Forecasting for Variation Process of Reliability of Rolling Bearing Vibration Performance Using Grey Bootstrap Poisson Method

Abstract

：Fusing the grey bootstrap principle into Poisson process, the grey bootstrap Poisson method is proposed to forecast the variation process of reliability of the rolling bearing vibration performance. A small number of raw variation-intensity information presented by bearing vibration is extracted with the help of the counting process of time series in short time interval, a large number of generated variation-intensity information is simulated by means of bootstrap resampling from raw variation-intensity information, the estimated value of variation intensity is obtained by using the grey prediction model to process generated variation-intensity information, and the variation process of reliability of the bearing vibration performance is forecasted in time via the reliability function expressed as Poisson process. Experimental investigation on reliability of bearing vibration as a time series shows that variable states of performance reliability can be described truly and predicted values are in very good accordance with test values.

Experimental Investigation on Reliability of Variation Process of Rolling Bearing Vibration Performance

“…Four data sequences of vibration acceleration of rolling bearings (type SKF6205) is collected to analyze the variation process when the wear diameters are 0mm, 0.1778mm, 0.5334mm and 0.7112mm [7]. Then the standard deviation values of the data sequences are obtained for different time series as shown in Fig.…”

“…In view of this, the maximum entropy grey bootstrap principle [7,8] is applied to obtain the estimated true value function and the functions of upper and lower bounds of reliability, which belongs to the poor information theory [9][10][11]. Then the experiment is conducted to analyze he variation process of vibration performance reliability of rolling bearings.…”

Simulation Analysis of the Variation of Bearing Vibration Performance Based on Fuzzy Set Theory (Part I: Theory)

“…X.T. Xia proposed the grey bootstrap Poisson method to forecast the variation process of reliability of the rolling bearing vibration performance [5].Weihua Li and Jing Li applied the continuous hidden semi -Markov model to the evaluation of bearing performance degradation and made early warning of the bearing performance degradation [6]. El Morsy and Mohamed used the optimal Morlet wavelet filtering and envelope detection to analyze the experimental signals of the inner ring failure of the rolling bearing [7].…”

The Reliability Assessment for Friction Torque Performance of Rolling Bearings

“…Ali explored the combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and proposed a method based on the data-driven prognostic approach under the condition of Weibull distribution [2]. However, many products with unknown probability distributions have highly stringent requirements for performance continuity reliability to ensure their safe [7][8][9][10].…”