Behravan, Ali: Diagnostic classifiers based on fuzzy Bayesian belief networks and deep neural networks for demand-controlled ventilation and heating systems. 2021
Inhalt
- ACKNOWLEDGMENTS
- ABSTRACT
- KURZFASSUNG
- TABLE OF CONTENTS
- LIST OF FIGURES
- LIST OF TABLES
- LIST OF ACRONYMS
- LIST OF PUBLICATIONS FROM THIS THESIS
- 1. INTRODUCTION
- 2. BASIC CONCEPTS AND RELATED WORK
- 2.1. BASIC CONCEPTS OF COMPONENT-BASED SYSTEMS
- 2.2. BASIC CONCEPTS FOR DEPENDABILITY
- 2.3. BASIC CONCEPTS FOR MUTUAL INFORMATION THEORY
- 2.4. STATE-OF-THE-ART IN HVAC SIMULATION
- 2.5. STATE-OF-THE-ART IN FAULT DETECTION AND DIAGNOSIS FOR HVAC SYSTEMS
- 3. SYSTEM MODEL
- 3.1. PHYSICAL MODEL
- 3.2. DEMAND-CONTROLLED VENTILATION SYSTEM
- 3.3. MODULAR COMPOSABILITY OF HVAC MODELS
- 4. SIMULATION FRAMEWORK OF THE DCV AND HEATING SYSTEM
- 4.1. MODELING AND SIMULATION OF THE SYSTEM MODEL
- 4.2. MODELING AND SIMULATION OF THE MODULAR COMPOSABILITY
- 5. FAULT INJECTION FRAMEWORK
- 6. FAILURE DETECTION AND FAULT DIAGNOSIS METHODOLOGY
- 6.1. COMPOSED DIAGNOSTIC CLASSIFIER BASED ON KNOWLEDGE-DRIVEN-BASED AND DATA-DRIVEN-BASED METHODS
- 6.2. DATA-DRIVEN-BASED FAULT DIAGNOSIS BASED ON MULTICLASS CLASSIFICATION
- 7. EVALUATION AND RESULTS
- 7.1. EVALUATION AND RESULTS FOR COMPOSED DIAGNOSTIC CLASSIFIER BASED ON KNOWLEDGE-DRIVEN AND DATA-DRIVEN METHODS
- 7.2. EVALUATION AND RESULTS FOR DATA-DRIVEN-BASED FAULT DIAGNOSIS BASED ON MULTICLASS CLASSIFICATION
- 7.3. DISCUSSION ON RESULTS
- 8. CONCLUSION AND FURTHER RESEARCH
- REFERENCES