齿轮振动信号滑动递归分析及其应用

Sliding Recurrence Analysis and its Application of Gear Vibration Signal

采用递归图对齿轮振动信号进行研究,发现不同状态下的齿轮振动信号递归图存在明显差异,分析了这些递归图所表征的传动系统动力学特征。将递归图看作一幅能反映齿轮状态信息的二值图像,用递归率、确定率、层流率、递归时间等递归特征量对该二值图像进行特征描述,分析了递归特征量所代表的系统动力学特征和对应的递归图像特征。采用滑动递归分析对递归图进行分析,以更好地刻画递归图局部特征。应用该方法结合高斯混合模型及最大贝叶斯分类器对采自实验台的齿轮振动信号进行故障分类实验,结果表明应用该特征提取方法可获得较高的故障识别率。

According to the recurrence plot analysis to the gear vibration signal,it is found that there are obvious difference between the gear condition and the driver system characteristics represented by recurrence plots.If the recurrence plots are regarded as a binary image,the parameters calculation by recurrence qualification analysis,such as recurrence rate,determinism,laminarity and recurrence time etc can be used to describe the feature of the image.The characteristics of recurrence plots that correspond to dynamical system and image respectively are analyzed.In order to depict the local feature of recurrence plot,the sliding recurrence analysis is proposed.The proposed approach combined with Gaussian mixture model and Bayesian maximum likelihood classifier are used to classify the gear vibration signals which are acquired from gear fault experiment facility.The classification results show that the higher discrimination rate can be achieved by the proposed method.