Systematic selection and evaluation of relevant surface roughness parameters for the characterisation of the innovative RPM-Synchronous Grinding process

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.

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Model for surface-roughness parameters determination in a virtual machine shop environment

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-008-1441-5 ◽

2008 ◽

Vol 40 (11-12) ◽

pp. 1137-1147 ◽

Cited By ~ 5

Author(s):

N. Bilalis ◽

M. Petousis ◽

A. Antoniadis

Keyword(s):

Surface Roughness ◽

Virtual Machine ◽

Roughness Parameters ◽

Machine Shop ◽

Surface Roughness Parameters

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Evaluation of Process Parameters in Machining of AA6063 Alloy

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1148.109 ◽

2018 ◽

Vol 1148 ◽

pp. 109-114

Author(s):

M. Balaji ◽

C.H. Nagaraju ◽

V.U.S. Vara Prasad ◽

R. Kalyani ◽

B. Avinash

Keyword(s):

Surface Roughness ◽

Regression Analysis ◽

Process Parameters ◽

Single Channel ◽

Cutting Speed ◽

Cutting Parameters ◽

Depth Of Cut ◽

Roughness Parameters ◽

Surface Roughness Parameters ◽

Aa6063 Alloy

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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