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.
|Journal||IOP Conference Series: Earth and Environmental Science|
|Publication status||Published - 19 Apr 2016|
|Event||2nd International Conference on Advances in Renewable Energy and Technologies, ICARET 2016 - Putrajaya, Malaysia|
Duration: 23 Feb 2016 → 25 Feb 2016
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Earth and Planetary Sciences(all)