摘要
离心压缩机轴承是主机中故障率最高的部件,针对其故障模式复杂难以辨识的特点,选取与其运行状态密切相关的多个振动参数作为原始特征模式,阐述如何从故障信号数据库中,应用模糊聚类方法对轴承运行状态进行评判,挖掘出对压缩机轴承故障诊断的敏感特征参数。通过现场采集到的大量数据验证,准确率达到95%。
There is frequent fault occurrence in the beating of centrifugal gas compressor.According to the character of difficult diagnosis of it, to make several vibration parameters highly related to running conditions original mode, evaluate bearing running conditions by applying fuzzy clustering way and demonstrate how to mine the parameter sensitive to diagnosis of fault from database. It is confirmed that the accuracy reaches 95 percent by data cellected from rite.
出处
《轴承》
北大核心
2006年第7期30-33,共4页
Bearing
基金
国家自然科学基金资助项目(编号50105015)
