Power Station Equipment Condition Evaluation and Maintenance Decision System
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.
machine learningdata-drivenfault detectionmaintenance decisionssystem development
万方数据
维普
