@article{(Open Science Index):https://publications.waset.org/pdf/10000683,
	  title     = {Wear Measuring and Wear Modelling Based On Archard, ASTM, and Neural Network Models},
	  author    = {A. Shebani and  C. Pislaru},
	  country	= {},
	  institution	= {},
	  abstract     = {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.
},
	    journal   = {International Journal of Mechanical and Mechatronics Engineering},
	  volume    = {9},
	  number    = {1},
	  year      = {2015},
	  pages     = {177 - 182},
	  ee        = {https://publications.waset.org/pdf/10000683},
	  url   	= {https://publications.waset.org/vol/97},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 97, 2015},
	}