The Study Of Condition Forecasting Support System For Feed Water System Of Boiler

In recent years, the successful using of combining prediction method in manyfields has exploited new way for the development of condition forecasting technology ofpower generating equipment.In this paper, for solving the problem that the equipment inpower plant are complex and difficult to predict their conditions accurately, a model ofcombining condition prediction on equipment in power plant based on grey GM(1,1)model and BP neural network is proposed on the basis of characteristic conditionparameters extraction. By fully using the operating parameters, condition monitoringparameters and operation statistic parameters, the conditions of equipment are predicted. The feed water system of boiler is one of important system of thermodynamiccirculation in power plant. It has important real signification to study the conditionforecasting of feed water system. Therefore, this paper applied the study fruit ofcombining condition prediction on the feed water system in power plant. The resultsreveal that the model has high efficiency and precision. The predicted results can be usedas a support next in making scientific maintenance decisions.