【摘要】 针对工业光纤网络通信故障检测过程繁琐、效率低的问题,设计了一种基于优化的决策树数据挖掘算法的光纤网络通信故障检测系统。系统以减少检测器重复工作和准确定位为目标,引入以决策树为核心的故障数据挖掘模块,降低了对非己空间的故障挖掘时间。将第一阶光纤网络故障分类时仅以IP地址作为参量变成第二阶分类时使用指定的网络指标为基础构建决策树,进一步提高故障检测精度。对某车辆制造企业现有的光纤网络应用结果表明,与标准决策树方法相比,该算法将精度从69.0%提升到99.9%,将误报率从3.14%降低到0.48%,优化效果明显。更多还原

【Abstract】 For tedious fault detection process and low detection efficiency of industrial optical network communication,an optical fiber network communication fault detection system based on optimized decision tree data mining algorithm was designed.In order to reduce the repeated rework of detector and realize accurate positioning,the fault data mining module taking the decision tree as the core was introduced into the system to reduce the time of fault mining in not its own space. Only taking the IP address as a parameter in the first-order fiber-optic network fault classification is changed into the construction of decision tree based on the specified network index in the second-order classification,which further improves the accuracy of fault detection.The application results of optical network existing in a vehicle manufacturing enterprise show that,compared with the standard method of decision tree,this algorithm has increased accuracy from 69.0% to 99.9%,and reduced the false report rate from3.14% to 0.48%. The optimization effect is obvious.更多还原