Health Degradation Monitoring and Early Fault Diagnosis of a Rolling Bearing Based on CEEMDAN and Improved MMSE

被引:78
作者
Lv, Yong [1 ,2 ]
Yuan, Rui [1 ,2 ]
Wang, Tao [1 ,2 ]
Li, Hewenxuan [3 ]
Song, Gangbing [4 ]
机构
[1] Wuhan Univ Sci & Technol, Minist Educ, Key Lab Met Equipment & Control Technol, Wuhan 430081, Hubei, Peoples R China
[2] Wuhan Univ Sci & Technol, Hubei Key Lab Mech Transmiss & Mfg Engn, Wuhan 430081, Hubei, Peoples R China
[3] Univ Rhode Isl, Dept Mech Ind & Syst Engn, Kingston, RI 02881 USA
[4] Univ Houston, Dept Mech Engn, Smart Mat & Struct Lab, Houston, TX 77204 USA
来源
MATERIALS | 2018年 / 11卷 / 06期
基金
中国国家自然科学基金;
关键词
health degradation monitoring; early fault diagnosis; CEEMDAN; improved MMSE; smoothed coarse graining process; rolling bearing; EMPIRICAL MODE DECOMPOSITION; MULTISCALE SAMPLE ENTROPY; TIME-SERIES; VIBRATION SIGNALS; PHASE-SPACE; CLASSIFICATION; REPRESENTATION; EXTRACTION; ALGORITHM;
D O I
10.3390/ma11061009
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Rolling bearings play a crucial role in rotary machinery systems, and their operating state affects the entire mechanical system. In most cases, the fault of a rolling bearing can only be identified when it has developed to a certain degree. At that moment, there is already not much time for maintenance, and could cause serious damage to the entire mechanical system. This paper proposes a novel approach to health degradation monitoring and early fault diagnosis of rolling bearings based on a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved multivariate multiscale sample entropy (MMSE). The smoothed coarse graining process was proposed to improve the conventional MMSE. Numerical simulation results indicate that CEEMDAN can alleviate the mode mixing problem and enable accurate intrinsic mode functions (IMFs), and improved MMSE can reflect intrinsic dynamic characteristics of the rolling bearing more accurately. During application studies, rolling bearing signals are decomposed by CEEMDAN to obtain IMFs. Then improved MMSE values of effective IMFs are computed to accomplish health degradation monitoring of rolling bearings, aiming at identifying the early weak fault phase. Afterwards, CEEMDAN is performed to extract the fault characteristic frequency during the early weak fault phase. The experimental results indicate the proposed method can obtain a better performance than other techniques in objective analysis, which demonstrates the effectiveness of the proposed method in practical application. The theoretical derivations, numerical simulations, and application studies all confirmed that the proposed health degradation monitoring and early fault diagnosis approach is promising in the field of prognostic and fault diagnosis of rolling bearings.
引用
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页数:22
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