Artificial neural networks for the modelling and fault diagnosis of technical processes:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2008
|
| Series: | Lecture notes in control and information sciences
377 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. [191] - 202 |
| Physical Description: | XXII, 206 S. Ill., graph. Darst. 24 cm |
| ISBN: | 9783540798712 |
Staff View
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Record in the Search Index
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| adam_text | CONTENTS 1 INTRODUCTION 1 1.1 ORGANIZATION OF THE BOOK 3 2 MODELLING
ISSUE IN FAULT DIAGNOSIS 7 2.1 PROBLEM OF FAULT DETECTION AND FAULT
DIAGNOSIS 8 2.2 MODELS USED IN FAULT DIAGNOSIS 11 2.2.1 PARAMETER
ESTIMATION 12 2.2.2 PARITY RELATIONS 12 2.2.3 OBSERVERS 13 2.2.4 NEURAL
NETWORKS 14 2.2.5 FUZZY LOGIC 15 2.3 NEURAL NETWORKS IN FAULT DIAGNOSIS
16 2.3.1 MULTI-LAYER FEEDFORWARD NETWORKS 16 2.3.2 RADIAL BASIS FUNCTION
NETWORK 18 2.3.3 KOHONEN NETWORK 20 2.3.4 MODEL BASED APPROACHES 21
2.3.5 KNOWLEDGE BASED APPROACHES 23 2.3.6 DATA ANALYSIS APPROACHES 23
2.4 EVALUATION OF THE FDI SYSTEM 24 2.5 SUMMARY 26 3 LOCALLY RECURRENT
NEURAL NETWORKS 29 3.1 NEURAL NETWORKS WITH EXTERNAL DYNAMICS 30 3.2
FULLY RECURRENT NETWORKS 31 3.3 PARTIALLY RECURRENT NETWORKS 32 3.4
STATE-SPACE NETWORKS 34 3.5 LOCALLY RECURRENT NETWORKS 36 3.5.1 MODEL
WITH THE IIR FILTER 40 3.5.2 ANALYSIS OF EQUILIBRIUM POINTS 43 3.5.3
CONTROLLABILITY AND OBSERVABILITY 47 3.5.4 DYNAMIC NEURAL NETWORK 49 3.6
TRAINING OF THE NETWORK 52 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/988160463 DIGITALISIERT DURCH * * CONTENTS XIII 7.2.2
DENSITY ESTIMATION 127 7.2.3 THRESHOLD CALCULATING - A SINGLE NEURON 130
7.2.4 THRESHOLD CALCULATING - A TWO-LAYER NETWORK 131 7.3 ROBUST FAULT
DIAGNOSIS 132 7.3.1 ADAPTIVE THRESHOLDS 133 7.3.2 FUZZY THRESHOLD
ADAPTATION 135 7.3.3 MODEL ERROR MODELLING 137 7.4 SUMMARY 140 8
INDUSTRIAL APPLICATIONS 141 8.1 SUGAR FACTORY FAULT DIAGNOSIS 141 8.1.1
INSTRUMENTATION FAULTS 143 8.1.2 ACTUATOR FAULTS 143 8.1.3 EXPERIMENTS
146 8.1.4 FINAL REMARKS 160 8.2 FLUID CATALYTIC CRACKING FAULT DETECTION
161 8.2.1 PROCESS MODELLING 163 8.2.2 FAULTY SCENARIOS 164 8.2.3 FAULT
DIAGNOSIS 164 8.2.4 ROBUST FAULT DIAGNOSIS 168 8.2.5 FINAL REMARKS 172
8.3 DC MOTOR FAULT DIAGNOSIS 172 8.3.1 AMIRA DR300 LABORATORY SYSTEM 173
8.3.2 MOTOR MODELLING 176 8.3.3 FAULT DIAGNOSIS USING DENSITY SHAPING
176 8.3.4 ROBUST FAULT DIAGNOSIS 181 8.3.5 FINAL REMARKS 182 9
CONCLUDING REMARKS AND FURTHER RESEARCH DIRECTIONS 187 REFERENCES 191
INDEX 203
|
| adam_txt |
CONTENTS 1 INTRODUCTION 1 1.1 ORGANIZATION OF THE BOOK 3 2 MODELLING
ISSUE IN FAULT DIAGNOSIS 7 2.1 PROBLEM OF FAULT DETECTION AND FAULT
DIAGNOSIS 8 2.2 MODELS USED IN FAULT DIAGNOSIS 11 2.2.1 PARAMETER
ESTIMATION 12 2.2.2 PARITY RELATIONS 12 2.2.3 OBSERVERS 13 2.2.4 NEURAL
NETWORKS 14 2.2.5 FUZZY LOGIC 15 2.3 NEURAL NETWORKS IN FAULT DIAGNOSIS
16 2.3.1 MULTI-LAYER FEEDFORWARD NETWORKS 16 2.3.2 RADIAL BASIS FUNCTION
NETWORK 18 2.3.3 KOHONEN NETWORK 20 2.3.4 MODEL BASED APPROACHES 21
2.3.5 KNOWLEDGE BASED APPROACHES 23 2.3.6 DATA ANALYSIS APPROACHES 23
2.4 EVALUATION OF THE FDI SYSTEM 24 2.5 SUMMARY 26 3 LOCALLY RECURRENT
NEURAL NETWORKS 29 3.1 NEURAL NETWORKS WITH EXTERNAL DYNAMICS 30 3.2
FULLY RECURRENT NETWORKS 31 3.3 PARTIALLY RECURRENT NETWORKS 32 3.4
STATE-SPACE NETWORKS 34 3.5 LOCALLY RECURRENT NETWORKS 36 3.5.1 MODEL
WITH THE IIR FILTER 40 3.5.2 ANALYSIS OF EQUILIBRIUM POINTS 43 3.5.3
CONTROLLABILITY AND OBSERVABILITY 47 3.5.4 DYNAMIC NEURAL NETWORK 49 3.6
TRAINING OF THE NETWORK 52 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/988160463 DIGITALISIERT DURCH * * CONTENTS XIII 7.2.2
DENSITY ESTIMATION 127 7.2.3 THRESHOLD CALCULATING - A SINGLE NEURON 130
7.2.4 THRESHOLD CALCULATING - A TWO-LAYER NETWORK 131 7.3 ROBUST FAULT
DIAGNOSIS 132 7.3.1 ADAPTIVE THRESHOLDS 133 7.3.2 FUZZY THRESHOLD
ADAPTATION 135 7.3.3 MODEL ERROR MODELLING 137 7.4 SUMMARY 140 8
INDUSTRIAL APPLICATIONS 141 8.1 SUGAR FACTORY FAULT DIAGNOSIS 141 8.1.1
INSTRUMENTATION FAULTS 143 8.1.2 ACTUATOR FAULTS 143 8.1.3 EXPERIMENTS
146 8.1.4 FINAL REMARKS 160 8.2 FLUID CATALYTIC CRACKING FAULT DETECTION
161 8.2.1 PROCESS MODELLING 163 8.2.2 FAULTY SCENARIOS 164 8.2.3 FAULT
DIAGNOSIS 164 8.2.4 ROBUST FAULT DIAGNOSIS 168 8.2.5 FINAL REMARKS 172
8.3 DC MOTOR FAULT DIAGNOSIS 172 8.3.1 AMIRA DR300 LABORATORY SYSTEM 173
8.3.2 MOTOR MODELLING 176 8.3.3 FAULT DIAGNOSIS USING DENSITY SHAPING
176 8.3.4 ROBUST FAULT DIAGNOSIS 181 8.3.5 FINAL REMARKS 182 9
CONCLUDING REMARKS AND FURTHER RESEARCH DIRECTIONS 187 REFERENCES 191
INDEX 203 |
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| callnumber-raw | TA169.6 |
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| callnumber-subject | TA - General and Civil Engineering |
| classification_rvk | SI 845 |
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| dewey-full | 620.0044 006.32 |
| dewey-hundreds | 600 - Technology (Applied sciences) 000 - Computer science, information, general works |
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| discipline | Informatik Mathematik |
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| isbn | 9783540798712 |
| language | English |
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| series2 | Lecture notes in control and information sciences |
| spelling | Patan, Krzysztof Verfasser aut Artificial neural networks for the modelling and fault diagnosis of technical processes Krzysztof Patan Berlin [u.a.] Springer 2008 XXII, 206 S. Ill., graph. Darst. 24 cm txt rdacontent n rdamedia nc rdacarrier Lecture notes in control and information sciences 377 Literaturverz. S. [191] - 202 Fault location (Engineering) Neural networks (Computer science) Technisches System (DE-588)4126276-1 gnd rswk-swf Rekursives neuronales Netz (DE-588)4379549-3 gnd rswk-swf Fehlererkennung (DE-588)4133764-5 gnd rswk-swf Technisches System (DE-588)4126276-1 s Fehlererkennung (DE-588)4133764-5 s Rekursives neuronales Netz (DE-588)4379549-3 s DE-604 Lecture notes in control and information sciences 377 (DE-604)BV005848579 377 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016709166&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Patan, Krzysztof Artificial neural networks for the modelling and fault diagnosis of technical processes Lecture notes in control and information sciences Fault location (Engineering) Neural networks (Computer science) Technisches System (DE-588)4126276-1 gnd Rekursives neuronales Netz (DE-588)4379549-3 gnd Fehlererkennung (DE-588)4133764-5 gnd |
| subject_GND | (DE-588)4126276-1 (DE-588)4379549-3 (DE-588)4133764-5 |
| title | Artificial neural networks for the modelling and fault diagnosis of technical processes |
| title_auth | Artificial neural networks for the modelling and fault diagnosis of technical processes |
| title_exact_search | Artificial neural networks for the modelling and fault diagnosis of technical processes |
| title_exact_search_txtP | Artificial neural networks for the modelling and fault diagnosis of technical processes |
| title_full | Artificial neural networks for the modelling and fault diagnosis of technical processes Krzysztof Patan |
| title_fullStr | Artificial neural networks for the modelling and fault diagnosis of technical processes Krzysztof Patan |
| title_full_unstemmed | Artificial neural networks for the modelling and fault diagnosis of technical processes Krzysztof Patan |
| title_short | Artificial neural networks for the modelling and fault diagnosis of technical processes |
| title_sort | artificial neural networks for the modelling and fault diagnosis of technical processes |
| topic | Fault location (Engineering) Neural networks (Computer science) Technisches System (DE-588)4126276-1 gnd Rekursives neuronales Netz (DE-588)4379549-3 gnd Fehlererkennung (DE-588)4133764-5 gnd |
| topic_facet | Fault location (Engineering) Neural networks (Computer science) Technisches System Rekursives neuronales Netz Fehlererkennung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016709166&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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| work_keys_str_mv | AT patankrzysztof artificialneuralnetworksforthemodellingandfaultdiagnosisoftechnicalprocesses |