Difference equation based empirical mode decomposition with application to separation enhancement of multi-fault vibration signals
Difference equation based empirical mode decomposition with application to separation enhancement of multi-fault vibration signals
复制标题
基于差分方程的经验模态分解及其在多故障振动信号分离增强中的应用
DOI：
10.1080/10236198.2016.1254206
复制
发表时间：
2017-01-01
影响因子：
1.1
通讯作者：
Peng, Zhongxiao
中科院分区：
文献类型：
--
作者：
Li, Zhixiong;Jiang, Yu;Peng, Zhongxiao
摘要经验模式分解（EMD）在信号处理中有着广泛的应用。然而，EMD对近模式特征频率和噪声敏感，导致模式混合问题。在齿轮箱振动分析中，模态混叠会严重影响齿轮箱多故障检测的性能。因此，本文提出了一种新的方法来解决模式混合问题的经验模态分解的齿轮箱多故障诊断。该方法将微分运算引入到本征模函数的分解中。微分运算可以提高对相邻频带的分解能力，因此微分EMD比非微分EMD更能识别特征频率相近的模态。此外，时间同步平均（TSA）与差分EMD相结合，以解决噪声问题。因此，建议TAS和差分EMD为基础的方法（TDEMD）可以解决模式混合的问题，提供有效的多故障检测齿轮箱。TDEMD已被测试实验使用的振动数据收集从齿轮箱上的两个不同的齿轮并发缺陷。结果表明，齿轮多故障的有效检测。
Abstract Empirical mode decomposition (EMD) has been applied to various applications in signal processing. However, EMD is susceptible to close mode characteristic frequencies and noise, resulting in the problem of mode mixing. The performance of multi-fault detection in gearboxes will be significantly degraded due to mode mixing in the vibration analysis. Hence, this paper presents a new method to address the mode mixing problem in EMD based gearbox multi-fault diagnosis. In this new method, the differential operation is introduced into the decomposition of the intrinsic mode functions. The decomposition ability of close frequency bands can be improved by the differential operation, and hence, the differential EMD can better identify the modes with close characteristic frequencies than its non-differential counterpart. In addition, time synchronous averaging (TSA) is combined with the differential EMD to address the noise issue. Thus, the proposed TAS and differential EMD based method (TDEMD) can solve the mode mixing problem to provide effective multi-fault detection for gearboxes. The TDEMD has been tested experimentally using vibration data collected from a gearbox with concurrent defects on two different gears. Results showed effective detection of gear multiple faults.