Study on the influence of round pits arrangement patterns on tribological properties of journal bearings

Yazhou Mao (School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang, China)
Yang Jianxi (Henan University of Science and Technology, Luoyang, China)
Xu Wenjing (Henan Luoyang Railway Information Engineering School, Luoyang, China)
Liu Yonggang (Henan University of Science and Technology, Luoyang, China)

Industrial Lubrication and Tribology

ISSN: 0036-8792

Publication date: 24 July 2019

Abstract

Purpose

The purpose of this paper is to investigate the effect of round pits arrangement patterns on tribological properties of journal bearing. In this paper, the tribological behaviors of journal bearing with different arrangement patterns under lubrication condition were studied based on M-2000 friction and wear tester.

Design/methodology/approach

The friction and wear of journal bearing contact surface were simulated by ANSYS. The wear mechanism of bearing contact surfaces was investigated by the means of energy dispersive spectrum analysis on the surface morphology and friction and wear status of the journal bearing specimens by Scanning Electron Microscopy (SEM) and Energy Dispersive Spectrometer (EDS). Besides, the wearing capacity of the textured bearing was predicted by using the GM (1,1) and Grey–Markov model.

Findings

As the loads increase, the friction coefficient of journal bearing specimens decrease first and then increase slowly. The higher rotation speed, the lower friction coefficient and the faster temperature build-up. The main friction method of the bearing sample is three-body friction. The existence of texture can effectively reduce friction and wear. In many arrangement patterns, the best is 4# bearing with round pits cross-arrangement pattern. Its texturing diameters are 60 µm and 125 µm, and the spacing and depth are 200 µm and 25 µm, respectively. In addition, the Grey–Markov model prediction result is more accurate and fit the experimental value better.

Originality/value

The friction and wear mechanism is helpful for scientific research and engineers to understand the tribological behaviors and engineering applications of textured bearing. The wear capacity of textured bearing is predicted by using the Grey–Markov model, which provides technical help and theoretical guidance for the service life and reliability of textured bearing.

Keywords

Citation

Mao, Y., Jianxi, Y., Wenjing, X. and Yonggang, L. (2019), "Study on the influence of round pits arrangement patterns on tribological properties of journal bearings", Industrial Lubrication and Tribology, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ILT-07-2018-0264

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Publisher

:

Emerald Publishing Limited

Copyright © 2019, Yazhou Mao and Yang Jianxi.

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


1. Introduction

The journal bearing is an important mechanical component supporting the relative motion of shaft parts. It had an important application in high-speed, high-precision and heavy load (Mao et al., 2018, 2019). The friction and wear of journal bearing is an important factor affecting the life and efficiency. The traditional principles of tribology held that the smoother the surface of contact, the smaller the friction and wear (Zhao et al., 2011). However, research results showed that the tribological properties of the contact surface could be effectively improved by processing different types of surface texturing on the contact surface (Usman and Park, 2018; Waldemar et al., 2018; Yin et al., 2018). Surface texture is called surface micro-modeling, which can reduce friction by machining a certain shape on the contact surface.

Over the several decades, circular micro dents were widely used in research because of its simple structure and easy processed. The surface texture arrangement had an effect on the tribological behavior of bearing, the reliability and service life were directly affected (Jin et al., 2017). Thus, the tribological behavior and wear mechanism of texture arrangement needed to be investigated. The common surface texture included circular, elliptical, spherical (Ashwin et al., 2013; Bai et al., 2011; Ma and Zhu, 2011), diamond, groove (Podgornik et al., 2012) and cone (Siripuram and Stephens, 2004; Pratap and Patra, 2018). Because the circular pit was easy to be processed and manufactured, it was the first choice for study the tribological behavior of surface texture arrangement. In this work, the arrangements of round pits were selected as the research object for the tribological behavior of surface texture. The tribological properties of journal bearings were influenced by texture arrangement, while the tribological properties of single-scale surface pattern arrangement with circular pits under lubricant and dry friction were studied. The results showed that single-scale surface pattern arrangement with circular pits could reduce friction and wear under lubricant (Hua et al., 2017). With the change of micro-dents radius under the surface, texture arrangement could improve tribological properties and bearing capacity (Li and Wang, 2013; Wang and Zhu, 2014). The friction coefficient of grid surface texture arrangement was smaller and more stable than that of the dimple texture arrangement and groove texture arrangement under the same conditions (Wang et al., 2017). The friction and wear of frictional pairs could be effectively reduced by selecting the appropriate textured area ratio under a certain arrangement (Rapoport et al., 2008; Hu and Hu, 2012; Xu et al., 2017). Other works studied the effect of the arrangement of compound dimples on the tribological properties. The results showed that compound dimples texture could reduce friction coefficient (Segu and Hwang, 2016). Especially, the effect of single-scale surface pattern and multi-scale surface pattern fabricated by roller-coining or direct laser interference patterning on the frictional performance of journal bearings were studied. The results showed greatly reduced coefficients of friction for all patterned samples (Grützmacher et al., 2018). In addition, the effect of different texture densities on the performance of a tilting pad thrust bearing were studied. It found that the single-scale surface pattern arrangement with different texture densities could only achieve minor improvement in terms of friction (Gropper et al., 2018). The surface texture friction reducing mechanism and implication for wear under different frictional regimes were investigated by Gachot et al. (2017). The above scholars have done many research works on surface texture to improve tribological performance of frictional pairs, but there are few studies on the tribological properties of surface texture bearing with multi-scale surface patterns arrangement of circular pits. Not only wear mechanism have not been investigated, but also the wearing capacity prediction is rarely reported.

Based on the M-2000 friction and wear tester and ANSYS software, the tribological properties of textured bearing samples with multi-scale surface arrangement patterns were studied. The friction and wear mechanism of textured bearing sample was explored by the energy dispersive spectroscopy of surface micro-morphology. In addition, the friction and wear status were investigated by using the Energy Dispersive Spectroscopy (EDS) and the Scanning Electron Microscopy (SEM) in this work. In following section, the GM (1,1) and Grey–Markov models were used to predict the wear capacity of textured bearing. The prediction method provided technical help and theoretical guidance for the service life and reliability of textured bearing.

2. Experiment

2.1 Preparation

In the work, the arc surface of test specimen was used to simulate tribological properties of journal bearing. The YLP-MDP152-20 three-dimensional fiber laser marking machine was used to process the surface texture of the workpiece. The type of fiber laser marking machine uses a diode-pumped short-pulse Nd: YANG laser, wavelength 1,064 nm, the indication type of laser-making machine is LD red light and wavelength 650 nm, output power is less than 5mW, repetition frequency 10KHz, laser pulse duration 8 ns, cooling by air cooling, operating environment temperature approximately 15°C-35°C, humidity requirements 40-80 per cent, the foundation amplitude is less than 50 μm, the vibration acceleration is less than 0.05 g and the machine power consumption is 0.5KW.

The grinding disc material used in the experiment is GCr15 bearing steel, while the surface hardness is HRC55-60 after quenching. According to the specification parameter requirements of the M-2000 friction and wear tester, the structural size of grinding disc and test sample is shown in Figure 1.

The thickness of the friction pair is 10 mm; the width of the sample is 30 mm; and the diameter of the grinding disc match with it is 50 mm. In the work, the semi-finished product and grinding disc were fabricated by required size and brass sample without heat treated. The surface hardness of the machined brass textured specimen is 266.5 HV, and the surface texturing brass specimen is shown in Figure 2(a). The partial schematic view of surface texturing of the Figure 2(a) is as shown in Figure 2(b).

2.2 Sample design

The material used in the experimental study is brass. 1# sample is smooth bearing specimen, that is, the textured area ratio, diameter, spacing and depth are 0. The area ratio of other bearing samples (2#, 3# and 4#) are 18.874 per cent, and the texturing diameters are 60 μm and 125 μm, while the spacing and depth are 200 μm and 25 μm, respectively. The surface texture with different arrangement are shown in Figure 3. In Figure 3, φ1 is angle of the displacement, and π is test sample bearing unfolding angle.

2.3 Experimental method

The M-2000 friction and wear tester was used in the experiment as shown in Figure 4. The M-2000 friction and wear tester were used to simulate the tribological properties of the journal bearing specimen with different arrangement patterns.

In the work, four kinds of brass texture specimens with different arrangement patterns were selected for experimental study. Before each test, the specimen was wiped with acetone, dried or air dried with a cold air blower to remove hard particles and debris attached to the surface. During the experiment, the lubricating oil dripping speed was 2 ml/min. The JUSTAR J400 15w-40 lubricating oil was selected in the work. The basic performance parameters of lubricating oil are shown in Table I.

The surface texture bearing sample during the experiment was usually in a boundary lubrication state and the roughness of the sample would affecting the tribological behavior. Any object in nature cannot be absolutely smooth, and the object must have a certain surface roughness. In fact, because of the existence of roughness on the surface of the experimental sample material, the boundary lubrication was generally in the state of mixed lubrication on the surface of the experimental sample material.

Surface texture bearing specimens with different arrangement patterns reached a period of time (30 minutes) test. The specimens were carefully remove from the tester and placed on the table for cooling. The test samples were cleaned with acetone and then dried by a cold air blower. Thus, the friction coefficient of sample is as follows:

(1) μ=QP=TR×P

where μ represents the friction coefficient; Q represents the friction force; P represents the normal load; T represents the friction torque; and R represents the bearing radius.

3. Results and discussion

3.1 The influence of load on friction performance of surface texture bearings

The effect of different loads on the friction performance of specimens with different arrangement patterns are investigated. The spindle speed was 200 rpm, the loads were 200 N, 400 N, 600 N, 800 N, 1,000 N and 1,200 N. The relationship between loads and friction coefficient of specimens with different arrangements is shown in Figure 5.

In Figure 5, as the external loads increased, the friction coefficient of bearing sample decreased gradually. The reason was that the friction coefficient of the bearing sample decreased with the increase of external load under the combined action of the friction pair normal loads and friction forces. In addition, with the increased of external loads, the oil film thickness on the surface of bearing specimen become thinner and the molecular spacing of lubricating oil on the surface was gradually compressed, which resulted in shorter oil film molecular spacing, the tighter oil film and the denser oil film thickness. Not only that, the hydrodynamic effect of bearing pair was more prominent with the increase of loads. Therefore, a reduction in the friction coefficient of friction pair was caused.

When the loads of surface specimens were higher than 800 N, the friction coefficient increased gradually. The reasons were as follows: first, the plastic deformation of surface texture samples occurred with the load increase gradually. The lubricating in the pits was extruded to the surface of the samples, which leaded to the turbulent flow on the surface of textured specimen and caused the friction coefficient to increase gradually. Second, the oil film thickness of the friction pair was compressed gradually, and the peaks of rough surface of samples were involved in the friction, which resulted in more grinding particles and made the friction coefficient increase steadily.

3.2 The influence of rotational speed on friction performance of surface texture bearings

The effect of different rotational speeds on the friction properties of bearing samples with different arrangements was investigated. In the experiment, the load was set 1000 N, the rotational speeds were 200 rpm and 400 rpm. The relationship between bearing sample and temperature and friction coefficient is shown in Figures 6(a) and (b).

In Figures 6(a) and (b), the friction coefficient decreased with the increase of rotational speed. First, the lubricating oil film of bearing pair, which was in contact with each other in the initial state, has not yet been formed and the hydrodynamic effect gradually appeared along with the change of rotating speed. The shaft and bearing were gradually separated by the forming of the lubricating oil film, and the mutual friction of roughness peaks between shaft and bearing were reduced. Second, the brass substrate material was relatively softer to accommodate a part of hard grinding particles. The existence of textured bearing pits as a container was capable of store lubricating oil. However, surface texture pits could effectively store grinding particles so as to reduce the occurrence of three-body friction and wear, which played a role in anti-friction and lubrication to a certain extent. Finally, according to the principle of function conversion, the laser beam energy and light energy emitting by the laser emitter were converted into heat energy when the laser beam manufacturing micro-modeling on the journal bearing samples. The increasing heat energy directly acted on the sample surface and caused local area changes. The tissue hardness of the local area of textured bearing specimen was changed to a certain extent and the local area of the surface texture was hardened to form a hardened layer. It made the textured bearing specimens show a better antifriction and lubrication during the experiment.

Surface texture bearing samples would inevitably cause surface friction fever, deformation and even wear on the surface of the specimens under the action of rotational speed, which would have a significant impact on the temperature of the surface texture journal bearing specimens. The lubricating oil has a viscosity–temperature effect. The temperature would lead to a change in the viscosity of the lubricating oil, which in turn reduced the load-bearing capacity and lubrication.

In Figures 6(a) and (b), as the rotational speed increased, the temperature of the bearing specimens increasing gradually. It was that the higher the rotational speed, the more frictional heating would be generated by the friction pair that is the higher the rotational speed, the faster the temperature raised. The temperature build-up caused by friction fever of 2#, 3# and 4# samples at the same rotational speed were lower than 1# bearing specimen. This indicated that the existence of surface texture could reduce the excessive temperature build-up of friction pair. In addition, the improper arrangement (3#) of surface texture would cause the temperature of the specimen to rise. On the contrary, the proper arrangement could not only reduce the failure of lubricating oil film by excessive temperature build-up, but also reduced friction and improved the service life of bearing pair.

3.3 Friction and wear analysis

The different loads and rotational speeds would bring different effects on the specimen with different arrangement patterns during the experiment. Supposed that the actual area of the relative sliding surface was A. The friction force F on the surface of sample in the mixed lubrication state was expressed as follows:

(2) F=A[αwτs+(1αw)τl]+Fp

where αw is the percentage of solid–solid contact area on the relative sliding surface in the contact area, αw = Am/A. Am is solid–solid contact area. τs and τl represent the shear strength of solid–solid and fluid surface, respectively. Fp represents resistance caused by furrows on the surface of experimental material.

The total load W of the relative sliding surface specimen was expressed as follows:

(3) W=A[αwp0+(1αw)pl]

where p0 and pl represent the pressure of shaping flow of sample and the pressure of the lubricating oil film, respectively. Supposed an average pressure was Pe, then W was expressed as follows:

(4) W=Ape

So the friction coefficient on the surface of the relative sliding specimen was expressed as follows:

(5) μ=FW=αw(τspe)+(1αw)τlpe+fp

The relationship between friction coefficient and specimen with the spindle speed 200 rpm and normal load pressure 1,000 N with different arrangement were shown in Figure 7.

The friction coefficient of bearing samples with different arrangements fluctuated greatly at the initial stage, and then, the following rule was similar, that is, the friction coefficient decreased and tended to be stable gradually. The reason for the occurrence of this phenomenon was that the specimen material relatively softer, and the bearing steel and the brass specimen were extruded and deformed in the process of running. Therefore, the running-in phenomenon appeared in the initial stage of the experiment. After the end of running-in period, the friction coefficient tended to be stable gradually because of the good friction matching between the circular arc surface of the sample and the GCr15 bearing steel friction disc. The bearing specimen with different arrangement patterns showed different anti-friction effects and the existence of surface texture could reduce friction better.

In Figure 7, the results of bearing specimens experiment expressed the rules of the tribological behaviors of the bearing specimens macroscopically. But the results of bearing samples experiment could not show the state of friction and wear under the contact state. To show the friction and wear state of bearing specimen under the contact state, the contact state of bearing specimen was simulated by ANSYS. The true value of friction coefficient μ must be estimated before ANSYS simulate the contact state.

Because of few data collected in the process of experiment, the poor information fusion technology was used to estimate the true value for friction coefficient μ in this paper. The validity and correctness of the technology had also been verified by many scholars (Xia, 2008; Xia et al., 2016). In this work, the membership function method, the maximum membership method, the arithmetic mean method and the rolling average method were selected. After three times of information fusion, when A range (δ) value meets the requirement of range criterion, the following equation is obtained:

(6) δj=maxi=1mX0kFjmini=1mX0kFjε

where X0kFj represents the solution sets for the calculation results of the k-th mathematical method after the j − 1 fusion; δj and ε represent the range value after the j-th fusion and arbitrarily small real values, respectively.

The fusion value Xtrue of the estimated values Xm after three times true value fusion was approximately equal to friction coefficient μ value, as shown in Table II.

When the surface to surface contact analysis was carried out in ANSYS, because the bearing had an axisymmetric characteristic, a quarter of the bearing was selected for analysis in this work. The results of ANSYS simulation showed the friction stress nephograms of bearings which are shown in Figure 8.

The friction stress of bearing specimens indicated that the resultant force of all external loads that was applied to the bearing sample was converted into friction stress. Therefore, the simulation results of the friction stress could reflect the friction and wear conditions on the surface of the bearing specimens.

In Figure 8, the comparison between the smooth-bearing specimen (a) and textured-bearing specimens [(b), (c) and (d)] showed that the friction stress on the bearing surface exhibited a certain fluctuation when the load and speed were fixed. The friction stress of the smooth-bearing specimen was more concentrated but distributed unevenly, and it aggravated the friction and wear of bearing specimen. However, the friction stress of textured bearing was dispersed and evenly distributed, which resulted in less friction and wear. The existence of texture made the friction stress on the surface of textured bearing more uniform and its anti-wear behavior better. In other words, the existence of texture could effectively reduce friction and wear.

The friction and wear behavior of samples with different arrangements were different. In many arrangements of the surface texture bearing specimens, 4# textured-bearing specimen was the best, and 2# textured-bearing specimen was superior to 3# textured-bearing specimen. Therefore, it could be concluded that the arrangement pattern of the 4# bearing specimen was the best in many arrangement patterns, which could effectively improve the friction stress distribution and the anti-friction behavior of the bearing specimens. The correctness of simulation results is needed to further be verified by the friction and wear test in the following section.

The correctness of simulation results are verified. The test kept the same conditions as the simulation: the load and rotational speed of bearing samples with different arrangement patterns were 1,000 N and 200 rpm, respectively. The wearing capacity of bearing sample after a period of friction and wear test was shown in Figure 9. In Figure 9, the wear rates of specimens with different arrangements were different. The wearing capacity of the 1# bearing specimen was the most serious and was 0.88 mg, which was much higher than the other specimens, while the wear amounts of the 2#, 3# and 4# specimens were reduced by 36.4, 28.4 and 53.4 per cent, respectively, compared with the 1# bearing specimen. The results showed that the 4# sample had the best anti-friction effect, then the 2# sample and then the 3# sample.

In Figure 8, the results of ANSYS simulation of friction stress were consistent with the results of the samples wear test in Figure 9. Thereby, the friction stress could be used to reflect an important index of anti-wear behavior of the sample and had a certain practical foundation. Meanwhile, the correctness of simulation results was verified accordingly. According to the friction stress nephogram of bearing samples in Figure 8, the optimal arrangement pattern was determined, which was verified accordingly by the agreement with the friction and wear test results.

3.4 Analysis of friction and wear mechanism

The surface micro-wear morphologies of brass specimen with different arrangements are shown in Figure 10. In Figure 10, furrows and wear debris were found on the surfaces and the number, depth and wear debris were different. The friction and wear of smooth bearing was more serious. There were two reasons for this phenomenon. One reason was that the smooth specimen could not store oil and wear particles. The wear particles scattered on the surface and caused three-body friction, which led to the occurrence of furrows. The other reason was that the brass specimen was softer; however, the surface hardness of GCr15 bearing steel was higher than brass sample. Lack of lubricant on the surface of the smooth bearing resulted in the lack of good lubricating effect. Friction aggravated the increase of wear particles, which further resulted in the friction and wear in the process of experiment.

The results showed that the main friction and wear mechanisms of brass specimens were friction particle wear. The existence of micro-pits could effectively store wear particles and lubricating oil, which reduced the occurrence of wear and three-body friction caused by the direct contact of the journal bearing specimen. The anti-friction and lubricating effect of the bearing specimen with different arrangements were different, but the best arrangement pattern for anti-wear and anti-friction behavior was the cross-arrangement pattern.

To sum up, different arrangement patterns led to different anti-friction behavior and lubrication effect. To some extent, improper arrangement patterns not only did not play a role in anti-wear and anti-friction performance, but also it aggravated the friction loss of bearing pair.

The difference of chemical composition on the surface of specimens after friction and wear test is further investigated. The EDS system was used to analyze the wear track of the wear surface. The spectral analysis of EDS for textured specimens were similar, and the surface spectra of smooth and textured specimens were shown in Figures 11(a) and (b). The percentage of elements detected on the surfaces of the smooth and textured specimens were shown in Table III. In Table III, the highest proportion of Cu and Zn elements were mainly from the brass specimen itself, and the detected C and O elements were derived from the main chemical elements in the lubricating oil remain on the surface of the brass specimen during the experiment. The difference between Figures 11(a) and (b) was the Fe element. Because the hardness of GCr15 bearing steel was higher than brass samples, the transfer of Fe element only occur from GCr15 bearing steel to brass specimens. Thereby, the friction and wear state of smooth surface was worse than textured specimens.

3.5 Prediction and hypothesis testing of wearing capacity of surface texture bearing

The research results showed that the 4# textured bearing specimen had the optimal anti-friction effect. In Figure 5, the friction would be aggravate if the surface load of the bearing specimen was higher than 800 N. The following focus on the further study on wear condition of the 4# textured-bearing specimen with different loads. The 4# textured-bearing sample with different loads at 200 rpm was tested, and the corresponding wear capacity was predicted by using Grey–Markov model. It provided technical help and theoretical guidance for the service life and reliability of bearing.

In the process of the experiment, few data and poor information were obtained. Therefore, a grey system theory was proposed by professor Deng (2002). Based on GM (1,1) it was known that grey prediction needed few data and simple calculation, and the prediction model of GM (1,1) was an exponential curve. But it was poor in fitting data series with large fluctuation and low prediction accuracy (Li et al., 2015).

According to the grey system theory, the GM (1,1) prediction model for wearing capacity of the 4# textured bearing specimen as follows:

(7) x^(0)(t+1)=0.43007e0.0339t

However, the Markov prediction model (Ramasso and Gouriveau, 2010) was suitable for problems with large volatility. Thus, the advantages of the two methods were combined to predict the data sequences with large random fluctuation. The predicted wearing capacity of bearing specimen are as shown in Figure 12.

In Figure 12, both prediction models could predict the bearing wearing capacity. However, there were some differences between the prediction results of the two models and test results, in which one was more significant for both prediction results. It was necessary to make a hypothesis testing on the significance of the both prediction results, and the significance of the prediction results was illustrated by Student’s test.

If Di = YiXi (i  =1, 2, … 12) was a sample from normal population N (μD, σD2), then μD and σD2 were unknown. The hypothesis testing was expressed as follows:

(8) H0:μd>0H1:μd<0

The following t-statistics is used as a test statistics:

(9) t=x¯dsd/n

where xd and sd represent the mean and standard deviation of the difference of paired observations sample, respectively. n represents the number of paired samples:

(10) t=x¯dsd/n=9e50.00472/12=0.0661

The significance of the prediction models at different significance levels (α = 0.01 and 0.05) were discussed and refer to t distribution table tα/2(11) = t0.005(11) = 3.1058 and tα/2(11) = t0.025(11) = 2.2010. Thus, the rejection region was known as follows:

(11) {tt0(n1)}={t3.1058&t2.2010}

According to t-values of the sample hypothesis testing, t = −0.0661 < −3.1058 and −2.2010 were obtained with the confidence levels α = 0.01 and 0.05. The t values do not fall within the rejection region. So the primary hypothesis H0 was accepted and alternative hypothesis H1 was rejected. Therefore, it was reasonable to believe that there was a significant difference between the prediction results of both prediction methods. And it is inferred from that the prediction results of Grey–Markov model was better than GM (1,1) prediction results.

In Figure 12, the calculation results showed that the average relative error of GM (1,1) was 0.962 per cent, and the average relative error of Grey–Markov model was 0.603 per cent. The average prediction accuracy of the Grey–Markov model increased by 0.36 per cent than GM (1,1). Thus, the Grey–Markov model was more accurate and it fit the experimental values better than the GM (1, 1).

4. Conclusions

In this present work, a series of experiments were carried out and the tribological properties of bearing with different arrangement patterns were investigated. By experiments, observation, ANSYS analysis and comparison, few conclusions were summarized as follows:

  • The tribological properties of bearing were affected by arrangement pattern. The proper arrangement pattern could not only reduce the failure of lubricant by excessive temperature build-up, but also improve the service life of bearing pair.

  • The main friction method of the bearing pair was three-body friction; the existence of texture could effectively reduce friction and wear. Besides, the cross-arrangement pattern was the best in the selected arrangement patterns.

  • The Grey–Markov model had a higher prediction accuracy than GM (1,1); the wearing capacity prediction results of 4# textured bearing sample were more accurate and fit the experimental values better.

Figures

Size of test specimen (a) and grinding disc (b)

Figure 1

Size of test specimen (a) and grinding disc (b)

Surface texture image of brass specimen

Figure 2

Surface texture image of brass specimen

Samples number and arrangement forms

Figure 3

Samples number and arrangement forms

M-2000 friction-wear testing site diagram

Figure 4

M-2000 friction-wear testing site diagram

Relationship between load and friction coefficient

Figure 5

Relationship between load and friction coefficient

Relationship between bearing samples and friction coefficient and temperature

Figure 6

Relationship between bearing samples and friction coefficient and temperature

Friction coefficient – time diagram

Figure 7

Friction coefficient – time diagram

Friction stress nephogram of bearing specimen

Figure 8

Friction stress nephogram of bearing specimen

Wearing capacity of specimens after wear experiment

Figure 9

Wearing capacity of specimens after wear experiment

Morphology of brass specimen

Figure 10

Morphology of brass specimen

Surface composition analysis of samples

Figure 11

Surface composition analysis of samples

The experimental values and predictive values of two models

Figure 12

The experimental values and predictive values of two models

Basic parameters of the great wall JUSTAR J400 15w-40 lubricating oil

Parameters Units Values
ISO viscosity grade 40
Flash point ºC 230
Pour point ºC −39
Viscosity in 100ºC m2/s 15.66
Density kg/m3 900

The estimated true value of bearing friction coefficient μ value

Estimate true values Xm
Arrangements Membership function method Maximum membership method Arithmetic mean method Rolling average method Fusion value Xtrue
1# 0.026 0.025 0.026 0.026 0.026
2# 0.017 0.017 0.017 0.017 0.017
3# 0.018 0.018 0.018 0.018 0.018
4# 0.015 0.015 0.015 0.015 0.015

Surface composition of brass specimens after wear experiment

Smooth surface Textured surface
Elements wt% at% wt% at%
Cu 68.12 48.21 66.96 46.83
Zn 20.33 16.95 19.84 15.18
Fe 0.41 0.23
C 9.60 30.64 11.91 35.87
O 1.54 3.97 1.29 2.12

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Number 50975075); Henan Provincial Key Laboratory of High Performance Bearing Technology (Number 2016ZCKF02); and Major Projects of Henan Province Foundation and Advanced Technology Research Project (Number 152300410083). The authors would also like to express their sincere thanks to the anonymous referees and the editor for their constructive comments.

Corresponding author

Mr Yazhou Mao can be contacted at: myzlcc@163.com