基于EMD和逻辑回归的轴承性能退化评估

发布时间：2018-04-25 13:40

  本文选题：滚动轴承 + 性能退化　； 参考：《机械设计与研究》2016年05期

【摘要】：为准确地评估滚动轴承的性能退化状态,提出了一种基于经验模态分解(empirical mode decomposition,EMD)和逻辑回归的评估方法。首先,提取轴承振动信号的本征模函数(intrinsic mode function,IMF)能量作为特征向量;其次,以轴承正常状态数据和失效状态的特征向量建立逻辑回归模型,获取回归参数;最后计算轴承信号全寿命周期的评估指数(confidential value,CV)。评估结果表明,该方法能及时发现早期故障,也能很好地描述轴承性能退化的各个阶段。
[Abstract]:In order to accurately evaluate the performance degradation of rolling bearings, an evaluation method based on empirical mode decomposition (EMD) and logical regression is proposed. Firstly, the intrinsic mode function intrinsics mode function IMF energy of the bearing vibration signal is extracted as the eigenvector, secondly, the logical regression model is established based on the normal state data of the bearing and the eigenvector of the failure state, and the regression parameters are obtained. Finally, the evaluation index for calculating the full life cycle of bearing signal is confidential value. The evaluation results show that this method can detect early faults in time, and can well describe each stage of bearing performance degradation.
【作者单位】： 华东交通大学机电工程学院;
【基金】：国家自然科学基金资助项目(51205130) 江西省科协重点活动项目(赣科协字[2014]88号
【分类号】：TH133.33
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本文编号：1801571