面向数据挖掘的静态电源综合故障诊断研究

A research for integrated error diagnosis of solid state power Oriented data mining

摘要:

静态电源是机场桥载设备最重要的组成部件之一,应用非常广泛。然而,其产生的频发故障会造成设备利用率低、修复率时长和经济损失等问题,在基于桥载设备的安监系统上,提出了静态电源综合故障诊断方法,通过数据挖掘软件,建立了静态电源故障诊断预测模型。通过在线数据库测试结果表明得到了综合故障诊断方法在预测静态电源故障上显现的特点,得到了静态电源的未来状态,实现了对静态电源的实时故障进行预测,进而为解决故障提供方向和目标,最终达到降低经济损失最大化的目的。

Abstract:

Solid state power is one of the most important part of the bridge-born equipment on airport. By structuring the model of error diagnosis prediction and the collecting node of safety monitoring information with the data mining software, frequent errors appearing on solid state power can be effectively avoided. The frequent errors will usually arose a series of problems, including low utilization rate, long repair rate time and severely economic losses and so on. By measuring on the basis of online database, it can be concluded that the obvious characteristics emerge in predicting the future state of static power. Moreover, what is the comprehensively optimal algorithm can effectively predict the future state of static power and make the real-time error prediction come true. Furthermore, the model can provide error solution with direction and goal. Finally, it gets the purpose that economic losses can be reduced to maximization.