大数据处理环境下大型机组设备故障可视化诊断方法研究

为了提升大型机组设备故障信息的提取效率,实现故障可视化诊断,提出大数据处理环境下大型机组设备故障可视化诊断方法。采用基于工作变形分析( ODS )的振动可视化技术完成大型机组设备的振动分析,获取设备不同模态下的故障频率响应信号,并将其频率谱作为故障特征,利用模糊减法聚类算法获取故障诊断结果;并利用三维平行散点图与人机交互将故障诊断结果可视化呈现。测试结果表明,该方法可通过数据聚类有效完成大型机组设备故障诊断,并且具备较好的可视化效果,可满足大型机组设备故障的可视化需求。

Research on Visualized Diagnosis Method of Large Unit Equipment Failure in Big Data Processing Environment

In order to improve the extraction efficiency of large-scale unit equipment fault information and realize the visual diagnosis of faults , a visual diagnosis method for large-scale unit equipment faults in a big data processing environment is proposed.The vibration visualization technology based on operational deformation shape( ODS ) is used to complete the vibration analysis of large unit equipment.The fault frequency response signals under different modes of the equipment are obtained , and the frequency spectrum is taken as the fault feature.The fuzzy subtraction clustering algorithm is used to obtain the fault diagnosis results ; The results of fault diagnosis are visualized by 3D parallel scatter diagram and human-computer interaction.The test results show that the method can effectively complete the fault diagnosis of large scale unit equipment through data clustering , and has a good visualization effect , which can meet the visualization requirements of large-scale unit equipment failure.