Accurately predicting the health status of power plant equipment is of great significance for determining the reliability and service life of the equipment.In order to perform predictive maintenance on power plant equipment,this paper proposes an edge predictive maintenance analysis model based on short-term and short-term memory models.Predict the remaining service life of equipment by considering the status of different components,and evaluate equipment degradation based on real-time data collected from operating equipment.To label the dataset,fuzzy logic is used to generate maintenance priorities,which are used to calculate the actual remaining service life.Deploy the proposed model to the power plant equipment and conduct performance evaluation.The results indicate that the edge prediction maintenance analysis model is much easier to develop and deploy,and has good predictive maintenance performance.
关键词
预测维护/故障检测/长短期记忆模型/边缘预测维护分析模型
Key words
predictive maintenance/fault detection/long-and short-term memory models/edge prediction maintenance analysis model
维普
万方数据