Design And Implementation Of Fan Fault Early Warning System

With the rapid development of wind power industry,wind power enterprise demand for software platform is also gradually expanding.Wind farm business usually only provide basic fan operating information,these data can't meet the wind power enterprises to carry out high quality statistical analysis and decision making requirements.Especially in the face of the fan structure is more and more complex cases,fan failure led to increasingly frequent and complex,which brings to the fan maintenance cost is very expensive.How can bring the maximization of economic benefit,for wind power enterprises are facing this problem,this paper discusses the application of the fan fault early warning the following research.Based on the wind power industry in the library two years fan fault information are classified statistics,according to the failure time of volatility,of every kind of fault for parameter selection.Because the decision tree is based on the theory of maximum entropy for a single fault classification has the very good effect,we for fan in different kinds of fault cases,respectively,to the creation of the decision tree model,the fan fault according to the different types of fan failure model creation process,according to the maximum entropy theory,find the fan fault for different species of lead to maximum entropy parameter,so as to further optimize the range of parameters.In view of the actual situation,resulting in the fan failure is g,how efficient for multiple categories to classify,we adopted here is based on support vector machine(SVM)as a precondition for decision-making of many kinds of fault,and set up a decision tree based on the SVM classification model verification,and the effect is obvious.Fan more classification based on the above model creation,we on the basis of using Spring MVC + Mybits architecture,warning of the fan is implemented.Finally,this paper study on the suitability of platform in detail.Analysis of the different wind farms,differences between the fan,and implements the method adapted to those differences.This method has been used in liaoning,Inner Mongolia.