AI-Based Anomaly Detection on IoT Data-Driven Thermal Power Plants for Condition Monitoring and Preventive Maintenance
Book Chapter
Gangwani, P, Joshi, S, Upadhyay, H et al. (2023). AI-Based Anomaly Detection on IoT Data-Driven Thermal Power Plants for Condition Monitoring and Preventive Maintenance
. 240 83-97. 10.1007/978-3-031-28581-3_8
Gangwani, P, Joshi, S, Upadhyay, H et al. (2023). AI-Based Anomaly Detection on IoT Data-Driven Thermal Power Plants for Condition Monitoring and Preventive Maintenance
. 240 83-97. 10.1007/978-3-031-28581-3_8
Anomalies are an integral part of every system's behavior and sometimes cannot be avoided. The thermal power plant systems are one of the most complex dynamical systems which must function properly all the time with the least amount of costs. Therefore, it is crucial to timely detect such anomalies in real-world running power plant systems for monitoring the condition of a component and to avoid any failure or future maintenance. This book chapter discusses the need for detecting anomalies in thermal power plant data for monitoring and maintaining the conditions of these power stations and discusses various Artificial Intelligence (AI) techniques to detect sensor data anomalies in different components of a thermal power plant.
