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End sem presentation 2018 -2019.pptx

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Praveen Kumar

The document summarizes research conducted on analyzing surface roughness in incremental forming processes. It discusses four different methods used - stylus method, Euclidean distance method, Hamming distance method, and GLCM method. Results are presented from experimental investigations comparing the surface roughness values obtained from each method when varying process parameters like tool diameter, step depth, and wall angle in incremental forming. The objectives of the research were to analyze surface roughness, formability, form accuracy and forming forces.

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BITS Pilani Hyderabad Campus EndSemesterPresentation SemesterI(2018-19) DepartmentofMechanicalEngineering Candidate Name : G. Praveen Kumar ID No. : 2016PHXF0420H Supervisor Name : Dr. K. Suresh DAC members: Dr. Pavan Kumar .P Dr. Nitin .K
BITS Pilani Hyderabad Campus Experimental investigations and mathematical modeling of incremental forming processes
BITS Pilani, Hyderabad Campus Contents Objectives of the Proposed Research Work done Analysis of Results Publications References 1
BITS Pilani, Hyderabad Campus Objectivesoftheproposedresearch 2 1. Analysis of surface roughness in parts formed by incremental forming. 2. Experimental and theoretical studies on formability in incremental forming. 3. Analysis of form accuracy, spring back and forming forces in incremental forming process. 4. Experimental investigation in incremental hole flanging process. 5. Finite element (FE) simulations of incremental forming.
BITS Pilani, Hyderabad Campus DigitalimageprocessingSurfaceroughness Digital Image processing Euclidean distance Hamming distance GLCM (Gray level co- occurance matrix) Wavelet analysis Workdone 3
BITS Pilani, Hyderabad Campus The Hamming distance represents the distance between two items by number of mismatches among their pairs of variables. For Hamming distance (倹) calculated from below equation. 倹 , = 1 =1 Where N is the dimension of the feature vector; pi is the ith component of the feature vector and qi is the ith component of the template vector 1 0 1 1 0 0 1 0 0 1 4 1 0 0 1 0 0 0 0 1 1 A B Hamming distance =3 Hamming distance method
BITS Pilani, Hyderabad Campus Reference Images Image (1) 256 x 256 Image (2) Image (27) 256 x 256 Ra Values Image 1 ---- 1.54 Image 2 ---- 2.40 Image 27 ---- 2.40 Image (a) 256 x 256 Test image A min value of Hamming distance means a test image matches closely with the reference image. HD1 HD2 HD3 HD27 5 Binary image Test image Reference image Calculation of Hamming distance
BITS Pilani, Hyderabad Campus Hamming distance method Results S.No Tool dia Step depth Wall angle Range Avg 速 T1 T2 T3 T4 T5 T6 Range 1 5 0.25 30 1.28 to 1.92 1.54 1.47 1.54速 1.47 1.47 1.47 1.47 1.47 to 1.54 2 5 0.75 30 2.36to 2.41 2.40 2.4速 2.02 2.4 2.02 2.4 2.02 2.02 to 2.40 3 5 1.25 30 3.2 to 3.24 3.22 3.22 速 3.22 2.02 2.02 3.22 3.22 2.02 to 3.22 4 5 0.25 50 1.15 to 1.19 1.17 1.17 1.17 1.17 1.17 1.17 1.17 1.17 5 5 0.75 50 3.48 to 3.69 3.59 1.66 3.59速 3.59 3.59 3.59 1.66 1.66 to 3.59 6 5 1.25 50 3.16 to 3.59 3.39 1.52 1.52 3.39 1.52 3.39 速 3.39 1.52 to 3.39 7 5 0.25 70 0.7 to 0.895 0.83 0.83 0.83速 0.83 0.83 0.83 0.83 0.83 8 5 0.75 70 2.85 to 3.47 3.22 3.22 3.22 速 0.83 3.22 3.22 3.22 3.22 9 5 1.25 70 2.21 to 2.61 2.48 2.48 速 0.7 0.7 0.7 0.7 0.7 0.7 to 2.48 10 10 0.25 30 1.22 to 1.92 1.69 0.83 0.83 0.83 1.69 速 0.83 0.83 0.83 to 1.69 11 10 0.75 30 2.11 to 2.37 2.24 1.66 2.24 1.66 速 1.66 1.66 1.66 1.66 to2.24 12 10 1.25 30 1.47 to 1.6 1.59 1.59 1.66 1.66 1.66 1.66 1.59 速 1.59 to1.66 13 10 0.25 50 0.714 to0.994 0.88 0.88 速 0.6 0.6 0.6 0.6 0.6 0.6 to 0.88 14 10 0.75 50 1.62 to 2.24 2.02 2.02 速 2.02 2.02 2.02 2.02 0.72 2.02 15 10 1.25 50 2.02 to 2.36 2.15 2.15 速 2.15 1.17 1.17 1.17 1.17 1.17 to 2.15 16 10 0.25 70 0.605 to 0.735 0.67 0.67速 0.67 2.02 2.02 0.67 2.02 0.67 to 2.02 17 10 0.75 70 1.51 to 1.79 1.66 1.66 速 1.66 1.66 1.66 0.6 1.66 1.66 18 10 1.25 70 1.33 to 1.61 1.47 1.47 1.17 1.17 1.47 1.17 1.47速 1.17 to 1.47 19 15 0.25 30 1.06 to 1.21 1.15 1.17 1.17 1.17 1.15速 1.17 1.15 1.15 to 1.17 20 15 0.75 30 0.961 to 1.23 1.12 1.12 速 1.12 1.66 1.66 1.66 1.66 1.12 to 1.66 21 15 1.25 30 0.811 to 1.3 1.07 1.07速 1.17 1.17 1.17 1.17 1.17 1.07 to 1.17 22 15 0.25 50 0.621 to 0.736 0.70 0.60 0.7速 0.6 0.6 0.6 0.6 0.6 to 0.7 23 15 0.75 50 0.529 to 0.679 0.60 0.6速 0.6 0.6 0.6 0.6 0.6 0.6 24 15 1.25 50 1.35 to 1.69 1.52 1.52 1.66 1.66 1.52 速 1.66 1.66 1.52 to1.66 25 15 0.25 70 0.649 to0.874 0.72 0.72速 0.72 0.72 0.72 0.72 0.72 0.72 26 15 0.75 70 2.14 to 2.45 2.32 1.66 2.32速 2.32 1.66 2.32 1.66 1.66 to 2.32 27 15 1.25 70 0.996 to 1.17 1.07 0.83 1.07 0.83 1.07 1.07 1.07 0.83 to 1.07 6
BITS Pilani, Hyderabad Campus Analysis of Results
BITS Pilani, Hyderabad Campus GLCM method Original Image GLCM Matrix GLCM Parameters Surface Roughness (Ra) 7 1.Standard deviation 2.Maximum Occurrence matrix 3. Maximum occurrence of position
BITS Pilani, Hyderabad Campus GLCM method Results Tool dia Step depth Wall angle Range Avg 速 T1 T2 T3 T4 T5 T6 Range 5 0.25 30 1.28 to 1.92 1.54 1.32 1.25 1.25 1.28 1.31 1.31 1.25 to 1.32 5 0.75 30 2.36to 2.41 2.40 1.25 1.35 1.26 1.32 1.25 1.24 1.25 to1.35 5 1.25 30 3.20 to 3.24 3.22 2.33 2.26 2.42 2.11 2.23 2.19 2.10 to 2.41 5 0.25 50 1.15 to 1.19 1.17 1.27 1.24 1.27 1.26 1.28 1.28 1.24 to 1.28 5 0.75 50 3.48 to 3.69 3.59 2.39 2.37 2.16 2.16 2.24 2.43 2.15 to 2.42 5 1.25 50 3.16 to 3.59 3.39 2.23 1.92 1.92 2.64 0.47 2.00 1.92 to 2.23 5 0.25 70 0.70 to 0.89 0.83 2.64 _ 2.17 2.44 1.91 1.91 1.91 to 2.64 5 0.75 70 2.85 to 3.47 3.22 1.28 1.38 1.25 1.27 1.44 1.27 1.25 to 1.44 5 1.25 70 2.21 to 2.61 2.48 2.41 _ 2.62 1.91 1.91 _ 1.91 to2.62 10 0.25 30 1.22 to 1.92 1.69 1.45 1.43 1.47 1.50 1.43 1.43 1.43 to 1.50 10 0.75 30 2.11 to 2.37 2.24 1.69 1.71 1.68 1.63 1.56 1.56 1.56 to 1.71 10 1.25 30 1.47 to 1.6 1.59 2.36 2.32 1.92 1.92 2.09 1.91 1.91 to 2.36 10 0.25 50 0.71 to0.99 0.88 1.35 1.36 1.37 1.42 1.35 1.35 1.35 to 1.42 10 0.75 50 1.62 to 2.24 2.02 2.06 1.91 2.38 2.16 2.40 1.87 1.87 to 2.40 10 1.25 50 2.02 to 2.36 2.15 2.22 2.43 2.21 2.10 2.15 2.13 2.10 to 2.43 10 0.25 70 0.60 to 0.73 0.67 1.25 1.25 1.99 1.41 1.44 2.34 1.25 to2.34 10 0.75 70 1.51 to 1.79 1.66 1.68 1.38 1.82 2.49 2.16 _ 1.38 to 2.49 10 1.25 70 1.33 to 1.61 1.47 1.27 1.25 1.24 1.25 1.25 1.26 1.24 to 1.27 15 0.25 30 1.06 to 1.21 1.15 1.38 1.38 1.41 1.37 1.48 1.40 1.38 to1.41 15 0.75 30 0.96 to 1.23 1.12 1.27 1.25 1.26 1.34 1.26 1.35 1.25 to 1.35 15 1.25 30 0.81 to 1.30 1.07 1.24 1.47 1.33 1.70 1.34 1.44 1.24 to 1.70 15 0.25 50 0.62 to 0.73 0.70 1.35 1.53 1.57 1.61 1.59 1.57 1.35 to1.61 15 0.75 50 0.52 to 0.67 0.60 1.27 1.27 1.25 1.27 1.26 1.26 1.26 to 1.27 15 1.25 50 1.35 to 1.69 1.52 1.26 1.34 1.45 1.42 1.31 2.44 1.26 to2.44 15 0.25 70 0.64 to0.87 0.72 1.37 2.17 1.32 1.25 1.69 1.33 1.25 to2.17 15 0.75 70 2.14 to 2.45 2.32 1.45 2.04 2.10 2.23 2.29 2.34 1.45 to 2.34 15 1.25 70 0.99 to 1.17 1.07 1.27 2.43 1.24 1.60 1.24 2.44 1.24 to 2.44 8
BITS Pilani, Hyderabad Campus Analysis of Results
BITS Pilani, Hyderabad Campus S.No Tool dia Step depth Wall angle Stylus method Ra value Range Euclidean distance method Ra value range Hamming distance method Ra value range GLCM Method Ra value range 1 5 0.25 30 1.28 to 1.92 1.15 to 1.54 1.47 to 1.54 1.25 to 1.32 2 5 0.75 30 2.36to 2.41 0.72 to 2.40 2.02 to 2.40 1.25 to1.35 3 5 1.25 30 3.2 to 3.24 2.15 to 3.22 2.02 to 3.22 2.10 to 2.41 4 5 0.25 50 1.15 to 1.19 1.17 1.17 1.24 to 1.28 5 5 0.75 50 3.48 to 3.69 3.22 to 3.59 1.66 to 3.59 2.15 to 2.42 6 5 1.25 50 3.16 to 3.59 2.15 to3.39 1.52 to 3.39 1.92 to 2.23 7 5 0.25 70 0.7 to 0.895 0.83 0.83 1.91 to 2.64 8 5 0.75 70 2.85 to 3.47 3.22 3.22 1.25 to 1.44 9 5 1.25 70 2.21 to 2.61 2.15 to 2.48 0.7 to 2.48 1.91 to2.62 10 10 0.25 30 1.22 to 1.92 1.17 to 169 0.83 to 1.69 1.43 to 1.50 11 10 0.75 30 2.11 to 2.37 1.52 to 2.24 1.66 to2.24 1.56 to 1.71 12 10 1.25 30 1.47 to 1.6 1.59 1.59 to1.66 1.91 to 2.36 13 10 0.25 50 0.71 to0.99 0.88 to 1.17 0.6 to 0.88 1.35 to 1.42 14 10 0.75 50 1.62 to 2.24 1.17 to2.02 2.02 1.87 to 2.40 15 10 1.25 50 2.02 to 2.36 2.15 to 3.22 1.17 to 2.15 2.10 to 2.43 16 10 0.25 70 0.60 to 0.73 0.67 to 0.72 0.67 to 2.02 1.25 to2.34 17 10 0.75 70 1.51 to 1.79 1.66 1.66 1.38 to 2.49 18 10 1.25 70 1.33 to 1.61 1.17 to 1.47 1.17 to 1.47 1.24 to 1.27 19 15 0.25 30 1.06 to 1.21 1.15 to 1.17 1.15 to 1.17 1.38 to1.41 20 15 0.75 30 0.96 to 1.23 1.12 to 1.52 1.12 to 1.66 1.25 to 1.35 21 15 1.25 30 0.81 to 1.3 1.07 to 1.17 1.07 to 1.17 1.24 to 1.70 22 15 0.25 50 0.62 to 0.73 0.7 to 0.83 0.6 to 0.7 1.35 to1.61 23 15 0.75 50 0.52 to 0.67 0.6 to 1.17 0.6 1.26 to 1.27 24 15 1.25 50 1.35 to 1.69 1.52 1.52 to1.66 1.26 to2.44 25 15 0.25 70 0.64 to0.87 0.72 0.72 1.25 to2.17 26 15 0.75 70 2.14 to 2.45 1.66 to 2.32 1.66 to 2.32 1.45 to 2.34 27 15 1.25 70 0.99 to 1.17 1.07 to2.15 0.83 to 1.07 1.24 to 2.44 Comparative Ra value range between Stylus, Eucliden ,Hamming and GLCM method 9
BITS Pilani, Hyderabad Campus International Conference: 1. Experimental studies on incremental hole flanging of steel sheets, 20th Edition of International Conference On Advances in materials and processing technologies, 11 - 14 December 2017. VIT University Chennai, India. (Accepted) 2. Analysis of formability in incremental forming processes, 7th international conference on materials processing and characterization 2017, GRIET, March 17-19 2017, Hyderabad, Telangana, India. (Published in Materials Today: Proceedings,Elsevier) Publications 10
BITS Pilani, Hyderabad Campus [1]. Jeyapoovan, T., Murugan, M. (2013). Surface roughness classification using image processing Measurement,46,2065-2072. [2]. E.S. Gadelmawla. (2004). A vision system for surface roughness characterization using the gray level co- occurrence matrix. NDT&E International, 37 577588. [3]. Shahabi, H.H., Ratnam, M.M. (2010). Noncontact roughness measurement of turned parts using machine ision. Journal of Int J Adv Manuf Technol 46:275284. [4]. Martin- Roche,D., Sanchez-Avila,C., and Sanchez-Reillo,R .(2001). Iris Recognition for Biometric Identification using Dyadic Wavelet Transform Zero-Crossing. Proceedings of the 35th IEEE International Carnahan Conference on Security Technology. London, UK, 2001,pp. 27277. References
BITS Pilani Hyderabad Campus THANKYOU
BITS Pilani, Hyderabad Campus Input image and corresponding gray-level co-occurrence matrix
BITS Pilani, Hyderabad Campus Graycomatrix creates the GLCM by calculating how often a pixel with gray-level (grayscale intensity) value i occurs horizontally adjacent to a pixel with the value j Each element (i,j) in glcm specifies the number of times that the pixel with value i occurred horizontally adjacent to a pixel with value j.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Ra No of Experiments Stylus_Min Stylus_Max Euclidean_Min Euclidean_Max
BITS Pilani, Hyderabad Campus Co-occurrence Matrix Features
BITS Pilani, Hyderabad Campus
BITS Pilani, Hyderabad Campus Histogram equalization is a technique for adjusting image intensities to enhance contrast.
BITS Pilani, Hyderabad Campus

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End sem presentation 2018 -2019.pptx

  • 1. BITS Pilani Hyderabad Campus EndSemesterPresentation SemesterI(2018-19) DepartmentofMechanicalEngineering Candidate Name : G. Praveen Kumar ID No. : 2016PHXF0420H Supervisor Name : Dr. K. Suresh DAC members: Dr. Pavan Kumar .P Dr. Nitin .K
  • 2. BITS Pilani Hyderabad Campus Experimental investigations and mathematical modeling of incremental forming processes
  • 3. BITS Pilani, Hyderabad Campus Contents Objectives of the Proposed Research Work done Analysis of Results Publications References 1
  • 4. BITS Pilani, Hyderabad Campus Objectivesoftheproposedresearch 2 1. Analysis of surface roughness in parts formed by incremental forming. 2. Experimental and theoretical studies on formability in incremental forming. 3. Analysis of form accuracy, spring back and forming forces in incremental forming process. 4. Experimental investigation in incremental hole flanging process. 5. Finite element (FE) simulations of incremental forming.
  • 5. BITS Pilani, Hyderabad Campus DigitalimageprocessingSurfaceroughness Digital Image processing Euclidean distance Hamming distance GLCM (Gray level co- occurance matrix) Wavelet analysis Workdone 3
  • 6. BITS Pilani, Hyderabad Campus The Hamming distance represents the distance between two items by number of mismatches among their pairs of variables. For Hamming distance (倹) calculated from below equation. 倹 , = 1 =1 Where N is the dimension of the feature vector; pi is the ith component of the feature vector and qi is the ith component of the template vector 1 0 1 1 0 0 1 0 0 1 4 1 0 0 1 0 0 0 0 1 1 A B Hamming distance =3 Hamming distance method
  • 7. BITS Pilani, Hyderabad Campus Reference Images Image (1) 256 x 256 Image (2) Image (27) 256 x 256 Ra Values Image 1 ---- 1.54 Image 2 ---- 2.40 Image 27 ---- 2.40 Image (a) 256 x 256 Test image A min value of Hamming distance means a test image matches closely with the reference image. HD1 HD2 HD3 HD27 5 Binary image Test image Reference image Calculation of Hamming distance
  • 8. BITS Pilani, Hyderabad Campus Hamming distance method Results S.No Tool dia Step depth Wall angle Range Avg 速 T1 T2 T3 T4 T5 T6 Range 1 5 0.25 30 1.28 to 1.92 1.54 1.47 1.54速 1.47 1.47 1.47 1.47 1.47 to 1.54 2 5 0.75 30 2.36to 2.41 2.40 2.4速 2.02 2.4 2.02 2.4 2.02 2.02 to 2.40 3 5 1.25 30 3.2 to 3.24 3.22 3.22 速 3.22 2.02 2.02 3.22 3.22 2.02 to 3.22 4 5 0.25 50 1.15 to 1.19 1.17 1.17 1.17 1.17 1.17 1.17 1.17 1.17 5 5 0.75 50 3.48 to 3.69 3.59 1.66 3.59速 3.59 3.59 3.59 1.66 1.66 to 3.59 6 5 1.25 50 3.16 to 3.59 3.39 1.52 1.52 3.39 1.52 3.39 速 3.39 1.52 to 3.39 7 5 0.25 70 0.7 to 0.895 0.83 0.83 0.83速 0.83 0.83 0.83 0.83 0.83 8 5 0.75 70 2.85 to 3.47 3.22 3.22 3.22 速 0.83 3.22 3.22 3.22 3.22 9 5 1.25 70 2.21 to 2.61 2.48 2.48 速 0.7 0.7 0.7 0.7 0.7 0.7 to 2.48 10 10 0.25 30 1.22 to 1.92 1.69 0.83 0.83 0.83 1.69 速 0.83 0.83 0.83 to 1.69 11 10 0.75 30 2.11 to 2.37 2.24 1.66 2.24 1.66 速 1.66 1.66 1.66 1.66 to2.24 12 10 1.25 30 1.47 to 1.6 1.59 1.59 1.66 1.66 1.66 1.66 1.59 速 1.59 to1.66 13 10 0.25 50 0.714 to0.994 0.88 0.88 速 0.6 0.6 0.6 0.6 0.6 0.6 to 0.88 14 10 0.75 50 1.62 to 2.24 2.02 2.02 速 2.02 2.02 2.02 2.02 0.72 2.02 15 10 1.25 50 2.02 to 2.36 2.15 2.15 速 2.15 1.17 1.17 1.17 1.17 1.17 to 2.15 16 10 0.25 70 0.605 to 0.735 0.67 0.67速 0.67 2.02 2.02 0.67 2.02 0.67 to 2.02 17 10 0.75 70 1.51 to 1.79 1.66 1.66 速 1.66 1.66 1.66 0.6 1.66 1.66 18 10 1.25 70 1.33 to 1.61 1.47 1.47 1.17 1.17 1.47 1.17 1.47速 1.17 to 1.47 19 15 0.25 30 1.06 to 1.21 1.15 1.17 1.17 1.17 1.15速 1.17 1.15 1.15 to 1.17 20 15 0.75 30 0.961 to 1.23 1.12 1.12 速 1.12 1.66 1.66 1.66 1.66 1.12 to 1.66 21 15 1.25 30 0.811 to 1.3 1.07 1.07速 1.17 1.17 1.17 1.17 1.17 1.07 to 1.17 22 15 0.25 50 0.621 to 0.736 0.70 0.60 0.7速 0.6 0.6 0.6 0.6 0.6 to 0.7 23 15 0.75 50 0.529 to 0.679 0.60 0.6速 0.6 0.6 0.6 0.6 0.6 0.6 24 15 1.25 50 1.35 to 1.69 1.52 1.52 1.66 1.66 1.52 速 1.66 1.66 1.52 to1.66 25 15 0.25 70 0.649 to0.874 0.72 0.72速 0.72 0.72 0.72 0.72 0.72 0.72 26 15 0.75 70 2.14 to 2.45 2.32 1.66 2.32速 2.32 1.66 2.32 1.66 1.66 to 2.32 27 15 1.25 70 0.996 to 1.17 1.07 0.83 1.07 0.83 1.07 1.07 1.07 0.83 to 1.07 6
  • 9. BITS Pilani, Hyderabad Campus Analysis of Results
  • 10. BITS Pilani, Hyderabad Campus GLCM method Original Image GLCM Matrix GLCM Parameters Surface Roughness (Ra) 7 1.Standard deviation 2.Maximum Occurrence matrix 3. Maximum occurrence of position
  • 11. BITS Pilani, Hyderabad Campus GLCM method Results Tool dia Step depth Wall angle Range Avg 速 T1 T2 T3 T4 T5 T6 Range 5 0.25 30 1.28 to 1.92 1.54 1.32 1.25 1.25 1.28 1.31 1.31 1.25 to 1.32 5 0.75 30 2.36to 2.41 2.40 1.25 1.35 1.26 1.32 1.25 1.24 1.25 to1.35 5 1.25 30 3.20 to 3.24 3.22 2.33 2.26 2.42 2.11 2.23 2.19 2.10 to 2.41 5 0.25 50 1.15 to 1.19 1.17 1.27 1.24 1.27 1.26 1.28 1.28 1.24 to 1.28 5 0.75 50 3.48 to 3.69 3.59 2.39 2.37 2.16 2.16 2.24 2.43 2.15 to 2.42 5 1.25 50 3.16 to 3.59 3.39 2.23 1.92 1.92 2.64 0.47 2.00 1.92 to 2.23 5 0.25 70 0.70 to 0.89 0.83 2.64 _ 2.17 2.44 1.91 1.91 1.91 to 2.64 5 0.75 70 2.85 to 3.47 3.22 1.28 1.38 1.25 1.27 1.44 1.27 1.25 to 1.44 5 1.25 70 2.21 to 2.61 2.48 2.41 _ 2.62 1.91 1.91 _ 1.91 to2.62 10 0.25 30 1.22 to 1.92 1.69 1.45 1.43 1.47 1.50 1.43 1.43 1.43 to 1.50 10 0.75 30 2.11 to 2.37 2.24 1.69 1.71 1.68 1.63 1.56 1.56 1.56 to 1.71 10 1.25 30 1.47 to 1.6 1.59 2.36 2.32 1.92 1.92 2.09 1.91 1.91 to 2.36 10 0.25 50 0.71 to0.99 0.88 1.35 1.36 1.37 1.42 1.35 1.35 1.35 to 1.42 10 0.75 50 1.62 to 2.24 2.02 2.06 1.91 2.38 2.16 2.40 1.87 1.87 to 2.40 10 1.25 50 2.02 to 2.36 2.15 2.22 2.43 2.21 2.10 2.15 2.13 2.10 to 2.43 10 0.25 70 0.60 to 0.73 0.67 1.25 1.25 1.99 1.41 1.44 2.34 1.25 to2.34 10 0.75 70 1.51 to 1.79 1.66 1.68 1.38 1.82 2.49 2.16 _ 1.38 to 2.49 10 1.25 70 1.33 to 1.61 1.47 1.27 1.25 1.24 1.25 1.25 1.26 1.24 to 1.27 15 0.25 30 1.06 to 1.21 1.15 1.38 1.38 1.41 1.37 1.48 1.40 1.38 to1.41 15 0.75 30 0.96 to 1.23 1.12 1.27 1.25 1.26 1.34 1.26 1.35 1.25 to 1.35 15 1.25 30 0.81 to 1.30 1.07 1.24 1.47 1.33 1.70 1.34 1.44 1.24 to 1.70 15 0.25 50 0.62 to 0.73 0.70 1.35 1.53 1.57 1.61 1.59 1.57 1.35 to1.61 15 0.75 50 0.52 to 0.67 0.60 1.27 1.27 1.25 1.27 1.26 1.26 1.26 to 1.27 15 1.25 50 1.35 to 1.69 1.52 1.26 1.34 1.45 1.42 1.31 2.44 1.26 to2.44 15 0.25 70 0.64 to0.87 0.72 1.37 2.17 1.32 1.25 1.69 1.33 1.25 to2.17 15 0.75 70 2.14 to 2.45 2.32 1.45 2.04 2.10 2.23 2.29 2.34 1.45 to 2.34 15 1.25 70 0.99 to 1.17 1.07 1.27 2.43 1.24 1.60 1.24 2.44 1.24 to 2.44 8
  • 12. BITS Pilani, Hyderabad Campus Analysis of Results
  • 13. BITS Pilani, Hyderabad Campus S.No Tool dia Step depth Wall angle Stylus method Ra value Range Euclidean distance method Ra value range Hamming distance method Ra value range GLCM Method Ra value range 1 5 0.25 30 1.28 to 1.92 1.15 to 1.54 1.47 to 1.54 1.25 to 1.32 2 5 0.75 30 2.36to 2.41 0.72 to 2.40 2.02 to 2.40 1.25 to1.35 3 5 1.25 30 3.2 to 3.24 2.15 to 3.22 2.02 to 3.22 2.10 to 2.41 4 5 0.25 50 1.15 to 1.19 1.17 1.17 1.24 to 1.28 5 5 0.75 50 3.48 to 3.69 3.22 to 3.59 1.66 to 3.59 2.15 to 2.42 6 5 1.25 50 3.16 to 3.59 2.15 to3.39 1.52 to 3.39 1.92 to 2.23 7 5 0.25 70 0.7 to 0.895 0.83 0.83 1.91 to 2.64 8 5 0.75 70 2.85 to 3.47 3.22 3.22 1.25 to 1.44 9 5 1.25 70 2.21 to 2.61 2.15 to 2.48 0.7 to 2.48 1.91 to2.62 10 10 0.25 30 1.22 to 1.92 1.17 to 169 0.83 to 1.69 1.43 to 1.50 11 10 0.75 30 2.11 to 2.37 1.52 to 2.24 1.66 to2.24 1.56 to 1.71 12 10 1.25 30 1.47 to 1.6 1.59 1.59 to1.66 1.91 to 2.36 13 10 0.25 50 0.71 to0.99 0.88 to 1.17 0.6 to 0.88 1.35 to 1.42 14 10 0.75 50 1.62 to 2.24 1.17 to2.02 2.02 1.87 to 2.40 15 10 1.25 50 2.02 to 2.36 2.15 to 3.22 1.17 to 2.15 2.10 to 2.43 16 10 0.25 70 0.60 to 0.73 0.67 to 0.72 0.67 to 2.02 1.25 to2.34 17 10 0.75 70 1.51 to 1.79 1.66 1.66 1.38 to 2.49 18 10 1.25 70 1.33 to 1.61 1.17 to 1.47 1.17 to 1.47 1.24 to 1.27 19 15 0.25 30 1.06 to 1.21 1.15 to 1.17 1.15 to 1.17 1.38 to1.41 20 15 0.75 30 0.96 to 1.23 1.12 to 1.52 1.12 to 1.66 1.25 to 1.35 21 15 1.25 30 0.81 to 1.3 1.07 to 1.17 1.07 to 1.17 1.24 to 1.70 22 15 0.25 50 0.62 to 0.73 0.7 to 0.83 0.6 to 0.7 1.35 to1.61 23 15 0.75 50 0.52 to 0.67 0.6 to 1.17 0.6 1.26 to 1.27 24 15 1.25 50 1.35 to 1.69 1.52 1.52 to1.66 1.26 to2.44 25 15 0.25 70 0.64 to0.87 0.72 0.72 1.25 to2.17 26 15 0.75 70 2.14 to 2.45 1.66 to 2.32 1.66 to 2.32 1.45 to 2.34 27 15 1.25 70 0.99 to 1.17 1.07 to2.15 0.83 to 1.07 1.24 to 2.44 Comparative Ra value range between Stylus, Eucliden ,Hamming and GLCM method 9
  • 14. BITS Pilani, Hyderabad Campus International Conference: 1. Experimental studies on incremental hole flanging of steel sheets, 20th Edition of International Conference On Advances in materials and processing technologies, 11 - 14 December 2017. VIT University Chennai, India. (Accepted) 2. Analysis of formability in incremental forming processes, 7th international conference on materials processing and characterization 2017, GRIET, March 17-19 2017, Hyderabad, Telangana, India. (Published in Materials Today: Proceedings,Elsevier) Publications 10
  • 15. BITS Pilani, Hyderabad Campus [1]. Jeyapoovan, T., Murugan, M. (2013). Surface roughness classification using image processing Measurement,46,2065-2072. [2]. E.S. Gadelmawla. (2004). A vision system for surface roughness characterization using the gray level co- occurrence matrix. NDT&E International, 37 577588. [3]. Shahabi, H.H., Ratnam, M.M. (2010). Noncontact roughness measurement of turned parts using machine ision. Journal of Int J Adv Manuf Technol 46:275284. [4]. Martin- Roche,D., Sanchez-Avila,C., and Sanchez-Reillo,R .(2001). Iris Recognition for Biometric Identification using Dyadic Wavelet Transform Zero-Crossing. Proceedings of the 35th IEEE International Carnahan Conference on Security Technology. London, UK, 2001,pp. 27277. References
  • 17. BITS Pilani, Hyderabad Campus Input image and corresponding gray-level co-occurrence matrix
  • 18. BITS Pilani, Hyderabad Campus Graycomatrix creates the GLCM by calculating how often a pixel with gray-level (grayscale intensity) value i occurs horizontally adjacent to a pixel with the value j Each element (i,j) in glcm specifies the number of times that the pixel with value i occurred horizontally adjacent to a pixel with value j.
  • 19. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Ra No of Experiments Stylus_Min Stylus_Max Euclidean_Min Euclidean_Max
  • 20. BITS Pilani, Hyderabad Campus Co-occurrence Matrix Features
  • 22. BITS Pilani, Hyderabad Campus Histogram equalization is a technique for adjusting image intensities to enhance contrast.