Expert Systems in Mineral and Metal Processing (eBook)

Proceedings of the IFAC Workshop, Espoo, Finland, 26-28 August 1991

S.L. Jamsa-Jounela, A. J. Niemi (Herausgeber)

eBook Download: PDF

2016 | 1. Auflage
220 Seiten
Elsevier Science (Verlag)
978-1-4832-9829-0 (ISBN)

Infos

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.

Inhalt

Front Cover 1
Expert Systems in Mineral and Metal Processing 4
Copyright Page 
5 
Table of Contents 10
IFAC WORKSHOP ON EXPERT SYSTEMS INMINERAL AND METAL PROCESSING 6
PREFACE 8
Opening Address 14
Opening Address 16
Closing Address 18
PART 1: GRINDING AND SEPARATION 20
CHAPTER 1. AN EXPERT SYSTEM FOR CONTROL OF A SAG/BALL 
20 
INTRODUCTION 20
APPLICATION 21
DEVELOPMENT TOOLS 21
SYSTEM DEVELOPMENT 21
DISCUSSION 23
FURTHER DEVELOPMENTS 24
CONCLUSIONS 25
ACKNOWLEDGMENTS 25
REFERENCES 25
CHAPTER 2. INTUITIVE PROCESS CONTROL SYSTEMPROGRAMMING 26
INTRODUCTION 26
HARDWARE AND SOFTWARE 26
THE REAGENT CONTROL PROBLEM 27
CONVENTIONAL CONTROL 27
THE INTUITIVE ALTERNATIVE 28
COUPLING OF G2 AND THE DCS 28
CASE STUDY 29
ECONOMIC BENEFITS 29
CONCLUSIONS 29
REFERENCES 29
CHAPTER 3. THE CONTROL OF MINERAL PROCESSING PLANTSUSING NEURAL NETWORK TECHNIQUES 32
INTRODUCTION 32
CONTROL OF A HYDROCYCLONE CLASSIFIER 32
CONTROL OF AN ADSORPTION PROCESS 35
CONCLUSIONS 36
REFERENCES 37
CHAPTER 4. AUTOMATION EXPERT SYSTEM FOR AIR SEPARATIONPLANT 38
INTRODUCTION 38
CHARACTERISTICS OF AIR SEPARATION PLANT 40
AUTOMATION MEANS 41
EVALUATION OF AUTOMATION SYSTEM 43
CONCLUSION 43
REFERENCES 43
CHAPTER 5. MODELLING AND CONTROL OF MINERAL PROCESSINGPLANTS USING NEURAL NETWORKS 44
INTRODUCTION 44
THE GRINDING DYNAMIC SIMULATOR 44
NEURAL BASED CONTROL STRATEGIES 46
ILLUSTRATIONS AND DISCUSSION 47
CONCLUSION 49
REFERENCES 49
PART 2: IRON- AND STEELMAKING 50
CHAPTER 6. CONTROL OF ELECTRIC ENERGY CONSUMPTION INSTEEL INDUSTRY USING KNOWLEDGE BASEDTECHNIQUES 50
INTRODUCTION 50
ORGANIZATIONAL ASPECTS 51
PROCESSES 51
MODELLING AND PREDICTION 51
DECISION MAKING IN THEPROTOTYPE 52
INTERFACES 52
RESULTS 52
EXPERIENCE AND FUTURECHALLENGES 53
CONCLUSIONS 54
ACKNOWLEDGEMENTS 54
REFERENCES 54
CHAPTER 7. DEVELOPMENT OF A SCHEDULING EXPERT SYSTEMFOR A STEELPLANT 58
THE SCHEDULING PROBLEMIN STEELMAKING 58
INITIAL PROTOTYPES 60
THE CURRENT SYSTEM - VASE 61
LESSONS LEARNED 62
FUTURE DEVELOPMENT 63
CONCLUSIONS 63
ACKNOWLEDGEMENTS 63
CHAPTER 8. AN EXPERT SYSTEM TO AID OPERATION OF BLASTFURNACE 64
INTRODUCTION 64
STRUCTURE OF THE EXPERT SYSTEM 65
DATA PROCESSING 65
CONSTRUCTION AND FEATURES OFTHE KNOWLEDGE BASE 65
DIAGNOSIS OF THE FORMATION OF INACTIVEZONE AT THE LOWER PART OF THE FURNACE 66
DIAGNOSIS OF THE UNSTABLE CONDITIONSOF THE INNER FURNACE GAS FLOW 66
RESULTS OF THE APPLICATION ON A REALBLAST FURNACE 66
CONCLUSION 68
REFERENCES 68
CHAPTER 9. A HYBRID EXPERT SYSTEM COMBINED WITH AMATHEMATICAL MODEL FOR BOF PROCESS CONTROL 70
INTRODUCTION 70
OUTLINE OF BOF BLOWING PROCESSAND BLOWING CONTROL SYSTEM 70
SYSTEM CONFIGURATION 72
THE NEWLY DEVELOPED BLOWINGCONTROL SYSTEM 72
APPLICATION RESULTSIN ACTUAL OPERATION 74
CONCLUSION 75
REFERENCES 75
CHAPTER 10. KNOWLEDGE BASED MODEL OF THERMAL STATE OFMETALLURGICAL LADLE 76
INTRODUCTION 76
MATHEMATICAL MODEL OF AMETALLURGICAL LADLE 77
BASIC CONCEPTS 78
DECISION MAKING LOGIC 78
DEFUZZYFIER 79
FUZZY MODEL OF MEAN INTEGRAL TEMPERATURE 79
FUZZY MODEL OF THE INITIA LTHERMAL STATE OF THE LADLE 79
SIMULATION RESULTS 80
CONCLUSIONS 80
REFERENCES 80
CHAPTER 11. APPLICATION OF EXPERT SYSTEM TO REAL TIMECOLD COIL TRANSPORTATION CONTROL INFINISHING LINE 82
INTRODUCTION 82
BACKGROUND TO THE DEVELOPMENTOF THE EXPERT SYSTEM 82
SYSTEM CONFIGURATION 83
OUTLINE OF THE EXPERT SYSTEM 84
RESULTS OF APPLYINGTHE EXPERT SYSTEM 85
CONCLUSION 86
REFERENCES 86
CHAPTER 12. EXPERT SYSTEM FOR MANUFACTURING ORDERDETERMINATION IN HOT-ROLLING PROCESS 90
INTRODUCTION 90
OUTLINE OF SEAMLESS PIPEROLLING SEQUENCE COMPOSITION 90
OVERVIEW OF THE SYSTEM 92
METHOD OF DISSOLVINGPROBLEMS INVOLVED INSEQUENCE COMPOSITION 93
EVALUATION 95
CONCLUSION 96
REFERENCES 96
CHAPTER 13. EXPERT SYSTEMS FOR THE AUTOMATIC SURFACEINSPECTION OF STEEL STRIP 98
INTRODUCTION 98
RULE-BASED CLASSIFICATION SYSTEM 99
KNOWLEDGE EXTRACTION METHODS 100
GENERATION OF RULE BASEDCLASSIFIERS 101
A NEURAL NETWORK CLASSIFIER 102
CONCLUSIONS 102
REFERENCES 102
CHAPTER 14. COIL TRANSFER EXPERT SYSTEM FOR A HOT STRIPMILL FINISHING LINE 108
INTRODUCTION 108
DEVELOPMENTAL OBJECTIVES 108
BACKGROUND BEHIND THE INTRODUCTION OFKNOWLEDGE ENGINEERING 108
OUTLINE OF CONTROL SYSTEM 109
EXPERT SYSTEM 110
BENEFITS 113
CONCLUSION 113
REFERENCES 113
CHAPTER 15. KNOWLEDGE ENGINEERING AN EXPERT SYSTEM TOTROUBLE-SHOOT QUALITY PROBLEMS IN THECONTINUOUS CASTING OF STEEL BILLETS 114
ABSTRACT 114
INTRODUCTION 114
KNOWLEDGE DOMAIN 114
KNOWLEDGE ACQUISITION 115
KNOWLEDGE REPRESENTATION 117
STRUCTURE OF THE EXPERT SYSTEM 118
EVALUATION OF THE EXPERT SYSTEM 119
REFINEMENT OF DOMAIN KNOWLEDGE 119
SUMMARY 119
ACKNOWLEDGEMENTS 119
REFERENCES 120
APPENDIX : QUALITY PROBLEMS IN BILLET CASTING 120
CHAPTER 16. APPLYING KNOWLEDGE-BASED TECHNIQUES TO THESCHEDULING OF STEEL ROLLING 122
1. INTRODUCTION 122
2. STEEL MANUFACTURING PROCESS 122
3. PLATE-MILL SCHEDULER 124
4. SCHEDULING METHOD 125
5. DISCUSSION 126
REFERENCES 127
PART 3 : GENERAL APPLICATIONS 128
CHAPTER 17. EXPERT SYSTEM FOR COAL BLENDING 128
PREFACE 128
DEFINITION OF THE SYSTEM AND ITS AIMS 128
OUTLINE OF THE SYSTEM AND ITS FEATURES 129
PROCESS OF KNOWLEDGE ACQUISITION 131
STUDY ON THE USE OF NUMERICALDESIGN METHODS 132
EVALUATION 133
CONCLUSIONS 133
ACKNOWLEDGMENTS 133
CHAPTER 18. A DATA BASED EXPERT SYSTEM FOR ENGINEERINGAPPLICATIONS 134
INTRODUCTION 134
CATEGORISATION OF A TRAINING DATA SET 134
CHARACTERISTICS OF THE CLUSTERINGTECHNIQUE 135
CLASSIFICATION OF DATA 136
CLUSTER VERIFICATION USINGCLASSIFICATION 136
SYSTEM SUITABILITY FOR A PARTICULAR 
137 
CONCLUSIONS 137
REFERENCES 137
CHAPTER 19. ADAPTIVE EXPERT SYSTEMS FOR METALLURGICALPROCESSES 138
INTRODUCTION 138
MULTILAYER SIMULATION 139
ADAPTIVE EXPERT SYSTEMS 142
MULTILEVEL CONTROL 143
CONCLUSIONS 143
REFERENCES 143
CHAPTER 20. KNOWLEDGE BASED SIMULATION AND IDENTIFICATION OF METALLURGICAL REACTORS 144
INTRODUCTION 144
KNOWLEDGE BASED MODEL 145
VALIDATION OF THE KNOWLEDGE BASED MODEL 146
FAULT DIAGNOSIS 148
DISCUSSION AND SIGNIFICANCE 149
REFERENCES 149
CHAPTER 21. SELF ORGANIZING CONTROL OF pH IN A STIRREDTANK REACTOR 150
INTRODUCTION 150
THEORETICAL BACKGROUND 150
THE pH CONTROL PROBLEM 152
EXPERIMENTAL SET-UP 153
RESULTS 153
CONCLUSIONS 155
REFERENCES 155
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
INTRODUCTION 158
ROCK SAMPLE AS SOURCE OFINFORMATION 159
DIGITAL IMAGES HANDLING,MANIPULATION AND ANALYSIS 159
ALGORITHMS ANALYSISAND DEFINITION 161
EXPERIMENTAL AND DISCUSSION 161
REFERENCES 165
PART 4: NEW METHODS 166
CHAPTER 23. NEURAL NETWORK MODEL FOR RECOGNITION OFCHARACTERS STENCILED ON SLABS 166
INTRODUCTION 166
QUALITY EVALUATION OFTHE CHARACTERS 166
PATTERN RECOGNITION USINGA MULTILAYER NEURAL NETWORK MODEL 167
APPLICATION OF THE NEURAL NETWORKMODEL TO THE SYSTEM 167
CAPABILITY OF THE NEURAL NETWORK 168
SYSTEM CONFIGURATION 168
EXPERIMENTAL RESULTS 169
CONCLUSION 169
REFERENCES 169
CHAPTER 24. AN EXPERT SYSTEM FOR CONTINUOUS STEELCASTING USING NEURAL NETWORKS 174
1. Introduction 174
2. Continuous steel casting 174
3. The network and its training 175
4. The knowledge base 176
5. Results 176
6. Conclusions 178
Acknowledgements 178
References 178
CHAPTER 25. NEURAL NETWORKS FOR STEADY-STATE PROCESS MODELLING AND FAULT DIAGNOSIS 180
ABSTRAC 180
KEYWORDS 180
INTRODUCTION 180
EVALUATION 181
DISCUSSION 182
REFERENCES 182
CHAPTER 26. MINERAL PROCESS CONTROL BY NEURAL NETWORK 186
INTRODUCTION 186
NEURAL NETWORK 186
OPTIMIZATIONOF THE ANN CONTROLLER 188
SYSTEM COMPOSITION 188
SIMULATION 189
DISCUSSION 189
CONCLUSION 190
ACKNOWLEDGEMENT 190
References 190
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
INTRODUCTION 192
FAULT DIAGNOSIS OF MINING EQUIPMENT 192
PROBLEM APPROACH 194
KNOWLEDGE ACQUISITION 194
SOFTWARE IMPLEMENTATION 194
CONCLUSION 195
ACKNOWLEDGEMENTS 195
REFERENCES 195
CHAPTER 28. THE SIMULATION OF ILL-DEFINED METALLURGICALPROCESSES USING A NEURAL NET TRAINING PROGRAM BASED ON CONJUGATE-GRADIENT OPTIMIZATION 198
INTRODUCTION 198
DIRECT MODELLING OF ACONTINUOUS REACTOR 199
NEURAL NETS 199
MODELLING A TYPICALMETALLURGICAL PROCESS 200
CONCLUSIONS 203
REFERENCES 203
LIST OF SYMBOLS 203
PART 5: PLENARY PAPERS 204
CHAPTER 29. REQUIREMENTS AND TECHNOLOGIES FOR OPERATIONS MANAGEMENT DECISION SUPPORT 204
INTRODUCTION 204
2.0 GENERAL DSS REQUIREMENTS 204
3.0 BRIEF REVIEW OF SUPPORTING TECHNOLOGIESAND APPLICATIONS 205
4.0 DSS ARCHITECTURES/LANGUAGES 207
5.0 RECOMMENDATIONS 208
6.0 REFERENCES 208
CHAPTER 30. APPLICATION VIEWPOINTS OF EXPERT SYSTEMS INMINERAL AND METAL PROCESSING 210
1. INTRODUCTION 210
2. EXPERT SYSTEMS IN PROCESS CONTROL 210
3. OTHER APPLICATIONS 212
4. ADVANTAGES 213
5. PROBLEMS 214
6. REFERENCES 214
AUTHOR INDEX 216

Produkt-Details

• Erscheint lt. Verlag: 1.9.2016
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Maschinenbau
• ISBN-10: 1-4832-9829-9 / 1483298299
• ISBN-13: 978-1-4832-9829-0 / 9781483298290