Search results

This paper uses numerical methods to investigate the collision and skidding of rolling elements in a cageless ball bearing. This paper aims to analyse the effects of the rotational speed and number of rolling elements on the rolling element collision and skidding.

Based on Hertzian theory and tribological theory, the collision contact model of the rolling element was established. Based on the proposed model, the differential equations of motion of the two degrees of freedom rolling element were constructed. The fourth-order Adams algorithm solved the collision contact force between the rolling elements. The sliding velocity between the rolling element and the inner and outer races was calculated.

The collision frequency and slip of rolling elements can be reduced by increasing the rotational speed appropriately and reducing the number of rolling elements by one.

The developed model can reveal the collision and slip characteristics of the rolling elements for cageless bearings. This study can provide theoretical guidance for the design and manufacture of cageless ball bearings.

The purpose of this paper is to introduce a high-speed rolling bearing test rig supported by sliding bearing and its first experimental results.

Through analyzing the disadvantages of using rolling bearing as supporting bearing, the bottlenecks that need to be resolved urgently in the development of rolling bearing experimental technology, and the advantages of the sliding bearing, this study used the sliding bearing as the supporting bearing for the high-speed rolling bearing test rig for the purpose of prolonging the service life, increasing the load capacity and promoting the operating stability.

The experimental results show that the high-speed rolling bearing test rig supported by sliding bearing could stably rotate at 70,800 rpm without installing the test bearing; the temperature of the sliding bearing is increasing with the rotating speed and the maximum is less than 95°C. Moreover, the new test rig, installing an angular contact ball bearing as test bearing, could also stably rotate at 54,000 rpm with 2 kN axial load and 1 kN radial load; the temperature of the sliding bearing is increasing with the rotating speed and the maximum temperature is less than 97°C.

Rolling test rig has been established.

This paper proposes a high-speed rolling bearing test rig supported by sliding bearing, which greatly prolongs the service life, increases the load capacity and promotes the operating stability, moreover, reduces the risk of supporting bearing failure before the test bearing. This paper can also provide a new idea and reference for the design of similar bearing test rig.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2020-0085/

The efficient and economical use of natural resources is a big issue. Machine elements with a rolling contact are highly relevant because of their wide application in technical systems and a large production quantity. Innovative hard machining can reduce the friction and increase the fatigue strength of rolling element bearings. The purpose of this study is to focus on the surface properties of such parts.

A new model to predict bearing fatigue life is presented which takes compressive residual stresses in the bearing subsurface area into consideration. The investigated bearings were machined by the processes of hard turning, hard turning with subsequent deep rolling and a combination of hard turning and deep rolling (turn-rolling) in one process step. Changes in the residual stress state during bearing fatigue tests were investigated and the influence of residual stresses on the bearings fatigue life was researched.

Both combinations including the deep rolling process decrease the surface roughness and induce compressive residual stresses. As a result, the L₁₀ fatigue life of roller bearings was increased by the factor of 2.5. Owing to the developed models, this effect can be considered within the design process.

In the context of the research program “Resource efficient Machine Elements (SPP1551),” machining processes of bearings were investigated regarding the bearing fatigue life. By inducing beneficial residual stresses on the bearings’ subsurface area, the fatigue life could be increased. Thus higher resource efficiency was achieved. To increase the productivity, a combination of hard turning and deep rolling was evaluated.

The purpose of this paper is to provide a fault diagnosis method for rolling bearings. Rolling bearings are widely used in industrial appliances, and their fault diagnosis is of great importance and has drawn more and more attention. Based on the common failure mechanism of failure modes of rolling bearings, this paper proposes a novel compound data classification method based on the discrete wavelet transform and the support vector machine (SVM) and applies it in the fault diagnosis of rolling bearings.

Vibration signal contains large quantity of information of bearing status and this paper uses various types of wavelet base functions to perform discrete wavelet transform of vibration and denoise. Feature vectors are constructed based on several time-domain indices of the denoised signal. SVM is then used to perform classification and fault diagnosis. Then the optimal wavelet base function is determined based on the diagnosis accuracy.

Experiments of fault diagnosis of rolling bearings are carried out and wavelet functions in several wavelet families were tested. The results show that the SVM classifier with the db4 wavelet base function in the db wavelet family has the best fault diagnosis accuracy.

This method provides a practical candidate for the fault diagnosis of rolling bearings in the industrial applications.

The main objective of the paper is to explore the theoretical correlation of base oil viscosity in grease and to study the effect of grease grade on mechanical vibrations associated with the damaged rolling bearings.

For theoretical purposes, formulation theory of dimensional analysis was implemented. Experiments were then performed on the test bearings lubricated with three different types of greases, namely, SKF LGHP2, SKF LGMT3 and SKF LGWA2.

The numerical results obtained from the theoretical model along with the results of experiments show that the vibration amplitudes of the defective bearings come down to a lower level when it is lubricated with the grease of a higher base oil viscosity.

The promising results from the theoretical model make it usable for the practical rotating machineries applying a variety of the rolling bearings. Consequently, if the bearing is not severely damaged, its performance can be increased by lubricating it with thicker grease.

Despite many significant contributions in the field to detect the presence of defects, not many studies have been performed that relate the lubrication condition of the rolling bearings with the vibration response, because around 50-75% of the bearing failures are attributed to be lubrication related. Hence, there is need to develop a mathematical model that can correlate the vibration severity of the bearings with viscosity of the lubricant oil in the greases along with other design and operating parameters.

ROLLING‐element bearings for aircraft turbine engine mainshaft applications are generally specified to be made of AISI M‐50 steel. Current aircraft turbine engine manufacturers' material specifications require a double vacuum melted (VIM‐VAR, for vacuum induction melt, vacuum arc smelt) AISI M‐50 steel for mainshaft bearings. With this material, ball bearing fatigue lives of nearly 100 times AFBMA predicted life have been obtained. Reduction in inclusion content, trace elements, and interstitial gas content is considered responsible for a major portion of this life advancement. AISI M‐50 also has the hot hardness and hardness retention ability for long‐life rolling‐element bearing operation at temperatures up to 588 K (600°F).

The purpose of this study was to examine the effect of the magnetic field to the friction coefficient in the rolling element bearings which exists in electric motors.

To achieve this, the test rig was modified to adjust the density of the magnetic flux applied to the rolling ball element bearing. Experiments were carried out in the magnetic field from 0 to 7.5 mTesla at magnetic flux density range from 15, 40 and 65 N constant loads. Also, its rotary speed selected as 100, 200, 400, 800 to 1200 rpm, respectively.

In the majority of the experiments, it was observed that the magnetic field affected the friction coefficient. This influence reduced the friction coefficient in some experimental conditions and increased in some of them.

In the literature, there are very few studies on the effect of magnetic flux density to the friction coefficient in these rolling element bearings. It has become clear that more studies have been conducted on the effects of the magnetic field and/or electrical current on bearing damages and failures. This aspect is a study with specificity.

Rolling bearings often cause engineering accidents due to early fatigue failure. The study of early fatigue failure mechanism and fatigue life prediction does not consider the integrity of the bearing surface. The purpose of this paper is to find new rolling contact fatigue (RCF) life model of rolling bearing.

An elastic-plastic finite element (FE) fatigue damage accumulation model based on continuous damage mechanics is established. Surface roughness, surface residual stress and surface hardness of bearing rollers are considered. The fatigue damage and cumulative plastic strain during RCF process are obtained. Mechanism of early fatigue failure of the bearing is studied. RCF life of the bearing under different surface roughness, hardness and residual stress is predicted.

To obtain a more accurate calculation result of bearing fatigue life, the bearing surface integrity parameters should be considered and the elastic-plastic FE fatigue damage accumulation model should be used. There exist the optimal surface parameters corresponding to the maximum RCF life.

The elastic-plastic FE fatigue damage accumulation model can be used to obtain the optimized surface integrity parameters in the design stage of bearing and is helpful for promote the development of RCF theory of rolling bearing.

The purpose of this study is to reveal the tribological performance of the textured rolling bearing.

In the present study, the oil film pressure distribution and load capacity analysis method are established, which integrate the micro-texture model and Hydrodynamic lubrication (HL) methods. The tribological performances of the textured rolling bearing under the various working condition, texture dimension and texture type are investigated systematically.

The results show that the oil film load capacity increases with the increase in the texture size. As the texture depth increases, the oil film load capacity increases first and then decreases, and then the load capacity is the largest at the texture depth range of 3 to 5 µm. In addition, the oil film load capacity of the matching pairs, such as Si4N3-Si4N3, GCr15- Si4N3 and GCr15-GCr15 are compared; the results show that the cases of using ceramic material can improve oil film load capacity of textured rolling bearing.

The current manuscript can be useful for supporting the reliability and life research of textured rolling bearing.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2020-0055

The purpose of this article is to present a new application of pursuit‐based analysis for diagnosing rolling element bearing faults.

Intelligent diagnosis of rolling element bearing faults in rotating machinery involves the procedure of feature extraction using modern signal processing techniques and artificial intelligence technique‐based fault detection and identification. This paper presents a comparative study of both the basis and matching pursuits when applied to fault diagnosis of rolling element bearings using vibration analysis.

Fault features were extracted from vibration acceleration signals and subsequently fed to a feed forward neural network (FFNN) for classification. The classification rate and mean square error (MSE) were calculated to evaluate the performance of the intelligent diagnostic procedure. Results from the basis pursuit fault diagnosis procedure were compared with the classification result of a matching pursuit feature‐based diagnostic procedure. The comparison clearly illustrates that basis pursuit feature‐based fault diagnosis is significantly more accurate than matching pursuit feature‐based fault diagnosis in detecting these faults.

Intelligent diagnosis can reduce the reliance on experienced personnel to make expert judgements on the state of the integrity of machines. The proposed method has the potential to be extensively applied in various industrial scenarios, although this application concerned rolling element bearings only. The principles of the application are directly translatable to other parts of complex machinery.

This work presents a novel intelligent diagnosis strategy using pursuit features and feed forward neural networks. The value of the work is to ease the burden of making decisions on the integrity of plant through a manual program in condition monitoring and diagnostics particularly of complex pieces of plant.