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Ranganatha, S.
- Studies on Effect of Hardness and Normal Load on Weight Loss and Plastic Deformation Morphology in Three Body Abrasion
Abstract Views :116 |
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Authors
Affiliations
1 Department of Mechanical Engineering, BGSIT, Mandya, Karnataka, IN
2 Department of Mechanical Engineering, UVCE, Bangalore, Karnataka, IN
3 Department of Mechanical Engineering, CITECH, Bangalore, Karnataka, IN
1 Department of Mechanical Engineering, BGSIT, Mandya, Karnataka, IN
2 Department of Mechanical Engineering, UVCE, Bangalore, Karnataka, IN
3 Department of Mechanical Engineering, CITECH, Bangalore, Karnataka, IN
Source
International Journal of Engineering Research, Vol 5, No SP 6 (2016), Pagination: 1237-1243Abstract
Machineries which are used in industries involves relative motion between two components called elements. These relative motion between elements is required either to transfer force or motions. In some cases, example material conveying system, relative motions exists between material and conveyor. All the above cases give rise to discontinuities in velocity and displacements. These discontinuities results in volume loss of materials. Loss of materials give rise to loss of durability and reliability of machines. There will be a lot of thrust in reducing the new advanced machines due to loss of materials or wear. Understanding wear and controlling is a strong need for advanced and reliable design of machines. Rubber wheel abrader with different sized sand as abrader is used for conducting the experiments. EN 24 (HT) Steel (269 BHN), EN (31) HT (450 BHN) EN 44 (HT) (500 BHN) were used as target materials. Experiments were conducted with two loads 53.2 N and 102.4 N. The speed was maintained at 200 rpm. The time of test was 6 minutes, the flow rate was 100 grams/min. The wear loss was estimated and found that for EN 24 HT was 0.15 at a normal load of 52.3 N and 0.21 at a load of 102.4 N. The wear loss was for EN 31 HT is 0.07 and 0.08 which are comparable at two different normal loads. In case of EN 44 HT the wear loss was found to be 0.04 at a normal load of 53.2 N and 0.07 at a normal load of 102.4 N. the effect of normal load was found to be less for materials of higher hardness. The morphology of deformation was found to characterize the experimentally observed wear loss volume for material of different hardness.Keywords
Abrasive Wear, Deformation, Hardness.Full Text
- Selected Single Face Tracking in Technically Challenging Different Background Video Sequences using Combined Features
Abstract Views :179 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science and Engineering, Government Engineering College, Hassan, IN
2 Department of Computer Science and Engineering, Kalpataru Institute of Technology, IN
3 Department of Computer Science and Engineering, Rajeev Institute of Technology, IN
1 Department of Computer Science and Engineering, Government Engineering College, Hassan, IN
2 Department of Computer Science and Engineering, Kalpataru Institute of Technology, IN
3 Department of Computer Science and Engineering, Rajeev Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 9, No 2 (2018), Pagination: 1911-1918Abstract
The commonly identified limitations of video face trackers are, the inability to track human face in different background video sequences with the conditions like occlusion, low quality, abrupt motions and failing to track single face when it contain multiple faces. In this paper, we propose a novel algorithm to track human face in different background video sequences with the conditions listed above. The proposed algorithm describes an improved KLT tracker. We collect Eigen, FAST as well as HOG features and combine them together. The combined features are given to the tracker to track the face. The algorithm being proposed is tested on challenging datasets videos and measured for performance using the standard metrics.Keywords
Track Human Face, Different Background, Video Sequences, KLT, Combined Features.
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- S. Ranganatha and Y.P. Gowramma, “Development of Robust Multiple Face Tracking Algorithm and Novel Performance Evaluation Metrics for Different Background Video Sequences”, International Journal of Intelligent Systems and Applications, Vol. 10, No. 8, pp. 19-35, 2018.
- S. Ranganatha and Y.P. Gowramma, “Image Training, Corner and FAST Features Based Algorithm for Face Tracking in Low Resolution Different Background Challenging Video Sequences”, International Journal of Image, Graphics and Signal Processing, Vol. 10, No. 8, pp. 39-53, 2018.
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