![]() Compared to existing indicators such as kurtosis, RMS, and Shannon entropy, the proposed method is superior while carrying out defect degradation monitoring.ĪB - Early identification of rolling element defects is always a topic of interest for researchers and the industry. The experimental study reveals that the proposed method is capable of raising the alarm about the initiation of defects at a very early stage. ![]() One is from XJTU-SY Bearing datasets and another is from the Centre for Intelligent Maintenance Systems. The testing of newly developed VMD based trigonometric entropy measure is carried out on the two different types of data set. Finally, dynamic degradation monitoring is carried out by observing the trend in the principal component having the highest diverse information. Thereafter, PCA of selected measures is carried out. Fourth, the variance of measure is computed and two modes having the highest variance are selected for principal component analysis (PCA). Third, trigonometric entropy measure of various VMD modes is computed. Second, a trigonometric entropy measure is developed to monitor the dynamic change occurring in the health of bearing. First, vibration signals are obtained and are further decomposed using VMD to obtain various frequency modes. For early fault identification, a simple and effective dynamic degradation monitoring method using variational mode decomposition (VMD) based trigonometric entropy measure is developed. N2 - Early identification of rolling element defects is always a topic of interest for researchers and the industry. T2 - a simple and effective tool for dynamic degradation monitoring of rolling element bearing T1 - VMD based trigonometric entropy measure Compared to existing indicators such as kurtosis, RMS, and Shannon entropy, the proposed method is superior while carrying out defect degradation monitoring.", Compared to existing indicators such as kurtosis, RMS, and Shannon entropy, the proposed method is superior while carrying out defect degradation monitoring.Ībstract = "Early identification of rolling element defects is always a topic of interest for researchers and the industry. Early identification of rolling element defects is always a topic of interest for researchers and the industry.
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