scholarly journals Dynamical Bayesian Significance Testing for Information on Performance Variation of Rolling Bearing for Space Applications

2013 ◽  
Vol 3 (1) ◽  
pp. 163
Author(s):  
Xintao Xia ◽  
Jiaqi Zhu
Keyword(s):  
Probability Density ◽  
Probability Distributions ◽  
Rolling Bearing ◽  
Significance Testing ◽  
Rolling Bearings ◽  
Space Applications ◽  
Significance Level ◽  
Mutation Probability ◽  
Unknown Probability ◽  
Performance Variation

A dynamical Bayesian significance testing method is proposed to examine information on performance variation of rolling bearings for space applications under the condition of an unknown probability distribution and trend in advance. Sub-series of time series of rolling bearing performance are obtained via a regularly sampling, probability density functions of sub-series are acquired with bootstrap and maximum entropy theory, a referenced sequence from sub-series is found by minimum variance principle, posterior probability density function is established according to Bayesian theory, and mutation probability is defined in the light of fuzzy set theory. At the given significance level, dynamical Bayesian significance testing for information on performance variation of rolling bearings is put into effect with the help of mutation probability. Experimental investigation presents that the method proposed can effectively detect variation information of rolling bearing performance with unknown probability distributions and trends.

Efficiency of application of the phase-chronometric method and neurodiagnostics for monitoring the degradation of rolling bearings during operation

2020 ◽  
pp. 43-50
Author(s):  
A.S. Komshin ◽  
K.G. Potapov ◽  
V.I. Pronyakin ◽  
A.B. Syritskii
Keyword(s):  
Life Cycle ◽  
Wavelet Analysis ◽  
Metrological Support ◽  
Rolling Bearing ◽  
Technical Condition ◽  
Measurement Information ◽  
Rolling Bearings ◽  
Vibration Diagnostics ◽  
Bearing Life ◽  
Alternative Approach

The paper presents an alternative approach to metrological support and assessment of the technical condition of rolling bearings in operation. The analysis of existing approaches, including methods of vibration diagnostics, envelope analysis, wavelet analysis, etc. Considers the possibility of applying a phase-chronometric method for support on the basis of neurodiagnostics bearing life cycle on the basis of the unified format of measurement information. The possibility of diagnosing a rolling bearing when analyzing measurement information from the shaft and separator was evaluated.

scholarly journals Predicting Remaining Useful Life of Rolling Bearings Based on Reliable Degradation Indicator and Temporal Convolution Network with the Quantile Regression

2021 ◽  
Vol 11 (11) ◽  
pp. 4773
Author(s):  
Qiaoping Tian ◽  
Honglei Wang
Keyword(s):  
Quantile Regression ◽  
Probability Density ◽  
Degradation Process ◽  
Remaining Useful Life ◽  
Health State ◽  
Rolling Bearings ◽  
Data Set ◽  
Time Frequency ◽  
Useful Life ◽  
Degradation Indicator

High precision and multi information prediction results of bearing remaining useful life (RUL) can effectively describe the uncertainty of bearing health state and operation state. Aiming at the problem of feature efficient extraction and RUL prediction during rolling bearings operation degradation process, through data reduction and key features mining analysis, a new feature vector based on time-frequency domain joint feature is found to describe the bearings degradation process more comprehensively. In order to keep the effective information without increasing the scale of neural network, a joint feature compression calculation method based on redefined degradation indicator (DI) was proposed to determine the input data set. By combining the temporal convolution network with the quantile regression (TCNQR) algorithm, the probability density forecasting at any time is achieved based on kernel density estimation (KDE) for the conditional distribution of predicted values. The experimental results show that the proposed method can obtain the point prediction results with smaller errors. Compared with the existing quantile regression of long short-term memory network(LSTMQR), the proposed method can construct more accurate prediction interval and probability density curve, which can effectively quantify the uncertainty of bearing running state.

The Effect of the EHD Pressure Spike on Rolling Bearing Fatigue

1987 ◽  
Vol 109 (3) ◽  
pp. 444-450 ◽  
Author(s):  
L. Houpert ◽  
E. Ioannides ◽  
J. C. Kuypers ◽  
J. Tripp
Keyword(s):  
Pressure Distribution ◽  
High Stress ◽  
Surface Damage ◽  
Rolling Bearing ◽  
Shear Stresses ◽  
Stress Concentrations ◽  
Surface Layers ◽  
Rolling Bearings ◽  
Life Model ◽  
Pressure Spike

A recently proposed fatigue life model for rolling bearings has been applied to the study of lifetime reduction under conditions conducive to microspalling. The presence of a spike in the EHD pressure distribution produces large shear stresses localized very close to the surface which may account for early failure. This paper describes a parametric study of the effect of such spikes. Accurate stress fields in the volume are calculated for simulated pressure spikes of different height, width and position relative to a Hertzian pressure distribution, as well as for different lubricant traction coefficients and film thicknesses. Despite the high stress concentrations in the surface layers, reductions in life predicted by the model are modest. Typically, the pressure spike may halve the life, with the implication that subsurface fatigue still dominates. In corroboration of this prediction, preliminary experimental work designed to reproduce microspalling conditions shows that microindents due to overrolling particles are a much more common form of surface damage than microspalling.

Probability distributions and orthogonal parameters

1950 ◽  
Vol 46 (2) ◽  
pp. 281-284 ◽  
Author(s):  
V. S. Huzurbazar
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Probability Distributions ◽  
Orthogonal Parameters ◽  
Image Position

Let f(x, αi) be the probability density function of a distribution depending on n parameters αi(i = 1,2, …, n). Then following Jeffreys(1) we shall say that the parameters αi are orthogonal if

Contribution to Rolling Bearing Reliability Modeling

2011 ◽  
Vol 110-116 ◽  
pp. 2497-2503 ◽  
Author(s):  
Zdenek Vintr ◽  
Michal Vintr
Keyword(s):  
Operating Time ◽  
Rolling Bearing ◽  
Time To Failure ◽  
Rolling Bearings ◽  
Mean Time To Failure ◽  
Reliability Modeling ◽  
Time Between Failures ◽  
Large Groups ◽  
Mean Time

Rolling bearings are usually considered to be non-repaired items the reliability of which is characterized by mean time to failure, or so called basic rating life. Reliability describes these parameters well in case the bearings are used in operation up to the very time the failure occurs, or during the time corresponding with basic rating life. In case of railway applications the bearings are often used in large groups and are preventively replaced after much shorter operating time as compared with their basic rating life. In the article there is a model which enables us to describe the bearings reliability in this specific case and to specify a number of failures which might be expected from a group of bearings during operating time, or to determine mean operating time between failures of bearings.

Rolling Bearing Parametric Excitation of a Jeffcott Rotor System

2020 ◽  
Author(s):  
Ghasem Ghannad Tehrani ◽  
Chiara Gastaldi ◽  
Teresa Maria Berruti
Keyword(s):  
Parametric Excitation ◽  
Rotational Speed ◽  
Input Parameter ◽  
Equations Of Motion ◽  
Harmonic Balance Method ◽  
Rolling Bearing ◽  
Mean Value ◽  
Hertzian Contact ◽  
Rolling Bearings ◽  
Jeffcott Rotor

Abstract Rolling bearings are still widely used in aeroengines. Whenever rotors are modeled, rolling bearing components are typically modeled using springs. In simpler models, this spring is considered to have a constant mean value. However, the rolling bearing stiffness changes with time due to the positions of the balls with respect to the load on the bearing, thus giving rise to an internal excitation known as Parametric Excitation. Due to this parametric excitation, the rotor-bearings system may become unstable for specific combinations of boundary conditions (e.g. rotational speed) and system characteristics (rotor flexibility etc.). Being able to identify these instability regions at a glance is an important tool for the designer, as it allows to discard since the early design stages those configurations which may lead to catastrophic failures. In this paper, a Jeffcott rotor supported and excited by such rolling bearings is used as a demonstrator. In the first step, the expression for the time–varying stiffness of the bearings is analytically derived by applying the Hertzian Contact Theory. Then, the equations of motion of the complete system are provided. In this study, the Harmonic Balance Method (HBM) is used to as an approximate procedure to draw a stability map, thus dividing the input parameter space, i.e. rotational speed and rotor physical characteristics, into stable and unstable regions.

Analysis of the Behaviour of Rolling Bearings in Contaminated Oil Using Some Condition Monitoring Techniques

2006 ◽  
Vol 220 (5) ◽  
pp. 447-453 ◽  
Author(s):  
T Akagaki ◽  
M Nakamura ◽  
T Monzen ◽  
M Kawabata
Keyword(s):  
Vibration Analysis ◽  
Wear Debris ◽  
Friction And Wear ◽  
Rolling Bearing ◽  
Rolling Bearings ◽  
Deep Groove ◽  
Deep Groove Ball Bearing ◽  
Observation Results ◽  
Wear Debris Analysis ◽  
Worn Surfaces

Friction and wear behaviours of rolling bearing in contaminated oil containing white-fused alumina particles were studied. The friction and wear processes were monitored using wear debris analysis, such as ferrography and spectrometric oil analysis program, and vibration analysis. Test bearing was a deep groove ball bearing (6002P5); Wear debris and worn surfaces of the bearing components were observed with a scanning electron microscope (SEM). It was found that the friction coefficient in the contaminated oil became lower by about 0.001 than that in the new oil for the large contaminants. The results of wear debris analysis showed that the large contaminants caused the high wear rate in the bearing. Three types of wear debris were commonly observed: thread-like debris, cutting chip debris, and plate-like debris. On the basis of the SEM observation results of the worn surfaces, wear mechanisms of these wear debris were discussed. The results of vibration analysis showed that the probability density function of vibration waveform was normal distribution in both the new and contaminated oils. In the contaminated oil, it changed depending on the contaminant size and the runtime, i.e. the progress of wear in the bearing. The result of wear debris analysis was related to that of vibration analysis and discussed.

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