Advances in Technical Diagnostics II
Proceedings of the 7th International Congress on Technical Diagnostics, ICTD 2022, 14–16 September 2022, Radom, Poland
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Beschreibung
This book reports on recent theories and methods for diagnostics and condition monitoring of machines, materials and industrial processes, with a special emphasis on the application of artificial intelligence and intelligent control systems. Gathering original contributions to the 7th International Congress on Technical Diagnostics, ICTD2022, held on September 14–16, 2022, in Radom, Poland, this book offers extensive information on the latest trends in machine diagnostics and on IoT, smart sensors and machine learning technology in advanced condition monitoring. It addresses both scientists and professionals and is intended to foster communication and collaborations between the two groups.
This book reports on recent theories and methods for diagnostics and condition monitoring of machines, materials and industrial processes, with a special emphasis on the application of artificial intelligence and intelligent control systems. Gathering original contributions to the 7th International Congress on Technical Diagnostics, ICTD2022, held on September 14–16, 2022, in Radom, Poland, this book offers extensive information on the latest trends in machine diagnostics and on IoT, smart sensors and machine learning technology in advanced condition monitoring. It addresses both scientists and professionals and is intended to foster communication and collaborations between the two groups.
Reports on latest trends in technical diagnostics research and practice Gives a special emphasis to Artificial Intelligence in condition monitoring Offers a good balance of theory and practice
Autor*in
Andrzej Puchalski
Themen in »Advances in Technical Diagnostics II«
Fault Detection and Identification with Neural Networks Fault Diagnosis with AI IoT for Condition Monitoring Diagnostics of Machines and Materials Structural Health Monitoring Cyber Attacks Detection in Connected and Automated Vehicles Monitoring and Control of Energy Systems Fuzzy Condition Monitoring Gearbox Vibration Modeling Acoustic Emission Sensors Machine Learning for Fault Detection Deep Learning in Condition Monitoring Vibroacoustic Models Online Monitoring Systems Optimization Algorithms in Condition Monitoring