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Wear Measuring And Wear Modelling Based On Archard, Astm, And Neural Network Models

Authors: Shebani, Amer; Pislaru, Crinela;

Wear Measuring And Wear Modelling Based On Archard, Astm, And Neural Network Models

Abstract

{"references": ["J. R. Davis, \"Surface Engineering for Corrosion and Wear Resistance\",\nASM international Publishing, USA, 2001.", "J. Stokes, \"Theory and Application of the High Velocity Oxy-Fuel\n(HVOF) Thermal Spray Process\", PhD thesis, School of Mechanical and\nManufacturing Engineering, Dublin City University, Ireland, 2008.", "J. A. Collins, \"Mechanical Design of Machine Elements and Machines\",\nJohn Wiley & Sons, USA, 2002.", "B. Bhushan, \"Tribology: Friction, Wear, and Lubrication\", CRC Press\nLCC, USA, 2000.", "A. Sethuramiah, \"Lubricated Wear Science and Technology\", Elsevier\nScience Publishing, USA, 2003.", "M. Braunovic, N. Myshkin, and V. Konchits, \"Fundamentals,\nApplications and Technology\", CRC press LCC, USA, 2007.", "O. Mokhlessi, H. M. Rad, \"Utilization of 4 types of Artificial Neural\nNetwork on the diagnosis of valve-physiological heart disease from heart\nsounds\", 17th Iranian Conference of Biomedical Engineering, Vol. 978,\npp. 4244-7484, Iran, 2010.", "L. Jinkun, \"Radial Basis Function (RBF) Neural Network control for\nMechanical Systems\", Springer, USA, 2013.", "C. Otto, \"Modeling a hydraulic drive using neural networks\",\nDepartment of Measurement and Control, University of Duisburg,\nGermany, 2000.\n[10] Ruano, \"Applications of neural networks to control systems\", University\nof Wales, School of Electronic Engineering Science University of Wales,\nBangor, 1992.\n[11] P. J. Blau, R. L. Martin, and L. Riester, \"A comparison of several surface\nfinish measurement methods as applied to ground ceramic and metal\nsurfaces\", Oak Ridge National Laboratory (Ornl), USA, 1996.\n[12] L. Mummery, \"Surface Texture Analysis the Handbook\", Hommlwerke\nGmbH, Germany, 1990.\n[13] W. Yan, N. P. Dowd, E. Busso, \"Numerical study of sliding wear caused\nby a loaded pin on a rotating disc\", Journal of the Mechanics and Physics\nof Solids, vol. 50, pp. 449 \u2013 470, 2002. Elsevier Science Publishing,\nUSA, 2002.\n[14] A. Sanchez, \"Tribological characterization of carbon based solid\nlubricants\", Master thesis, Texas A&M University, USA, 2011.\n[15] Orvnas, \"Simulation of rail wear on the Swedish light rail line\nTvarbanan\", Master thesis, Royal Institute of Technology (KTH),\nDepartment of Engineering, Stockholm, 2005.\n[16] ASTM, \"Standard Test Method for Wear Testing with a Pin-on-Disk\nApparatus\", ASTM Publishing, Vol. 14.02, pp. 95 \u2013 99, USA, 2000.\n[17] N. X. Randall, \"Tribological Characterization of Biomaterials\",\nMaterials for Medical Devices, ASM, ASM Handbook, ASM\nInternational Press, Vol. 23, p 148\u2013156, Switzerland, 2007.\n[18] Steel stockholders, \"EN8 Steel\", KV steel Ltd, UK, 2014.\nhttp://kvsteel.co.uk/steel/EN8.html (online).\n[19] Aalco, \"Aluminum, Aalco metal Ltd, UK, 2014.\nhttps://www.google.co.uk/webhp?sourceid=chrome-instant&ion=1&\nespv=2&ie=UTF-8#q=Aluminium%20Alloy%206082 (online).\n[20] N. B. Karayiannis, \"Reformulated Radial Basis Neural Networks Trained\nby Gradient Descent\", IEEE Trans. Neural Networks, vol. 10, pp. 657-\n671, Aug. 2002.\n[21] J. Moody, and C. Darken, \"Fast learning in Networks of Locally-Tuned\nProcessing Units\", neural computation, Vol. 1, 1989.\n[22] R. Mammone, \"Artificial Neural Networks for Speech and Vision\", New\nJersey, USA, 1994.\n[23] L. Fu, \"Neural Networks in Computer Intelligence\", university of\nFlorida, 1994."]}

The wear measuring and wear modelling are fundamental issues in the industrial field, mainly correlated to the economy and safety. Therefore, there is a need to study the wear measurements and wear estimation. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin is made of steel with a tip, positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument. The Talysurf profilometer was used to measure the pin/disc wear scar depth, digital microscope was used to measure the diameter and width of wear scar, and the alicona was used to measure the pin wear and disc wear. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling. Simulation results were implemented by using the Matlab program. This paper focuses on how the alicona can be used for wear measurements and how the neural network can be used for wear estimation.

Keywords

Wear measuring, T1, Neural Network, Alicona., TJ, Wear modelling

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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