MACHALÍK Stanislav, ZEMČÍK Pavel and JURÁNEK Roman. Využití obrazové analýzy v tribotechnické diagnostice. Pardubice: University of Pardubice, 2013. ISBN 978-80-7395-583-0.
Publication language:czech
Original title:Využití obrazové analýzy v tribotechnické diagnostice
Title (en):Image Analysis for Tribodiagnostic
Place:Pardubice, CZ
Publisher:University of Pardubice
Wear particle analysis, Ferrography
Image analysis of wear particles is a suitable support tool for detail analysis of engine, gear, hydraulic and industrial oils. Is allows to obtain information not only of basic parameters of abrasion particles but also data that would be very difficult to obtain wusin classical ways of evaluation. based on the analysis of morphological or image characteristic of particles, the progress of wearing the machine parts can be prevented or the optimum period for changing the oil can be determined
The aim of this paper is to explore the possibilites of using the image analysis combined with the method of analytical ferrography and suggest a tool for automated particle classification. Corrent methods of wear particle analysis are derived from the evaluation that does not offer an exact idea of processes that take place between the friction surfaces in the engine system. The work is based upon the method of analytical ferrography which allows to evaluate the state of the machine. The benefit of the use of classifiers defined in this work is the possibility of automated evaluation of analytical ferrography outputs; the use of them eliminates the crucial disadvantage of ferrographical analysis which is the dependence of the subjective evaluation done by expert who performs the analysis.
Classifiers are defined as a result of using methods of machine learning. Based on an extensive database of particles that was created in the forst part of this work, the classifiers were trained - as a result, they make the evaluation of ferrographically separated abrasion particles from oils taken from lubricated systems possible. In the next stage experiments were carried out and optimum classifier settings were determined based on resultsof the experiments.
   author = {Stanislav Machal{\'{i}}k and Pavel Zem{\v{c}}{\'{i}}k and
	Roman Jur{\'{a}}nek},
   title = {Vyu{\v{z}}it{\'{i}} obrazov{\'{e}} anal{\'{y}}zy v
	tribotechnick{\'{e}} diagnostice},
   pages = {112},
   year = {2013},
   location = {Pardubice, CZ},
   publisher = {University of Pardubice},
   ISBN = {978-80-7395-583-0},
   language = {czech},
   url = {}

Your IPv4 address:
Switch to IPv6 connection

DNSSEC [dnssec]