E3S Web Conf.
Volume 236, 20213rd International Conference on Energy Resources and Sustainable Development (ICERSD 2020)
|Number of page(s)||4|
|Section||Green Technology Innovation and Intelligent Application of Environmental Equipment|
|Published online||09 February 2021|
Fault warning method based on extreme learning regression and fuzzy reasoning
1 State Grid Jiangsu Electric Power Co., Ltd, Nanjing 210024 China
2 Jiangsu Fangtian Co., Ltd, Nanjing 210036 China
Corresponding to author: email@example.com
Aiming at the problem of condition monitoring of thermal power units, a fault early warning method based on fuzzy learning machine is proposed. The extreme learning regression model between monitoring parameters is established by using real-time data. Then the estimated value is fuzzed and used for fuzzy reasoning, finally, the fault diagnosis results of the unit under small abnormal state are obtained. The simulation data of a 1000 MW unit is used for verification test and results show that the proposed method is reliable and accurate which is suitable for thermal unit state warning.
© The Authors, published by EDP Sciences 2021
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