In order to solve the problem that it is difficult to effectively analyze and evaluate the reliability level of power plant equipment due to the complex operating conditions in the actual operation process,and there are various problems such as frequent temporary maintenance,insufficient maintenance,excess maintenance,blind maintenance and other prob-lems in the subsequent maintenance process of the power station equipment,this paper develops a set of power station e-quipment status evaluation and maintenance decision system.With machine learning as the support of algorithms,combined with thermal expertise to establish a data-driven thermal process model,and the model is used to conduct real-time online condition monitoring and evaluation of on-site operating equipment,providing basic information for maintenance decisions and fault diagnosis.
关键词
机器学习/数据驱动建模/故障诊断/维修决策/系统开发
Key words
machine learning/data-driven/fault detection/maintenance decisions/system development
维普
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