Traction Behavior of Some Lubricants Used for Rolling Bearings in Spacecraft Applications: Experiments and Thermal Model Based on Primary Laboratory Data

2001 ◽  
Vol 124 (1) ◽  
pp. 72-81 ◽  
Author(s):  
Daniel Ne´lias ◽  
Eric Legrand ◽  
Philippe Vergne ◽  
Jean-Bernard Mondier

Three synthetic oils used in spacecraft mechanisms (Pennzane SHF X2000, Nye 186 A, and Fomblin Z25) have been studied. Rheological tests were performed in order to characterize the behavior of each fluid versus pressure, temperature and shear rate. That includes the determination of the WLF viscosity model parameters. Tribological tests were carried out to measure the traction coefficient for operating conditions representative of spacecraft applications. Experimental results were compared with theoretical ones obtained using a non-newtonian thermal model. The modeling of traction in EHL contact is based on the Johnson and Tevaarwerk’s model modified to account for the shear heating of the fluid. The variations of the lubricant thermal conductivity with respect to temperature and pressure are also considered. In this model, input data comes directly from rheological experiments or are derived from other measurements through physical relationships. These rheological and tribological characterizations are essential to better describe the behavior of a lubricated rolling bearing.

2010 ◽  
Vol 136 ◽  
pp. 316-320 ◽  
Author(s):  
Jian Ping Liu ◽  
Xin Yi Zhang ◽  
Qing Xuan Jia

Based on Johnson and Tevaarwerk’s model, traction coefficient was obtained for operating conditions representative of spacecraft applications. In this model input data come directly from rheological experiments or are derived from other measurements through physical relationships. Theoretical results were also compared with experimental ones which were measured for the same operating conditions.


1987 ◽  
Vol 109 (3) ◽  
pp. 235-240 ◽  
Author(s):  
J. Kraus ◽  
J. J. Blech ◽  
S. G. Braun

A method is presented for the extraction of rolling bearings characteristics (stiffness and damping) under operating conditions. The method is based on experimental modal analysis combined with a mathematical model of the rotor-bearings-support system. The method has been applied for the investigation of the effect of speed, preload, and free outer race bearings on system stiffness and damping. The method proves to be very accurate for stiffness determination and reasonably so for damping.


2010 ◽  
Vol 29-32 ◽  
pp. 1602-1607 ◽  
Author(s):  
Xiang Shun Chen ◽  
Hu Biao Zeng ◽  
Zhi Xiong Li

Rolling bearings are widely used in various areas including aircraft, mining, manufacturing, and agriculture, etc. The breakdowns of the rotational machinery resulted from the rolling bearing failures account for 30%. It is therefore imperative to monitor the rolling bearing conditions in time in order to prevent the malfunctions of the plants. In the present paper is described a fault detection and diagnosis technique for rolling bearing multi-faults based on wavelet-principle component analysis (PCA) and fuzzy k-nearest neighbor (FKNN). In the diagnosis process, the wavelet analysis was firstly employed to decompose the vibration data of the rolling bearings under eight different operating conditions, and for each sample its energy of each sub-band was calculated to obtain the original feature space. Then, the PCA was used to reduce the dimensionality of the original feature vector and hence the most important features could be gotten. Lastly, the FKNN algorithm was employed in the pattern recognition to identify the conditions of the bearings of interest. The experimental results suggest that the sensitive fault features can be extracted efficiently after the wavelet-PCA processing, and the proposed diagnostic system is effective for the rolling bearing multi-fault diagnosis. In addition, the proposed method can achieve higher performance than that without PCA with respect to the classification rate.


1985 ◽  
Vol 107 (3) ◽  
pp. 367-377 ◽  
Author(s):  
E. Ioannides ◽  
T. A. Harris

This paper describes a novel model for the prediction of fatigue life in rolling bearings. Central to this model is the postulation of a statistical relationship between the probability of survival, the fatigue life, and a stress-related fatigue criterion level above a fatigue limit for an elementary volume of material in the bearing. Using this concept, the stress volume to fatigue and the fatigue life of the bearing can be calculated for different loads, material and operating conditions. Comparisons between experimentally obtained rolling bearing fatigue lives and lives predicted using this theory indicate its ability to account for phenomena hitherto excluded from fatigue life predictions. Furthermore, comparisons between experimentally obtained fatigue lives for other specimens used in structural fatigue tests and fatigue lives predicted using the new model show good agreement.


2019 ◽  
Vol 11 (12) ◽  
pp. 168781401989721 ◽  
Author(s):  
Changchang Che ◽  
Huawei Wang ◽  
Qiang Fu ◽  
Xiaomei Ni

Rolling bearings are the vital components of rotary machines. The collected data of rolling bearing have strong noise interference, massive unlabeled samples, and different fault features. Thus, a deep transfer learning method is proposed for rolling bearings fault diagnosis under variable operating conditions. To obtain robust feature representation, the denoising autoencoder is used to denoise and reduce dimension of unlabeled rolling bearing signals. For those unlabeled target domain signals, a feature matching method based on multi-kernel maximum mean discrepancies between source domain and target domain is adopted to get enough labeled target domain samples. Then, these rolling bearing signals are converted to multi-dimensional graph samples and fed into a convolutional neural network model for fault diagnosis. To improve the generalization of convolutional neural network under variable operating conditions, we combine model-based transfer learning with feature-based transfer learning to initialize and optimize the convolutional neural network parameters. The effectiveness of the proposed method is validated through several comparative experiments of Case Western Reserve University data. The results demonstrate that the proposed method can learn features adaptively from noisy data and increase the accuracy rate by 2%–8% comparing with other models.


2013 ◽  
Vol 633 ◽  
pp. 103-116 ◽  
Author(s):  
Radoslav Tomovic

One of the most important characteristics of a rolling bearing is the load distribution on rolling elements. This paper provides an analysis on the influence of the internal construction of rolling bearings on load distribution and the number of active rolling elements. The analysis was performed using a new mathematical model for the boundary level calculations of the bearing deflection and external radial load for the inner ring support onqrolling bearing elements. The model considers two boundary positions of inner ring support on an even and odd number of rolling elements. The developed model enables a very simple determination of the number of active rolling elements participating in an external load transfer, depending on the bearing type and internal radial clearance.


1990 ◽  
Vol 112 (1) ◽  
pp. 23-26 ◽  
Author(s):  
P. K. Gupta ◽  
T. E. Tallian

Models for the correction of classical fatigue life for material imperfections and severity of operating conditions in rolling bearings are implemented in a bearing dynamics computer code. The significance of life correction factors is then demonstrated for both ball and cylindrical roller bearings over a range of operating conditions.


Author(s):  
I Bercea ◽  
D Nélias ◽  
G Cavallaro

To increase the rigidity of bearings-shaft systems, the shaft is often supported by a series of double-row rolling bearings. Little work on multiple-row rolling bearings has been published. A comprehensive model is proposed which permits the determination of the internal interactions. The total elastic deflection between bearing rings is described using a vector-and-matrix method. A variety of double-row rolling bearing types are analysed, such as tapered roller bearing, cylindrical roller bearing, spherical roller bearing, self-aligning ball bearings and angular contact ball bearing. The basic internal geometry (including the internal clearance) and the effect of the initial preload (in term of the initial axial compression) are considered.


2017 ◽  
Vol 20 (1) ◽  
Author(s):  
DUMITRU-CRISTINEL NADABAICA ◽  
VALENTIN NEDEFF ◽  
LUMINITA BIBIRE ◽  
NARCIS BÂRSAN

<p>In the calculation of the rolling bearings lifetime are taking in to consideration the distribution of the work load on each rolling elements, obliquity, internal operation clearance and pre-stressing. In the case of a rolling bearing with a defect, the internal operation clearance have an influence upon the evolution of its deterioration and remaining lifetime by: internal manufacturing clearance; the expansion of the inner ring when the rolling bearing is mounted on a adapter sleeve; the contraction of the outer ring when the rolling bearing is mounted in the housing; and the temperature difference between rolling bearing rings during operation. This paper presents an experimental study regarding to the influence of the internal operation clearance of the ZKL 1205K rolling bearing upon the remaining lifetime in same operating conditions. </p>


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