Chaotic Characteristic and Nonlinear Dynamic Performance of Rolling Bearing Friction Torque

2010 ◽  
Vol 26-28 ◽  
pp. 88-92 ◽  
Author(s):  
Xin Tao Xia ◽  
Tao Mei Lv ◽  
Fan Nian Meng
Keyword(s):  
Time Series ◽  
Nonlinear Dynamic ◽  
Dynamic Performance ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Box Dimension ◽  
Rolling Bearings ◽  
Chaotic Characteristic ◽  
Chaotic Theory ◽  
Bearing Friction

Based on the chaotic theory, the methods of the Lyapunov exponent and the box dimension were applied to evaluate the chaotic characteristic and the nonlinear dynamic performance of the rolling bearing friction torque. The time series were obtained via the experimental investigation on the friction torque of the rolling bearings under the condition of different rotational speeds. It is found that the rolling bearing friction torque is of a chaotic system because the maximum of Lyapunov exponents of its time series is greater than zero according to the chaotic theory. And the result shows that the mean of the box dimension of the friction torque increases with the rotational speed of the rolling bearing, revealing the new dynamic performance of the rolling bearing friction torque as a time series.

Information Entropy of Rolling Bearing Friction Torque as Data Series

2010 ◽  
Vol 44-47 ◽  
pp. 1115-1119 ◽  
Author(s):  
Xin Tao Xia ◽  
Long Chen ◽  
Fan Nian Meng
Keyword(s):  
Experimental Investigation ◽  
Information Entropy ◽  
Rotational Speed ◽  
Dynamic Performance ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Data Series ◽  
Entropy Theory ◽  
Rolling Bearings ◽  
Bearing Friction

The information entropy theory is applied to evaluate the uncertainty of the rolling bearing friction torque. The data series are obtained via the experimental investigation on the friction torque of the rolling bearings under the condition of different rotational speeds. And the result shows that the information entropy of the friction torque increases with the rotational speed of the rolling bearing, revealing the new dynamic performance of the rolling bearing friction torque as a data series.

Uncertainty of Rolling Bearing Friction Torque as Data Series Using Grey Bootstrap Method

2010 ◽  
Vol 44-47 ◽  
pp. 1125-1129
Author(s):  
Xin Tao Xia ◽  
Long Chen ◽  
Fan Nian Meng
Keyword(s):  
System Theory ◽  
Experimental Investigation ◽  
Bootstrap Method ◽  
Dynamic Performance ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Data Series ◽  
Rolling Bearings ◽  
The Mean ◽  
Bearing Friction

Based on the information poor system theory, the grey bootstrap method is employed to estimate the uncertainty of the rolling bearing friction torque. The data series are obtained via the experimental investigation of the friction torque of the rolling bearings under the condition of different rotational speeds. And the results show that the mean of the dynamic fluctuant range (MDFR) of the friction torque increases with the rotational speed of the rolling bearing, revealing the new dynamic performance of the rolling bearing friction torque as a data series.

Poor Information Analysis of Rolling Bearing Friction Torque Characteristic Parameter Based on Phase Space

2011 ◽  
Vol 382 ◽  
pp. 167-171
Author(s):  
Lei Lei Gao ◽  
Xin Tao Xia
Keyword(s):  
Time Series ◽  
Phase Space ◽  
Characteristic Parameter ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Point Estimation ◽  
Experimental Result ◽  
Bayesian Probability ◽  
Characteristic Parameters ◽  
Bearing Friction

The friction torque of rolling bearings belongs to an information poor system with unknown probability distributions and trends. This counteracts dynamical assessment for the characteristics of the rolling bearing friction torque as a time series. For this reason, the chaos theory is employed to recover the original dynamic characteristics of a friction torque time series by means of the phase space reconstruction theory. The dynamical Bayesian probability density function of the characteristic parameters of the friction torque is constructed by the information poor theory based on the phase space. The method for point estimation, interval estimation, and trend estimation of the characteristic parameters is proposed in this paper. The investigation shows that the error between the calculated result and the experimental result is very small.

Chaos Prediction of Rolling Bearing Friction Torque

2010 ◽  
Vol 26-28 ◽  
pp. 190-193 ◽  
Author(s):  
Xin Tao Xia ◽  
Tao Mei Lv
Keyword(s):  
Time Series ◽  
Experimental Investigation ◽  
Chaos Theory ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Local Region ◽  
Space Applications ◽  
Region Method ◽  
Weight One ◽  
Bearing Friction

Based on the chaos theory, the adding-weight one-rank local-region method was applied to predict the time series of the rolling bearing friction torque. The experimental investigation on the rolling bearing for space applications shows that the method is able to predict effectively the rolling bearing friction torque, only with very small predicted error.

Dynamic Prediction of Rolling Bearing Friction Torque Using Lyapunov Exponent Method

2010 ◽  
Vol 44-47 ◽  
pp. 1120-1124 ◽  
Author(s):  
Xin Tao Xia ◽  
Tao Mei Lv
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Small Data ◽  
Data Sets ◽  
Dynamic Prediction ◽  
Information Method ◽  
Small Data Sets ◽  
Bearing Friction

Based on the chaos theory, the Lyapunov exponent method is employed to predict dynamically the time series of the rolling bearing friction torque. First, the embedding dimension and the delay time for the phase space reconstruction are estimated with the Cao method and the mutual information method, respectively. Second, the maximum of the Lyapunov exponents is calculated by small data sets. Lastly, the nearest neighboring point is sought via the Euclidean distance. The experimental investigation shows that the method proposed in this paper is able to forecast effectively the rolling bearing friction torque as a time series, only with very small predicted error.

Standard Uncertainty of Rolling Bearing Vibration as Time Series

2011 ◽  
Vol 382 ◽  
pp. 133-136
Author(s):  
Xin Tao Xia ◽  
Lei Lei Gao ◽  
Xiao Chao Sun
Keyword(s):  
Time Series ◽  
Measurement Theory ◽  
Failure Process ◽  
Rolling Bearing ◽  
Standard Uncertainty ◽  
Bearing Failure ◽  
Vibration Acceleration ◽  
Rolling Bearings ◽  
Vibrational Acceleration ◽  
Bearing Vibration

The standard uncertainty in the measurement theory is applied to evaluate the change of the rolling bearing vibration acceleration generated by the failure on the surface of the ring raceway. The time series are obtained via the experimental investigation on the vibrational acceleration of the rolling bearings with different failure diameters. And the result shows that the standard uncertainty of the vibrational acceleration increases nonlinearly with the failure diameter, revealing a new characteristic of the variation of the rolling bearing failure process. It follows that for a rolling bearing in running, the failure process can be described by the standard uncertainty of its vibration acceleration, laying a foundation for failure warning of a rolling bearing.

Gray Chaos Evaluation Model for Prediction of Rolling Bearing Friction Torque

2010 ◽  
Vol 38 (3) ◽  
pp. 102623 ◽  
Author(s):  
M. R. Mitchell ◽  
R. E. Link ◽  
Xia Xintao ◽  
Lv Taomei ◽  
Meng Fannian
Keyword(s):  
Evaluation Model ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Bearing Friction

Stages prediction of the remaining useful life of rolling bearing based on regularized extreme learning machine

2021 ◽  
pp. 095440622110095
Author(s):  
Chenchen Wu ◽  
Hongchun Sun ◽  
Zihan Zhang
Keyword(s):  
Time Series ◽  
Pearson Correlation ◽  
Selection Criterion ◽  
Rolling Bearing ◽  
Remaining Useful Life ◽  
Rolling Bearings ◽  
Vibration Signals ◽  
Useful Life ◽  
Bearing Vibration ◽  
Learning Machine

The prediction of the remaining useful life (RUL) of rolling bearings is an important means to ensure the rotating machinery's safe operation. At present, most of the proposed methods use direct prediction based on bearing vibration signals, which not only have low prediction accuracy but also time-consuming. This paper proposes a staged prediction method, and the regularized learning machine (RELM) based on the proposed sensitive degradation feature is applied to predict RUL of the bearing with high accuracy and speed. Firstly, the relative root mean square value (RRMS) is used to divide the degradation stages of rolling bearings. Secondly, the RRMS indicator is used for multi-step time series prediction in the normal phase of the bearing. Thirdly, in the bearing's degradation stage, the Pearson Correlation Coefficient (PCC) Combined Entropy Weight Method (EWM) feature selection criterion is proposed to predict the RUL of the rolling bearing. Finally, the sensitive degradation feature of the bearing vibration signals is input into RELM to predict the RUL. The bearing data sets of PHM Challenging 2012 are used to verify the effectiveness of the proposed method. Three comparative experiments have been verified to prove the accuracy and rapidity of the proposed method in time series forecasting.

GreenBearings – Friction Behaviour of DLC-Coated Dry Running Deep Groove Ball Bearings

2015 ◽  
Vol 805 ◽  
pp. 147-153 ◽  
Author(s):  
Julia Kröner ◽  
Stephan Tremmel ◽  
Serge Kursawe ◽  
Yashar Musayev ◽  
Tim Hosenfeldt ◽  
...  
Keyword(s):  
Friction And Wear ◽  
Energy Savings ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Wear Behaviour ◽  
Ball Bearings ◽  
Rolling Bearings ◽  
Pumping Stations ◽  
Deep Groove ◽  
First Results

Due to the use of rolling bearings instead of plain bearings friction and wear are drastically reduced in all kind of machines. However, despite the high technical standard of modern rolling bearings there is still a significant potential for optimization. Preliminary Studies show a reduction of the friction torque of up to 44 % compared to conventional rolling bearings because of the use of tribological coatings in certain applications. Based on the millionfold usage of rolling bearings in all industrial fields the reduced lost energy adds up to a remarkable potential for energy savings. If friction and wear are lowered sufficiently, the use of conventional lubricants based on mineral oil can be successively decreased or even completely avoided. In the latter case, the socalled dry running of the rolling bearing, the energy consumption of machines and systems can additionally be reduced significantly. For example, pumping stations or compressed air units, which would be necessary for transporting or spraying the lubricants, can then be saved.This paper presents first results of DLC-coated deep groove ball bearings, which are tested in a four-bearing-test-rig under purely radial load with respect to their friction and wear behaviour.

Dynamic Prediction Model for Rolling Bearing Friction Torque Using Grey Bootstrap Fusion Method and Chaos Theory

2012 ◽  
Vol 443-444 ◽  
pp. 87-96 ◽  
Author(s):  
Xin Tao Xia ◽  
Tao Mei Lv
Keyword(s):  
Probability Distributions ◽  
Rolling Bearing ◽  
Friction Torque ◽  
Local Region ◽  
Fusion Method ◽  
Dynamic Prediction ◽  
Region Method ◽  
True Value ◽  
Weight One ◽  
Bearing Friction

Synthesizing the grey bootstrap fusion method and the five chaos forecasting methods (viz., the adding-weight zero-rank local-region method, the one-rank local-region method, the adding-weight one-rank local-region method, the improved adding-weight one-rank local-region method, and the maximum Lyapunov exponent method), a dynamic prediction model is proposed to calculate the predicted true value and the predicted interval of a chaotic time series under the condition of unknown probability distributions and trends. At the same time, the five forecasting values are acquired with the help of the five chaos forecasting methods, respectively, and the five forecasting values are fused to deduce the predicted true value and the predicted interval by means of the grey bootstrap fusion method. As time goes on, a series of the predicted true value and the predicted interval is obtained dynamically. Experimental investigation of the rolling bearing friction torque shows that using the grey bootstrap fusion method, the predicted true value and the measured values have an identical trend only with a small error, the predicted interval is acquired along with a high reliability, and the dynamic prediction of the rolling bearing friction torque as a chaotic time series is made without any prior knowledge of probability distributions and trends.

Sign in / Sign up

Export Citation Format

Share Document