The algorithm of crack and crack tip coordinates detection in optical images during fatigue test; IOP Conference Series: Materials Science and Engineering; Vol. 177 : Mechanical Engineering, Automation and Control Systems (MEACS 2016)

Bibliografiske detaljer
Parent link:IOP Conference Series: Materials Science and Engineering
Vol. 177 : Mechanical Engineering, Automation and Control Systems (MEACS 2016).— 2017.— [012019, 6 p.]
Institution som forfatter: Национальный исследовательский Томский политехнический университет (ТПУ) Институт физики высоких технологий (ИФВТ) Кафедра материаловедения в машиностроении (ММС)
Andre forfattere: Panin S. V. Sergey Viktorovich, Chemezov V. O., Lyubutin P. S. Pavel Stepanovich, Titkov V. V.
Summary:Title screen
An algorithm of crack detection during fatigue testing of materials, designed to automate the process of cyclic loading and tracking the crack tip, is proposed and tested. The ultimate goal of the study is aimed at controlling the displacements of the optical system with regard to the specimen under fatigue loading to ensure observation of the 'area of interest'. It is shown that the image region that contains the crack may be detected and positioned with an average error of 1.93%. In terms of determining the crack tip position, the algorithm provides the accuracy of its localization with the average error value of 56 pixels.
Sprog:engelsk
Udgivet: 2017
Serier:Information technologies in Mechanical Engineering
Fag:
Online adgang:http://dx.doi.org/10.1088/1757-899X/177/1/012019
http://earchive.tpu.ru/handle/11683/37879
Format: Electronisk Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654016

MARC

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330 |a An algorithm of crack detection during fatigue testing of materials, designed to automate the process of cyclic loading and tracking the crack tip, is proposed and tested. The ultimate goal of the study is aimed at controlling the displacements of the optical system with regard to the specimen under fatigue loading to ensure observation of the 'area of interest'. It is shown that the image region that contains the crack may be detected and positioned with an average error of 1.93%. In terms of determining the crack tip position, the algorithm provides the accuracy of its localization with the average error value of 56 pixels. 
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