER DEVELOPMENTS;24
10.1.7;CONCLUSIONS;25
10.1.8;ACKNOWLEDGMENTS;25
10.1.9;REFERENCES;25
10.2;CHAPTER 2. INTUITIVE PROCESS CONTROL SYSTEMPROGRAMMING;26
10.2.1;INTRODUCTION;26
10.2.2;HARDWARE AND SOFTWARE;26
10.2.3;THE REAGENT CONTROL PROBLEM;27
10.2.4;CONVENTIONAL CONTROL;27
10.2.5;THE INTUITIVE ALTERNATIVE;28
10.2.6;COUPLING OF G2 AND THE DCS;28
10.2.7;CASE STUDY;29
10.2.8;ECONOMIC BENEFITS;29
10.2.9;CONCLUSIONS;29
10.2.10;REFERENCES;29
10.3;CHAPTER 3. THE CONTROL OF MINERAL PROCESSING PLANTSUSING NEURAL NETWORK TECHNIQUES;32
10.3.1;INTRODUCTION;32
10.3.2;CONTROL OF A HYDROCYCLONE CLASSIFIER;32
10.3.3;CONTROL OF AN ADSORPTION PROCESS;35
10.3.4;CONCLUSIONS;36
10.3.5;REFERENCES;37
10.4;CHAPTER 4. AUTOMATION EXPERT SYSTEM FOR AIR SEPARATIONPLANT;38
10.4.1;INTRODUCTION;38
10.4.2;CHARACTERISTICS OF AIR SEPARATION PLANT;40
10.4.3;AUTOMATION MEANS;41
10.4.4;EVALUATION OF AUTOMATION SYSTEM;43
10.4.5;CONCLUSION;43
10.4.6;REFERENCES;43
10.5;CHAPTER 5. MODELLING AND CONTROL OF MINERAL PROCESSINGPLANTS USING NEURAL NETWORKS;44
10.5.1;INTRODUCTION;44
10.5.2;THE GRINDING DYNAMIC SIMULATOR;44
10.5.3;NEURAL BASED CONTROL STRATEGIES;46
10.5.4;ILLUSTRATIONS AND DISCUSSION;47
10.5.5;CONCLUSION;49
10.5.6;REFERENCES;49
11;PART 2: IRON- AND STEELMAKING;50
11.1;CHAPTER 6. CONTROL OF ELECTRIC ENERGY CONSUMPTION INSTEEL INDUSTRY USING KNOWLEDGE BASEDTECHNIQUES;50
11.1.1;INTRODUCTION;50
11.1.2;ORGANIZATIONAL ASPECTS;51
11.1.3;PROCESSES;51
11.1.4;MODELLING AND PREDICTION;51
11.1.5;DECISION MAKING IN THEPROTOTYPE;52
11.1.6;INTERFACES;52
11.1.7;RESULTS;52
11.1.8;EXPERIENCE AND FUTURECHALLENGES;53
11.1.9;CONCLUSIONS;54
11.1.10;ACKNOWLEDGEMENTS;54
11.1.11;REFERENCES;54
11.2;CHAPTER 7. DEVELOPMENT OF A SCHEDULING EXPERT SYSTEMFOR A STEELPLANT;58
11.2.1;THE SCHEDULING PROBLEMIN STEELMAKING;58
11.2.2;INITIAL PROTOTYPES;60
11.2.3;THE CURRENT SYSTEM - VASE;61
11.2.4;LESSONS LEARNED;62
11.2.5;FUTURE DEVELOPMENT;63
11.2.6;CONCLUSIONS;63
11.2.7;ACKNOWLEDGEMENTS;63
11.3;CHAPTER 8. AN EXPERT SYSTEM TO AID OPERATION OF BLASTFURNACE;64
11.3.1;INTRODUCTION;64
11.3.2;STRUCTURE OF THE EXPERT SYSTEM;65
11.3.3;DATA PROCESSING;65
11.3.4;CONSTRUCTION AND FEATURES OFTHE KNOWLEDGE BASE;65
11.3.5;DIAGNOSIS OF THE FORMATION OF INACTIVEZONE AT THE LOWER PART OF THE FURNACE;66
11.3.6;DIAGNOSIS OF THE UNSTABLE CONDITIONSOF THE INNER FURNACE GAS FLOW;66
11.3.7;RESULTS OF THE APPLICATION ON A REALBLAST FURNACE;66
11.3.8;CONCLUSION;68
11.3.9;REFERENCES;68
11.4;CHAPTER 9. A HYBRID EXPERT SYSTEM COMBINED WITH AMATHEMATICAL MODEL FOR BOF PROCESS CONTROL;70
11.4.1;INTRODUCTION;70
11.4.2;OUTLINE OF BOF BLOWING PROCESSAND BLOWING CONTROL SYSTEM;70
11.4.3;SYSTEM CONFIGURATION;72
11.4.4;THE NEWLY DEVELOPED BLOWINGCONTROL SYSTEM;72
11.4.5;APPLICATION RESULTSIN ACTUAL OPERATION;74
11.4.6;CONCLUSION;75
11.4.7;REFERENCES;75
11.5;CHAPTER 10. KNOWLEDGE BASED MODEL OF THERMAL STATE OFMETALLURGICAL LADLE;76
11.5.1;INTRODUCTION;76
11.5.2;MATHEMATICAL MODEL OF AMETALLURGICAL LADLE;77
11.5.3;BASIC CONCEPTS;78
11.5.4;DECISION MAKING LOGIC;78
11.5.5;DEFUZZYFIER;79
11.5.6;FUZZY MODEL OF MEAN INTEGRAL TEMPERATURE;79
11.5.7;FUZZY MODEL OF THE INITIA LTHERMAL STATE OF THE LADLE;79
11.5.8;SIMULATION RESULTS;80
11.5.9;CONCLUSIONS;80
11.5.10;REFERENCES;80
11.6;CHAPTER 11. APPLICATION OF EXPERT SYSTEM TO REAL TIMECOLD COIL TRANSPORTATION CONTROL INFINISHING LINE;82
11.6.1;INTRODUCTION;82
11.6.2;BACKGROUND TO THE DEVELOPMENTOF THE EXPERT SYSTEM;82
11.6.3;SYSTEM CONFIGURATION;83
11.6.4;OUTLINE OF THE EXPERT SYSTEM;84
11.6.5;RESULTS OF APPLYINGTHE EXPERT SYSTEM;85
11.6.6;CONCLUSION;86
11.6.7;REFERENCES;86
11.7;CHAPTER 12. EXPERT SYSTEM FOR MANUFACTURING ORDERDETERMINATION IN HOT-ROLLING PROCESS;90
11.7.1;INTRODUCTION;90
11.7.2;OUTLINE OF SEAMLESS PIPEROLLING SEQUENCE COMPOSITION;90
11.7.3;OVERVIEW OF THE SYSTEM;92
11.7.4;METHOD OF DISSOLVINGPROBLEMS INVOLVED INSEQUENCE COMPOSITION;93
11.7.5;EVALUATION;95
11.7.6;CONCLUSION;96
11.7.7;REFERENCES;96
11.8;CHAPTER 13. EXPERT SYSTEMS FOR THE AUTOMATIC SURFACEINSPECTION OF STEEL STRIP;98
11.8.1;INTRODUCTION;98
11.8.2;RULE-BASED CLASSIFICATION SYSTEM;99
11.8.3;KNOWLEDGE EXTRACTION METHODS;100
11.8.4;GENERATION OF RULE BASEDCLASSIFIERS;101
11.8.5;A NEURAL NETWORK CLASSIFIER;102
11.8.6;CONCLUSIONS;102
11.8.7;REFERENCES;102
11.9;CHAPTER 14. COIL TRANSFER EXPERT SYSTEM FOR A HOT STRIPMILL FINISHING LINE;108
11.9.1;INTRODUCTION;108
11.9.2;DEVELOPMENTAL OBJECTIVES;108
11.9.3;BACKGROUND BEHIND THE INTRODUCTION OFKNOWLEDGE ENGINEERING;108
11.9.4;OUTLINE OF CONTROL SYSTEM;109
11.9.5;EXPERT SYSTEM;110
11.9.6;BENEFITS;113
11.9.7;CONCLUSION;113
11.9.8;REFERENCES;113
11.10;CHAPTER 15. KNOWLEDGE ENGINEERING AN EXPERT SYSTEM TOTROUBLE-SHOOT QUALITY PROBLEMS IN THECONTINUOUS CASTING OF STEEL BILLETS;114
11.10.1;ABSTRACT;114
11.10.2;INTRODUCTION;114
11.10.3;KNOWLEDGE DOMAIN;114
11.10.4;KNOWLEDGE ACQUISITION;115
11.10.5;KNOWLEDGE REPRESENTATION;117
11.10.6;STRUCTURE OF THE EXPERT SYSTEM;118
11.10.7;EVALUATION OF THE EXPERT SYSTEM;119
11.10.8;REFINEMENT OF DOMAIN KNOWLEDGE;119
11.10.9;SUMMARY;119
11.10.10;ACKNOWLEDGEMENTS;119
11.10.11;REFERENCES;120
11.10.12;APPENDIX : QUALITY PROBLEMS IN BILLET CASTING;120
11.11;CHAPTER 16. APPLYING KNOWLEDGE-BASED TECHNIQUES TO THESCHEDULING OF STEEL ROLLING;122
11.11.1;1. INTRODUCTION;122
11.11.2;2. STEEL MANUFACTURING PROCESS;122
11.11.3;3. PLATE-MILL SCHEDULER;124
11.11.4;4. SCHEDULING METHOD;125
11.11.5;5. DISCUSSION;126
11.11.6;REFERENCES;127
12;PART 3 : GENERAL APPLICATIONS;128
12.1;CHAPTER 17. EXPERT SYSTEM FOR COAL BLENDING;128
12.1.1;PREFACE;128
12.1.2;DEFINITION OF THE SYSTEM AND ITS AIMS;128
12.1.3;OUTLINE OF THE SYSTEM AND ITS FEATURES;129
12.1.4;PROCESS OF KNOWLEDGE ACQUISITION;131
12.1.5;STUDY ON THE USE OF NUMERICALDESIGN METHODS;132
12.1.6;EVALUATION;133
12.1.7;CONCLUSIONS;133
12.1.8;ACKNOWLEDGMENTS;133
12.2;CHAPTER 18. A DATA BASED EXPERT SYSTEM FOR ENGINEERINGAPPLICATIONS;134
12.2.1;INTRODUCTION;134
12.2.2;CATEGORISATION OF A TRAINING DATA SET;134
12.2.3;CHARACTERISTICS OF THE CLUSTERINGTECHNIQUE;135
12.2.4;CLASSIFICATION OF DATA;136
12.2.5;CLUSTER VERIFICATION USINGCLASSIFICATION;136
12.2.6;SYSTEM SUITABILITY FOR A PARTICULAR
APPLICATION;137
12.2.7;CONCLUSIONS;137
12.2.8;REFERENCES;137
12.3;CHAPTER 19. ADAPTIVE EXPERT SYSTEMS FOR METALLURGICALPROCESSES;138
12.3.1;INTRODUCTION;138
12.3.2;MULTILAYER SIMULATION;139
12.3.3;ADAPTIVE EXPERT SYSTEMS;142
12.3.4;MULTILEVEL CONTROL;143
12.3.5;CONCLUSIONS;143
12.3.6;REFERENCES;143
12.4;CHAPTER 20. KNOWLEDGE BASED SIMULATION AND IDENTIFICATION OF METALLURGICAL REACTORS;144
12.4.1;INTRODUCTION;144
12.4.2;KNOWLEDGE BASED MODEL;145
12.4.3;VALIDATION OF THE KNOWLEDGE BASED MODEL;146
12.4.4;FAULT DIAGNOSIS;148
12.4.5;DISCUSSION AND SIGNIFICANCE;149
12.4.6;REFERENCES;149
12.5;CHAPTER 21. SELF ORGANIZING CONTROL OF pH IN A STIRREDTANK REACTOR;150
12.5.1;INTRODUCTION;150
12.5.2;THEORETICAL BACKGROUND;150
12.5.3;THE pH CONTROL PROBLEM;152
12.5.4;EXPERIMENTAL SET-UP;153
12.5.5;RESULTS;153
12.5.6;CONCLUSIONS;155
12.5.7;REFERENCES;155
12.6;CHAPTER 22. OSTECH (Ornamental Stone TExtural CHaracterization):A Structure of Expert System to Evaluate and Describe Numerically the Textural and Structural Features of Ornamental Stone Slabs;158
12.6.1;INTRODUCTION;158
12.6.2;ROCK SAMPLE AS SOURCE OFINFORMATION;159
12.6.3;DIGITAL IMAGES HANDLING,MANIPULATION AND ANALYSIS;159
12.6.4;ALGORITHMS ANALYSISAND DEFINITION;161
12.6.5;EXPERIMENTAL AND DISCUSSION;161
12.6.6;REFERENCES;165
13;PART 4: NEW METHODS;166
13.1;CHAPTER 23. NEURAL NETWORK MODEL FOR RECOGNITION OFCHARACTERS STENCILED ON SLABS;166
13.1.1;INTRODUCTION;166
13.1.2;QUALITY EVALUATION OFTHE CHARACTERS;166
13.1.3;PATTERN RECOGNITION USINGA MULTILAYER NEURAL NETWORK MODEL;167
13.1.4;APPLICATION OF THE NEURAL NETWORKMODEL TO THE SYSTEM;167
13.1.5;CAPABILITY OF THE NEURAL NETWORK;168
13.1.6;SYSTEM CONFIGURATION;168
13.1.7;EXPERIMENTAL RESULTS;169
13.1.8;CONCLUSION;169
13.1.9;REFERENCES;169
13.2;CHAPTER 24. AN EXPERT SYSTEM FOR CONTINUOUS STEELCASTING USING NEURAL NETWORKS;174
13.2.1;1. Introduction;174
13.2.2;2. Continuous steel casting;174
13.2.3;3. The network and its training;175
13.2.4;4. The knowledge base;176
13.2.5;5. Results;176
13.2.6;6. Conclusions;178
13.2.7;Acknowledgements;178
13.2.8;References;178
13.3;CHAPTER 25. NEURAL NETWORKS FOR STEADY-STATE PROCESS MODELLING AND FAULT DIAGNOSIS;180
13.3.1;ABSTRAC;180
13.3.2;KEYWORDS;180
13.3.3;INTRODUCTION;180
13.3.4;EVALUATION;181
13.3.5;DISCUSSION;182
13.3.6;REFERENCES;182
13.4;CHAPTER 26. MINERAL PROCESS CONTROL BY NEURAL NETWORK;186
13.4.1;INTRODUCTION;186
13.4.2;NEURAL NETWORK;186
13.4.3;OPTIMIZATIONOF THE ANN CONTROLLER;188
13.4.4;SYSTEM COMPOSITION;188
13.4.5;SIMULATION;189
13.4.6;DISCUSSION;189
13.4.7;CONCLUSION;190
13.4.8;ACKNOWLEDGEMENT;190
13.4.9;References;190
13.5;CHAPTER 27. PROGNOS: A PROTOTYPE EXPERT SYSTEM FOR FAULT DIAGNOSIS OF THE TRANSMISSION SYSTEM OF LOAD-HAUL-DUMP VEHICLES IN KIRUNA MINE,LKAB, SWEDEN;192
13.5.1;INTRODUCTION;192
13.5.2;FAULT DIAGNOSIS OF MINING EQUIPMENT;192
13.5.3;PROBLEM APPROACH;194
13.5.4;KNOWLEDGE ACQUISITION;194
13.5.5;SOFTWARE IMPLEMENTATION;194
13.5.6;CONCLUSION;195
13.5.7;ACKNOWLEDGEMENTS;195
13.5.8;REFERENCES;195
13.6;CHAPTER 28. THE SIMULATION OF ILL-DEFINED METALLURGICALPROCESSES USING A NEURAL NET TRAINING PROGRAM BASED ON CONJUGATE-GRADIENT OPTIMIZATION;198
13.6.1;INTRODUCTION;198
13.6.2;DIRECT MODELLING OF ACONTINUOUS REACTOR;199
13.6.3;NEURAL NETS;199
13.6.4;MODELLING A TYPICALMETALLURGICAL PROCESS;200
13.6.5;CONCLUSIONS;203
13.6.6;REFERENCES;203
13.6.7;LIST OF SYMBOLS;203
14;PART 5: PLENARY PAPERS;204
14.1;CHAPTER 29. REQUIREMENTS AND TECHNOLOGIES FOR OPERATIONS MANAGEMENT DECISION SUPPORT;204
14.1.1;INTRODUCTION;204
14.1.2;2.0 GENERAL DSS REQUIREMENTS;204
14.1.3;3.0 BRIEF REVIEW OF SUPPORTING TECHNOLOGIESAND APPLICATIONS;205
14.1.4;4.0 DSS ARCHITECTURES/LANGUAGES;207
14.1.5;5.0 RECOMMENDATIONS;208
14.1.6;6.0 REFERENCES;208
14.2;CHAPTER 30. APPLICATION VIEWPOINTS OF EXPERT SYSTEMS INMINERAL AND METAL PROCESSING;210
14.2.1;1. INTRODUCTION;210
14.2.2;2. EXPERT SYSTEMS IN PROCESS CONTROL;210
14.2.3;3. OTHER APPLICATIONS;212
14.2.4;4. ADVANTAGES;213
14.2.5;5. PROBLEMS;214
14.2.6;6. REFERENCES;214
15;AUTHOR INDEX;216