Non-contact Surface Roughness Measurement Research Articles

Non-contact surface roughness measurement of blasted specimens using machine vision technique

Non-contact surface roughness measurement of blasted specimens using machine vision technique

Research on Rapid Measurement Technology of Roughness Based on Light Scattering

The roughness is an important parameter to evaluate the parts surface quality, so it is very important to measure the surface roughness of high-precision parts. In order to meet the needs of rapid and non-contact measurement of surface roughness, a new method based on optical scattering distribution is proposed in this paper. By analyzing the modulation effect of surface roughness on incident light, the relationship between surface roughness and scattering distribution is established. Based on the analysis of the characteristics of light source, detector and their relative position, the scattered light distribution measurement system is constructed. In the measurement system, the surface roughness is measured by real-time acquisition of scattering distribution. The roughness of different samples is measured by this method and white light interferometer, and the measurement standard deviation is less than 0.15nm. The measurement results show that this method is feasible and effective.

Recent Trends in Non-Contact Surface Roughness Measurement by White Light Interferometry

Recent Trends in Non-Contact Surface Roughness Measurement by White Light Interferometry

Performance of a new hybrid cutting-abrasive tool for the machining of fibre reinforced polymer composites

A new hybrid cutting-abrasive machining tool (turn-grind) is detailed for high-quality machining of fibre reinforced polymer (FRP) composites, comprising single point carbide inserts electroplated with multi-layers of diamond abrasives 120 μm grain size, to form an abrasive region adjacent to an abrasive-free cutting edge. Experimental data are presented for turning tubes of CFRP and GFRP. The surface quality of workpieces after machining was evaluated through surface roughness measurements and SEM imaging. Cutting-only caused more defects such as delamination and fibre to pull out. Compared with cutting-only, contact and non-contact measurement of surface roughness (Ra) in both axial and radial directions showed an increase for CFRP and GFRP with roundness error reduced to 50%. No significant increase in cutting force was observed.

Non-contact surface roughness measurement using laser speckle technique

This paper deals with selected contact type stylus method and non-contact type machine vision method using laser speckle for components prepared by grinding of AISI 1040 steel with a variety of wheels and varied depth of cut. In this interactive study, Optical method based on statistical properties of binary images is proposed for machined surfaces. Grounded metal surfaces are used to develop a binary digitized speckle pattern by a beam of He-Ne laser light source. High end camera is used to capture the image of a speckle pattern. White to black pixels ratios is computed from the binary images using image processing toolbox in Matlab. The correlation is developed between white to black pixels ratio and measured two-dimensional surface roughness parameter. Two-dimensional surface roughness parameters are recorded using a contact-type surface profilometer. The results which opted, clearly supports that these parameters have a relationship with a degree of surface roughness. A linear relationship is observed between parameter obtained from proposed technique and measured value of surface roughness using surface profilometer. The statistical analysis represents the performance of maximum relative error in prediction of surface roughness is 9%.

In-situ measurement of surface roughness using chromatic confocal sensor

Surface roughness is an important characteristic which affects the quality, performance and lifetime of many types of industrial products, ranging from mechanical and biomedical parts to semiconductors and optics. In recent years, in-situ measurement for surface roughness is increasingly demanded to provide real-time feedback and reduce systematic errors of realignment and repositioning during manufacturing. Commercially available instruments, such as stylus profilometer, confocal laser scanning microscope and coherence scanning interferometer, are limited to a relatively low measurement speed and difficult for in-situ measurement. In this paper, an in-house developed surface measuring system using chromatic confocal sensor was integrated into a mass finishing cell to perform in-situ and non-contact surface roughness measurement. The surface roughness parameters are calculated and evaluated according to ISO 4287 and ISO 4288. From the preliminary experiments, it was verified that the relative error of surface roughness measurements can be kept within 5%.

Measurement of Angle Encoder Disk Surface Parameters

This research covers a novel approach to non-contact angle encoder disk roughness measurements while using the proposed system attached to the rotary table with an implemented reference angle encoder. Non-contact surface measurement methods are analyzed in the paper. The proposed non-contact surface roughness measurement technique involves the use of a conventional optical disc laser reading system as a cost saving solution. Assets and drawbacks as well as detailed analysis of the measurement procedure are given in the paper. The structure of the device is presented within this article together experimental results.

Non-Contact Surface Roughness Measurement by Implementation of a Spatial Light Modulator.

The surface structure, especially the roughness, has a significant influence on numerous parameters, such as friction and wear, and therefore estimates the quality of technical systems. In the last decades, a broad variety of surface roughness measurement methods were developed. A destructive measurement procedure or the lack of feasibility of online monitoring are the crucial drawbacks of most of these methods. This article proposes a new non-contact method for measuring the surface roughness that is straightforward to implement and easy to extend to online monitoring processes. The key element is a liquid-crystal-based spatial light modulator, integrated in an interferometric setup. By varying the imprinted phase of the modulator, a correlation between the imprinted phase and the fringe visibility of an interferogram is measured, and the surface roughness can be derived. This paper presents the theoretical approach of the method and first simulation and experimental results for a set of surface roughnesses. The experimental results are compared with values obtained by an atomic force microscope and a stylus profiler.

Machine vision method for non-contact measurement of surface roughness of a rotating workpiece

Purpose – This paper aims to propose a non-contact method using machine vision for measuring the surface roughness of a rotating workpiece at speeds of up to 4,000 rpm. Design/methodology/approach – A commercial digital single-lens-reflex camera with high shutter speed and backlight was used to capture a silhouette of the rotating workpiece profile. The roughness profile was extracted at sub-pixel accuracy from the captured images using the moment invariant method of edge detection. The average (Ra), root-mean square (Rq) and peak-to-valley (Rt) roughness parameters were measured for ten different specimens at spindle speeds of up to 4,000 rpm. The roughness values measured using the proposed machine vision system were verified using the stylus profilometer. Findings – The roughness values measured using the proposed method show high correlation (up to 0.997 for Ra) with those determined using the profilometer. The mean differences in Ra, Rq and Rt between the two methods were only 4.66, 3.29 and 3.70 per cent, respectively. Practical implications – The proposed method has significant potential for application in the in-process roughness measurement and tool condition monitoring from workpiece profile signature during turning, thus, obviating the need to stop the machine. Originality/value – The machine vision method combined with sub-pixel edge detection has not been applied to measure the roughness of a rotating workpiece.

Surface roughness extraction based on Markov random field model in wavelet feature domain

Based on the computer texture analysis method, a new noncontact surface roughness measurement technique is proposed. The method is inspired by the nonredundant directional selectivity and highly discriminative nature of the wavelet representation and the capability of the Markov random field (MRF) model to capture statistical regularities. Surface roughness information contained in the texture features may be extracted based on an MRF stochastic model of textures in the wavelet feature domain. The model captures significant intrascale and interscale statistical dependencies between wavelet coefficients. To investigate the relationship between the texture features and surface roughness Ra, a simple research setup, which consists of a charge-coupled diode camera without a lens and a diode laser, was established, and the laser speckle texture patterns are acquired from some standard grinding surfaces. The research results have illustrated that surface roughness Ra has a good monotonic relationship with the texture features of the laser speckle pattern. If this measuring system is calibrated with the surface standard samples roughness beforehand, the surface roughness actual value Ra can be deduced in the case of the same material surfaces ground at the same manufacture conditions.

Quality improvement of machine vision-based non-contact inspection of surface roughness in turning through adaptive neuro-fuzzy interference system

Today's competitive global manufacturing scenario drives a strong demand for accurate non-contact automated measurement of surface roughness in turning operations. This paper investigates the potential of various possible combinations of a number of surface image features, such as, statistical features extracted from grey-level co-occurrence matrices, discrete cosine transform coefficient and discrete Fourier transform coefficient, in machine vision-based non-contact measurement of surface roughness of turned AISI1045 steel work pieces. Adaptive neuro-fuzzy interference system (ANFIS) models, each of which utilises a particular combination of the above-mentioned image features for accomplishing non-contact prediction of surface roughness, are developed and compared in this paper. Analyses of experimental data demonstrate that the approach, which utilises statistical features for non-contact measurement of surface roughness, outperforms the other approaches in terms of surface roughness prediction accuracy and yields substantial improvement in the accuracy level of machine vision-based non-contact measurement of surface roughness in turning.

研磨ロボット用光学的表面粗さセンサの研究 （第３報） 異方性表面粗さを有する場合

For the reasons of harsh environment in polishing procedures, an optical, non-contact measurement of surface roughness is better suited to in-process measurement than contact sensors such as a stylus meter. The authors have proposed a new optical method for measuring surface roughness by use of a halogen light source and a CCD camera. Based on the Torrance-Sparrow model, the proposed procedure theoretically converts the data of the reflected light into surface roughness represented in Rq (roughness in root mean square).In this paper, we attempt to apply the proposed method to estimate a ground direction. From the results of the computer simulation and the experiments, the ground direction can be estimated within the error of 10 degrees. Further, the root-mean-square roughness can be evaluated within the error of 5% to the true value.

Noncontact surface roughness measurement of engineering surfaces by total integrated infrared scattering

As precision engineering surfaces are gaining in importance in industry, so are the surface quality requirements. These surfaces have rms roughness typically ranging from some nanometers up to a few micrometers. Although numerous techniques exist for rough surface characterization, from traditional line-scanning stylus profilometers to modern three-dimensional (3-D) measurement instruments, there is a need for a fast, area-covering technique. An efficient method for the characterization of smooth surfaces is elastic light scattering. At visible wavelengths, the limits on roughness range and spatial frequency range make the method unsuitable for characterizing engineering surfaces. By increasing the wavelength of the incident light from the visible to the infrared, elastic light scattering turns out to be applicable for engineering surfaces. We have used total integrated scattering at 10.6 μm wavelength to measure rms roughness up to two micrometers. In this paper, the instrument design and properties are reviewed. We also present results from measurements on ground steel surfaces. Excellent correspondence with mechanical stylus measurements exists for surfaces with rms roughness in the range from 0.1–1.7 μm. The technique shows potential for rapid quality inspection of engineering surfaces.

Fatigue Gauge Utilizing Slip Deformation of Alumium Foil : 1st Report, Slip Initiation and Surface Roughening Phenomena Under Uniaxial Stressing

Fundamental characteristic of slip initiation and surface roughening phenomena in aluminum foil during the fatigue process are investigated under constant amplitude stressing. Applicability of the foil to the fatigue gauge that utilizes these phenomena to detect fatigue damage is discussed. It is found that the slip initiation phenomenon in aluminum foil is easily observed by an optical microscope and that the effects of temperature and cyclic speed on the slip initiation are quite small. Accordingly, aluminum foil can be used as the fatigue gauge that utilizes the slip initiation phenomenon. It is also found that evolution of surface roughness caused by the slip deformation is dependent on cyclic stress and the number of cycles. Therefore, this phenomenon also enables use of the foil as the fatigue gauge that makes use of surface roughness. Measuring accuracy of stress by this foil is about 5 MPa, and in-process measurements of cyclic strains or fatigue damage can be practicable provided that non-contact surface roughness measurement is adopted.