基于统计学方法的滚动轴承故障诊断

Application of statistics methods on fault diagnosis in bearing

提出了滚动轴承故障诊断的统计学方法应用,基于概率分布原理,该方法能够解决滚动轴承局部损伤模式识别的问题。实验室模拟几种滚动轴承工作状态,利用DLF-4电荷电压滤波积分放大器和INV306U智能信号采集分析仪分别采集相应的数据,然后进行相关处理与分析,分析结果以图标的形式给出。结果表明:基于概率分布原理的方法在轴承故障信号的处理中能够消除噪声影响,提取故障特征信息,从而识别出滚动轴承的实际工作状态,取得了较好的效果。

This paper puts up with the application of statistical methods on fault diagnosis in rolling beating, and this methods based on statistical distribution principle can deal with local damage pattern identification of rolling bearing. In process ＂of test, experimental data from several rolling bearing condition, which is simulated in laboratory, is amplified by DLF-4 charge voltage filter points amplifier and acquired and analyzed by INV306U smart signal acquisition analyzer instrument. The results presented by figures and tables show that during the processing of fault signals of bearing the method can eliminate the influence of background noise, extract fault characteristic signals, identify the practical conditions of rolling bearing and obtain obvious effects.