A rolling bearing signal model based on a correlation probability box

Tang, Hong; Dai, H. L.; Li, Zihao; Du, Yi

doi:10.1016/j.measurement.2021.109652

Cited by 2 publications

(1 citation statement)

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“…Probability distribution can unify the regularity and randomness of signals, and probability density can better reflect the characteristics of signals [5]. Therefore, this paper proposes a fusion of probability density and l 2norm to measure the similarity of vibration signals of the electric spindle, which can effectively improve the accuracy of measurement results and has stronger robustness to noise [6][7].…”

Section: Introductionmentioning

confidence: 99%

Research on Vibration Similarity Measure of Motorized Spindle Bearing Based on Probability and l2-Norm

Wu,

Zheng,

et al. 2023

Advances in Transdisciplinary Engineering

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The electric spindle is an essential component of modern CNC machine tools as it plays a crucial role in determining the performance and accuracy of the machine. However, the vibration of its bearing unit can significantly impact the spindle’s operational reliability and service life. Therefore, it is essential to develop a reliable method to distinguish between synchronous and asynchronous vibrations at both ends of the electric spindle. In this paper, we propose a signal similarity measurement method based on probability and l2-norm to address this issue. The proposed method employs EMD to decompose the vibration signals of the electric spindle bearings at both ends. Then, probability distribution and l2-norm are used to measure signal similarity effectively. This approach can effectively distinguish between synchronous and asynchronous vibrations at both ends of the electric spindle. Experimental testing was conducted to verify the effectiveness of this method. The results show that the proposed method is reliable and effective in distinguishing between synchronous and asynchronous vibrations at both ends of the electric spindle. This method has the potential to enhance the bearing’s service life and the operational reliability of the electric spindle.

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Section: Introductionmentioning

confidence: 99%