A Novel Approach to Quantifying Surface Roughness in Grinding

2007 ◽  
Vol 339 ◽  
pp. 147-151
Author(s):  
Chun Hua Ju ◽  
Yi Xie
Keyword(s):  
Surface Roughness ◽  
Standard Deviation ◽  
Vision System ◽  
Computer Control ◽  
Mean Value ◽  
Quality Characteristic ◽  
Edge Image ◽  
Gray Image ◽  
Novel Approach ◽  
Machined Surfaces

Surface roughness is an important quality characteristic in grinding. Measurement of surface roughness by means of mechanical stylus is widely done in metrology. In this paper, a new machine vision system has been utilized to quantify the surface roughness of machined surfaces (ground and milled). Compared with other measurement methods, it is accurate, quick and credible. This system is mounted on the grinding machine and automates the measurement process by using computer control to automatically position the CCD and capture digital images of machined surfaces between grinding cycles. It was proposed that the proportional formula was used in calibrating this system, and calibration precision meets application requirement. Not only the statistic character of gray image but also which of edge image were calculated out. These characters include the mean value of pixels (Mean), standard deviation (σ), maximal value (Max) and minimal value (Min), the number of pixels on the examine line(Count), etc. It was found out that the standard deviation value σ of the gray image could express the surface roughness most. The correlation between σ and Ra is established by interpolating σ value used Lagrange interpolation law, and the σ value is converted into Ra value through the calculation procedure finally.

scholarly journals Effect of Different Finishing and Polishing Techniques on Surface Roughness of Two Universal Nanohybrid Composite Resins

2020 ◽  
Vol 8 (D) ◽  
pp. 182-188
Author(s):  
Ebaa Alagha ◽  
Waad Alotaibi ◽  
Maha Maghrbil ◽  
Laila Hakami ◽  
Maram Alrashedi
Keyword(s):  
Surface Roughness ◽  
Composite Resin ◽  
Vision System ◽  
Mean Value ◽  
Composite Resins ◽  
Resin Composites ◽  
Light Sectioning ◽  
Light Curing ◽  
Nanohybrid Composite ◽  
Glass Slab

AIM: This study investigated the effect of different finishing and polishing systems on surface roughness of two types of universal nanohybrid composite resins. MATERIALS AND METHODS: A total number of 40 samples will be prepared to form two main equal groups of specimens (n = 20), according to the composite resin materials. Two universal nanohybrid resin composites were used in this study. First group (A1) is a universal nanohybrid composite resin (Mosaic) and the second group (A2) is a universal nanohybrid composite resin (Harmonize). Each group was subdivided equally into four equal subgroups (n = 5), according to the used finishing and polishing systems. Mold was made to prepare the specimens with a central hole of 4 mm in diameter and 4 mm in thickness. Light curing tip was placed touching the glass slab for 20 s then the cured specimens were removed from the mold and the specimens immediately and immersed in distilled water at 37°C for 24 h. Surface roughness (Ra) was measured using light sectioning vision system. SEM was done to support the results. RESULTS: The results showed that the lowest (Ra) values were recorded by the specimens under Myler strip followed by Polishing Discs treated specimens followed by Diacomp Plus specimens and the highest (Ra) values were recorded by white polishing stone specimens and regardless to finishing or polishing, it was found that mosaic resin composites group recorded statistically significant (p < 0.05) lower roughness mean value than Harmonize resin composites group. p ≤ 0.05 is statistically significant in all tests. CONCLUSION: Achieving long-lasting esthetics in resin composites restorations needs special attention for obtaining optimal resin polymerization and a perfect surface finish using the appropriate finishing and polishing system.

scholarly journals Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2421
Author(s):  
Roberta Fusco ◽  
Vincenza Granata ◽  
Mauro Mattace Raso ◽  
Paolo Vallone ◽  
Alessandro Pasquale De Rosa ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Univariate Analysis ◽  
Mean Value ◽  
Blood Oxygenation ◽  
Breast Lesions ◽  
Dce Mri ◽  
Malignant Lesions ◽  
The Mean ◽  
And Diffusion ◽  
Skewness And Kurtosis

Purpose. To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. Methods. Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. Results. R2* and D had a significant negative correlation (−0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the ‘poor’ diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. Conclusions. Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.

Optimal parameters of abrasive flow finishing for hip joint implants

2021 ◽  
pp. 095440542199561
Author(s):  
Yahya Choopani ◽  
Mohsen Khajehzadeh ◽  
Mohammad Reza Razfar
Keyword(s):  
Surface Roughness ◽  
Standard Deviation ◽  
Femoral Head ◽  
Hip Joint ◽  
Spherical Shape ◽  
Shape Deviation ◽  
Head Surface ◽  
Joint Implants ◽  
Finishing Processes ◽  
Abrasive Flow Finishing

Total hip arthroplasty (THA) is one of the most well-known orthopedic surgeries in the world which involves the substitution of the natural hip joint by prostheses. In this process, the surface roughness of the femoral head plays a pivotal role in the performance of hip joint implants. In this regard, the nano-finishing of the femoral head of the hip joint implants to achieve a uniform surface roughness with the lowest standard deviation is a major challenge in the conventional and advanced finishing processes. In the present study, the inverse replica fixture technique was used for automatic finishing in the abrasive flow finishing (AFF) process. For this aim, an experimental setup of the AFF process was designed and fabricated. After the tests, experimental data were modeled and optimized to achieve the minimum surface roughness in the ASTM F138 (SS 316L) femoral head of the hip joint through the use of response surface methodology (RSM). The results confirmed uniform surface roughness up to the range of 0.0203 µm with a minimum standard deviation of 0.00224 for the femoral head. Moreover, the spherical shape deviation of the femoral head was achieved in the range of 7 µm. The RSM results showed a 99.71% improvement in the femoral head surface roughness (0.0007) µm under the optimized condition involving the extrusion pressure of 9.10 MPa, the number of finishing cycles of 95, and SiC abrasive mesh number of 1000.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

scholarly journals Influence of Relative Displacement on Surface Roughness in Longitudinal Turning of X37CrMoV5-1 Steel

Materials ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1317
Author(s):  
Michal Skrzyniarz ◽  
Lukasz Nowakowski ◽  
Edward Miko ◽  
Krzysztof Borkowski
Keyword(s):  
Surface Roughness ◽  
Standard Deviation ◽  
Surface Texture ◽  
Roughness Parameter ◽  
Relative Displacement ◽  
Edge Radius ◽  
Shaping Process ◽  
Feed Value ◽  
Longitudinal Turning ◽  
Final Effect

The shaping process of surface texture is complicated and depends on many factors and phenomena accompanying them. This article presents the author’s test stand for the measurement of relative displacements in a tool–workpiece system during longitudinal turning. The aim of this study was to determine the influence of edge radius on the relative displacement between the tool and workpiece. The cutting process was carried out with inserts with different edge radii for X37CrMoV5-1 steel. As a result of the research, vibration charts of the tool–workpiece system were obtained. In the range of feed 0.03–0.18 mm/rev, the values of the standard deviation of relative displacements in the x-axis were obtained in the range of 0.36–0.78 μm for the insert with an edge radius of rn = 48.8 μm. As a result of the work, it was determined that for the feed value of 0.12 mm/rev for all inserts, the relative displacements are the smallest. As the final effect, the formula for forecasting the Ra roughness parameter was presented.

scholarly journals An image dehazing algorithm based on double priors constraint

2018 ◽  
Vol 189 ◽  
pp. 04009
Author(s):  
Kun Liu ◽  
Shiping Wang ◽  
Linyuan He ◽  
Duyan Bi ◽  
Shan Gao
Keyword(s):  
Standard Deviation ◽  
Mean Value ◽  
Experimental Results ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Color Distortion ◽  
Local Media ◽  
Dark Channel

Aiming at the color distortion of the restored image in the sky region, we propose an image dehazing algorithm based on double priors constraint. Firstly, we divided the haze image into sky and non-sky regions. Then the Color-lines prior and dark channel prior are used for estimating the transmission of sky and non-sky regions respectively. After introducing color-lines prior to correct sky regions restored by the dark channel prior, we get an accurate transmission. Finally, the local media mean value and standard deviation are used to refine the transmission to obtain the dehazing image. Experimental results show that the algorithm has obvious advantages in the recovery of the sky area.

In Situ: A Novel Approach for the Production of Micro Holes

2010 ◽  
Vol 126-128 ◽  
pp. 885-890
Author(s):  
K.P. Somashekhar ◽  
N. Ramachandran ◽  
Jose Mathew
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Feed Rate ◽  
Machining Parameters ◽  
Average Roughness ◽  
Arithmetic Average ◽  
Quantitative Correlation ◽  
Good Surface ◽  
Novel Approach ◽  
Micro Holes

This work is on the preparation of microelectrodes for μ-EDM operation using μ-WEDG process. Electrodes of Ø500 μm are fabricated with various discharge energy machining conditions. Effects of gap voltage, capacitance & feed rate on the surface finish of the electrodes and overcut of the thus produced micro holes are investigated. The profile of microelectrodes is measured using surface roughness tester with 2μm stylus interfaced with SURFPAK software. The study demonstrated that for brass electrodes an arithmetic average roughness value as low as 1.7μm and an overcut of 3 µm could be achieved. The significant machining parameters are found using ANOVA. Surface of the produced microelectrodes are examined using Scanning Electron Microscope. μ-WEDG process parameters could be adjusted to achieve good surface integrity on microelectrodes. Experimental results showed that the surface roughness of microelectrodes depended primarily on feed rate of the electrode. The observations showed the clear and quantitative correlation existing between the micrometer level surface quality and process parameters. The resulting microelectrodes are found to be of exceptionally high quality and could be used for μ- EDM operation on different types of work materials.

Synchronous Issue of IR-Based Large Scale Volume Localization System

2014 ◽  
Vol 496-500 ◽  
pp. 1643-1647
Author(s):  
Ying Feng Wu ◽  
Gang Yan Li
Keyword(s):  
Standard Deviation ◽  
Mobile Robot ◽  
Large Volume ◽  
Large Scale ◽  
Image Acquisition ◽  
Mean Value ◽  
Network Synchronization ◽  
Localization System ◽  
Localization Performance ◽  
The Mean

IR-based large scale volume localization system (LSVLS) can localize the mobile robot working in large volume, which is constituted referring to the MSCMS-II. Hundreds cameras in LSVLS must be connected to the control station (PC) through network. Synchronization of cameras which are mounted on different control stations is significant, because the image acquisition of the target must be synchronous to ensure that the target is localized precisely. Software synchronization method is adopted to ensure the synchronization of camera. The mean value of standard deviation of eight cameras mounted on two workstations is 12.53ms, the localization performance of LSVLS is enhanced.

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