Publication: Artificial Intelligence Application in Power Generation Industry: Initial considerations
Date
2016
Authors
Ismail R.I.B.
Ismail Alnaimi F.B.
Al-Qrimli H.F.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Physics Publishing
Abstract
With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.
Description
Artificial intelligence; Competition; Condition monitoring; Genetic algorithms; Iterative methods; Neural networks; Problem solving; Fault detection and diagnosis; Faults detection; Intelligent condition monitoring; Mitigation measures; Nonlinear iterations; Plant operations; Power generation industries; Problem-solving abilities; Fault detection; artificial intelligence; artificial neural network; competitiveness; genetic algorithm; industrial technology; monitoring system; power generation; power plant