Discussion: “Fatigue Life of High-Speed Ball Bearings With Silicon Nitride Balls” (Parker, R. J., and Zaretsky, E. V., 1975, ASME J. Lubr. Technol., 97, pp. 350–355)

1975 ◽  
Vol 97 (3) ◽  
pp. 356-356
Author(s):  
R. Valori
Keyword(s):  
Fatigue Life ◽  
Silicon Nitride ◽  
High Speed ◽  
Ball Bearings

scholarly journals Fatigue Life of High-Speed Ball Bearings With Silicon Nitride Balls

1975 ◽  
Vol 97 (3) ◽  
pp. 350-355 ◽  
Author(s):  
R. J. Parker ◽  
E. V. Zaretsky
Keyword(s):  
Fatigue Life ◽  
Silicon Nitride ◽  
High Speed ◽  
Bearing Steel ◽  
Rolling Element Bearing ◽  
Ball Bearings ◽  
Rolling Element ◽  
Low Mass ◽  
Element Bearing ◽  
Steel Balls

Hot-pressed silicon nitride was evaluated as a rolling-element bearing material. This material has a low specific gravity (41 percent that of bearing steel) and has a potential application as low mass balls for very high-speed ball bearings. The five-ball fatigue tester was used to test 12.7-mm- (0.500-in-) dia silicon nitride balls at maximum Hertz stresses ranging from 4.27 × 109 N/m2 (620,000 psi) to 6.21 × 109 N/m2 (900,000 psi) at a race temperature of 328K (130 deg F). The fatigue life of NC-132 hot-pressed silicon nitride was found to be equal to typical bearing steels and much greater than other ceramic or cermet materials at the same stress levels. A digital computer program was used to predict the fatigue life of 120-mm- bore angular-contact ball bearings containing either steel or silicon nitride balls. The analysis indicates that there is no improvement in the lives of bearings of the same geometry operating at DN values from 2 to 4 million where silicon nitride balls are used in place of steel balls.

Friction Torque Measurement in Partial Hybrid S-C Angular Contact Ball Bearings

2014 ◽  
Vol 658 ◽  
pp. 339-344
Author(s):  
Viorel Paleu ◽  
Ioan Damian ◽  
Cristel Stirbu
Keyword(s):  
Silicon Nitride ◽  
High Speed ◽  
Equilibrium Temperature ◽  
Friction Torque ◽  
Ball Bearings ◽  
Self Healing ◽  
Testing Device ◽  
Torque Measurement ◽  
Steel Balls ◽  
Partial Hybrid

To monitor the friction torque evolution in tandems of angular contact ball bearings, a new testing device is developed. New partial hybrid bearings from 7206C series are obtained by combining 8 steel balls with 4 silicon nitride balls of the same diameter equally spaced in the cage, these bearings being denoted hereafter as 8S-4C type. For comparison, tests are carried-out also on conventional all-steel bearings and hybrid bearings with all the steel balls replaced by silicon nitride balls. The equilibrium temperature of the all-steel, hybrid and 8S-4C ball bearings is determined by tests. At high speed and light axial load, the 8S-4C ball bearings withstand to an oil shut-off test of one minute, while the similar all-steel bearings seized. The 8S-4C partial hybrid ball bearings can be an advantageous solution comparative to more expensive all hybrid bearings, avoiding the scuffing due to the self-healing effect induced by the higher hardness of the silicon nitride balls.

Ceramics in Rolling Element Bearings

1979 ◽  
Author(s):  
C. F. Bersch ◽  
Philip Weinberg
Keyword(s):  
Fatigue Life ◽  
Silicon Nitride ◽  
Cooling System ◽  
Extreme Environment ◽  
Ball Bearings ◽  
Rolling Element Bearings ◽  
Turbine Engine ◽  
Rolling Element ◽  
Rolling Elements ◽  
History Of

The feasibility of using hot-pressed silicon nitride (HPSN) for rolling elements and for races in ball bearings and roller bearings has been explored. HPSN offers opportunities to alleviate many current bearing problems including DN and fatigue life limitations, lubricant and cooling system deficiencies, and extreme environment demands. The history of ceramic bearings and the results of various element tests, bearing tests in rigs, and bearing tests in a turbine engine will be reviewed. The advantages and problems associated with the use of HPSN in rolling element bearings will be discussed.

The Performance of Ball Bearings With Silicon Nitride Ceramic Balls in High Speed Spindles for Machine Tools

1988 ◽  
Vol 110 (4) ◽  
pp. 693-698 ◽  
Author(s):  
Hirotoshi Aramaki ◽  
Yoshio Shoda ◽  
Yuka Morishita ◽  
Takeshi Sawamoto
Keyword(s):  
Silicon Nitride ◽  
Temperature Rise ◽  
Machine Tools ◽  
High Speed ◽  
Low Cost ◽  
Steel Ball ◽  
Ball Bearings ◽  
Grease Lubrication ◽  
Frictional Loss ◽  
High Speeds

Two types of angular contact ball bearings for machine tools having steel rings and silicon nitride balls were tested and the temperature rise was compared with that of conventional steel ball bearings with grease lubrication and oil-air lubrication as well. Experimental results indicated that the temperature rise of silicon nitride ball bearings was much lower than that of steel ball bearings at high speeds. Calculations made using a computer demonstrated that the reduction of gyroscopic moments and centrifugal forces acting on balls because of the low density of silicon nitride resulted in about 30 to 50 percent less frictional loss at high speeds even with low-cost lubrication such as grease or oil-air.

Research on modeling and mechanical behaviors of matched angular contact ball bearings

2020 ◽  
pp. 095440622093703
Author(s):  
Jianguo Gu ◽  
Yimin Zhang
Keyword(s):  
Fatigue Life ◽  
High Speed ◽  
Transformation Method ◽  
Axial Position ◽  
Ball Bearings ◽  
Mechanical Behaviors ◽  
Heavy Load ◽  
Rotating Speed ◽  
Proposed Model ◽  
Stiffness Characteristics

In engineering applications, angular contact ball bearings are usually mounted in pairs to accommodate the high-speed and heavy-load conditions. The usability, security, and stability of rotating machinery systems are heavily dependent on the mechanical behaviors of matched angular contact ball bearings. However, few related works about matched bearings have been reported. Consequently, it is of great significance to investigate the mechanical properties of matched bearings. This paper presents an analysis of the stiffness and fatigue life characteristics of matched angular contact ball bearings under axial position preload. First, an improved quasi-static model is proposed by using universal coordinate transformation method to investigate the stiffness characteristics of matched bearings. On basis of this, the fatigue life of matched bearings under running condition can be calculated. Then, the validity of the proposed model is verified via comparison between calculated results with previously published experimental results. Finally, a pair of 7206B bearings is taken as a numerical example to illustrate the application of the proposed model. The effects of bearing configuration form, preload, external loads, rotating speed on the stiffness, and fatigue life of matched bearings are discussed in detail.

scholarly journals Evaluation of Electron-Beam Welded Hollow Balls for High-Speed Ball Bearings

1971 ◽  
Vol 93 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Harold H. Coe ◽  
Richard J. Parker ◽  
Herbert W. Scibbe
Keyword(s):  
Fatigue Life ◽  
High Speed ◽  
Ball Bearing ◽  
Similar Data ◽  
Ball Bearings ◽  
Outer Race ◽  
Rolling Element ◽  
Solid Ball ◽  
Steel Balls ◽  
Weld Area

An experimental investigation was performed with two series (115 and 215) of 75 mm bore ball bearings using hollow balls as the rolling elements. The bearings were tested at 500 and 1000 pounds thrust loads at shaft speeds up to 24000 rpm. The 115 series bearings with 1/2-in. SAE 52100 steel balls showed very little difference in torque, outer-race temperature, or rolling-element fatigue life when compared to similar data for a solid ball bearing. The 215 series bearings with 11/16-in. AISI M-50 steel balls showed only slight differences in torque and outer-race temperature but a very significant decrease in rolling-element fatigue life compared to a solid ball bearing. The balls failed in flexure fatigue, due to a stress concentration in the weld area.

Load Spectrum Compiling and Fatigue Life Estimation of the Automobile Wheel Hub

2020 ◽  
Vol 13 ◽  
Author(s):  
Xintian Liu ◽  
Yang Qu ◽  
Xiaobing Yang ◽  
Yongfeng Shen
Keyword(s):  
Fatigue Life ◽  
High Speed ◽  
Two Dimensional ◽  
Load Spectrum ◽  
One Dimensional ◽  
Life Estimation ◽  
Load Spectra ◽  
Fatigue Life Estimation ◽  
Program Load Spectrum ◽  
Program Load

Background:: In the process of high-speed driving, the wheel hub is constantly subjected to the impact load from the ground. Therefore, it is important to estimate the fatigue life of the hub in the design and production process. Objective:: This paper introduces a method to study the fatigue life of car hub based on the road load collected from test site. Methods:: Based on interval analysis, the distribution characteristics of load spectrum are analyzed. The fatigue life estimation of one - dimensional and two - dimensional load spectra is compared by compiling load spectra. Results:: According to the S-N curve cluster and the one-dimensional program load spectrum, the estimated range fatigue life of the hub is 397,100 km to 529,700 km. For unsymmetrical cyclic loading, each level means and amplitude of load were obtained through the Goodman fatigue empirical formula, and then according to S-N curve clusters in the upper and lower curves and two-dimensional program load spectrum, estimates the fatigue life of wheel hub of the interval is 329900 km to 435200 km, than one-dimensional load spectrum fatigue life was reduced by 16.9% - 17.8%. Conclusion:: This paper lays a foundation for the prediction of fatigue life and the bench test of fatigue durability of auto parts subjected to complex and variable random loads. At the same time, the research method can also be used to estimate the fatigue life of other bearing parts or high-speed moving parts and assemblies.

Temperature Rise Prediction of Oil-Air Lubricated Angular Contact Ball Bearings Using Artificial Neural Network

2019 ◽  
Vol 12 (3) ◽  
pp. 248-261
Author(s):  
Baomin Wang ◽  
Xiao Chang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Temperature Rise ◽  
High Speed ◽  
Ball Bearing ◽  
Influence Factors ◽  
Ball Bearings ◽  
Ann Model ◽  
Angular Contact Ball Bearing ◽  
Artificial Neural

Background: Angular contact ball bearing is an important component of many high-speed rotating mechanical systems. Oil-air lubrication makes it possible for angular contact ball bearing to operate at high speed. So the lubrication state of angular contact ball bearing directly affects the performance of the mechanical systems. However, as bearing rotation speed increases, the temperature rise is still the dominant limiting factor for improving the performance and service life of angular contact ball bearings. Therefore, it is very necessary to predict the temperature rise of angular contact ball bearings lubricated with oil-air. Objective: The purpose of this study is to provide an overview of temperature calculation of bearing from many studies and patents, and propose a new prediction method for temperature rise of angular contact ball bearing. Methods: Based on the artificial neural network and genetic algorithm, a new prediction methodology for bearings temperature rise was proposed which capitalizes on the notion that the temperature rise of oil-air lubricated angular contact ball bearing is generally coupling. The influence factors of temperature rise in high-speed angular contact ball bearings were analyzed through grey relational analysis, and the key influence factors are determined. Combined with Genetic Algorithm (GA), the Artificial Neural Network (ANN) model based on these key influence factors was built up, two groups of experimental data were used to train and validate the ANN model. Results: Compared with the ANN model, the ANN-GA model has shorter training time, higher accuracy and better stability, the output of ANN-GA model shows a good agreement with the experimental data, above 92% of bearing temperature rise under varying conditions can be predicted using the ANNGA model. Conclusion: A new method was proposed to predict the temperature rise of oil-air lubricated angular contact ball bearings based on the artificial neural network and genetic algorithm. The results show that the prediction model has good accuracy, stability and robustness.

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