Fault detection of a roller-bearing system through the EMD of a wavelet denoised signal.
Fault detection of a roller-bearing system through the EMD of a wavelet denoised signal.
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DOI：
10.3390/s140815022
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发表时间：
2014-08-14
期刊：
影响因子：
--
通讯作者：
Koh BH
中科院分区：
文献类型：
--
作者：
Ahn JH;Kwak DH;Koh BH
本文研究了基于小波消噪和固有模态函数协方差矩阵特征正交值的滚动轴承故障检测方法。通过经验模态分解（EMD）得到轴承振动信号的IMF。小波域中的信号筛选过程消除了可能导致轴承状况预测不准确的噪声破坏部分。我们将去噪后的轴承信号分割成几个区间，并将每个区间分解成IMF。每个分段的第一个IMF被收集，成为计算协方差矩阵。我们发现，从健康和受损轴承的协方差矩阵表现出不同的的drone配置文件，这可以是一个损伤敏感的功能。我们还说明了传统的方法的特征提取，观察峰度值的测量信号，比较所提出的技术的功能。研究论证了基于小波去噪的可行性，并通过实验室实验表明，跟踪IMF协方差矩阵的适当正交值可以成为监测轴承故障的有效可靠措施。
This paper investigates fault detection of a roller bearing system using a wavelet denoising scheme and proper orthogonal value (POV) of an intrinsic mode function (IMF) covariance matrix. The IMF of the bearing vibration signal is obtained through empirical mode decomposition (EMD). The signal screening process in the wavelet domain eliminates noise-corrupted portions that may lead to inaccurate prognosis of bearing conditions. We segmented the denoised bearing signal into several intervals, and decomposed each of them into IMFs. The first IMF of each segment is collected to become a covariance matrix for calculating the POV. We show that covariance matrices from healthy and damaged bearings exhibit different POV profiles, which can be a damage-sensitive feature. We also illustrate the conventional approach of feature extraction, of observing the kurtosis value of the measured signal, to compare the functionality of the proposed technique. The study demonstrates the feasibility of wavelet-based de-noising, and shows through laboratory experiments that tracking the proper orthogonal values of the covariance matrix of the IMF can be an effective and reliable measure for monitoring bearing fault.
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DOI：
10.3390/s140100283
发表时间：
2013-12-24
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Kwak DH;Lee DH;Ahn JH;Koh BH
通讯作者：
Koh BH
影响因子：
8.4
作者：
Cheng, JS;Yu, DJ;Yang, Y
通讯作者：
Yang, Y
影响因子：
8.4
作者：
Sugumaran, V.;Ramachandran, K. I.
通讯作者：
Ramachandran, K. I.
影响因子：
8.4
作者：
Ericsson, S;Grip, N;Strömberg, JO
通讯作者：
Strömberg, JO
影响因子：
7
作者：
DeCarlo, LT
通讯作者：
DeCarlo, LT