scholarly journals Analysis and Prediction of Wear Performance of Different Topography Surface

Materials ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5056
Author(s):  
Ben Wang ◽  
Minli Zheng ◽  
Wei Zhang

Surface roughness parameters are an important factor affecting surface wear resistance, but the relevance between the wear resistance and the surface roughness parameters has not been well studied. This paper based on the finite element simulation technology, through the grey incidence analysis (GIA) method to quantitatively study the relevance between the wear amount of per unit sliding distance (ΔVs) and the surface texture roughness parameters under dry friction conditions of the different surface topography. A zeroth order six-variables grey model, GM(0,6), for prediction the wear characteristic parameter ΔVs was established, and the experiment results verified that the prediction model was accurate and reasonable.

2017 ◽  
Vol 54 (2) ◽  
pp. 64-71
Author(s):  
A. Leitans ◽  
J. Lungevics ◽  
J. Rudzitis ◽  
A. Filipovs

Abstract The present paper discusses and analyses tribological properties of various coatings that increase surface wear resistance. Four Ti/C-N nanocoatings with different coating deposition settings are analysed. Tribological and metrological tests on the samples are performed: 2D and 3D parameters of the surface roughness are measured with modern profilometer, and friction coefficient is measured with CSM Instruments equipment. Roughness parameters Ra, Sa, Sz, Str, Sds, Vmp, Vmc and friction coefficient at 6N load are determined during the experiment. The examined samples have many pores, which is the main reason for relatively large values of roughness parameter. A slight wear is identified in all four samples as well; its friction coefficient values range from 0,.21 to 0.29. Wear rate values are not calculated for the investigated coatings, as no expressed tribotracks are detected on the coating surface.


2016 ◽  
Vol 75 (3) ◽  
pp. 335-346 ◽  
Author(s):  
Lidia Gurau ◽  
Nadir Ayrilmis ◽  
Jan Thore Benthien ◽  
Martin Ohlmeyer ◽  
Manja Kitek Kuzman ◽  
...  

2021 ◽  
Vol 13 (11) ◽  
pp. 2210
Author(s):  
Zohreh Alijani ◽  
John Lindsay ◽  
Melanie Chabot ◽  
Tracy Rowlandson ◽  
Aaron Berg

Surface roughness is an important factor in many soil moisture retrieval models. Therefore, any mischaracterization of surface roughness parameters (root mean square height, RMSH, and correlation length, ʅ) may result in unreliable predictions and soil moisture estimations. In many environments, but particularly in agricultural settings, surface roughness parameters may show different behaviours with respect to the orientation or azimuth. Consequently, the relationship between SAR polarimetric variables and surface roughness parameters may vary depending on measurement orientation. Generally, roughness obtained for many SAR-based studies is estimated using pin profilers that may, or may not, be collected with careful attention to orientation to the satellite look angle. In this study, we characterized surface roughness parameters in multi-azimuth mode using a terrestrial laser scanner (TLS). We characterized the surface roughness parameters in different orientations and then examined the sensitivity between polarimetric variables and surface roughness parameters; further, we compared these results to roughness profiles obtained using traditional pin profilers. The results showed that the polarimetric variables were more sensitive to the surface roughness parameters at higher incidence angles (θ). Moreover, when surface roughness measurements were conducted at the look angle of RADARSAT-2, more significant correlations were observed between polarimetric variables and surface roughness parameters. Our results also indicated that TLS can represent more reliable results than pin profiler in the measurement of the surface roughness parameters.


2018 ◽  
Vol 1148 ◽  
pp. 109-114
Author(s):  
M. Balaji ◽  
C.H. Nagaraju ◽  
V.U.S. Vara Prasad ◽  
R. Kalyani ◽  
B. Avinash

The main aim of this work is to analyse the significance of cutting parameters on surface roughness and spindle vibrations while machining the AA6063 alloy. The turning experiments were carried out on a CNC lathe with a constant spindle speed of 1000rpm using carbide tool inserts coated with Tic. The cutting speed, feed rate and depth of cut are chosen as process parameters whose values are varied in between 73.51m/min to 94.24m/min, 0.02 to 0.04 mm/rev and 0.25 to 0.45 mm respectively. For each experiment, the surface roughness parameters and the amplitude plots have been noted for analysis. The output data include surface roughness parameters (Ra,Rq,Rz) measured using Talysurf and vibration parameter as vibration amplitude (mm/sec) at the front end of the spindle in transverse direction using single channel spectrum analyzer (FFT).With the collected data Regression analysis is also performed for finding the optimum parameters. The results show that significant variation of surface irregularities and vibration amplitudes were observed with cutting speed and feed. The optimum cutting speed and feed from the regression analysis were 77.0697m/min and 0.0253mm/rev. for the minimum output parameters. No significant effect of depth of cut on output parameters is identified.


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