The imaging algorithm for the ultrasonic testing of metal castings by the application of automated testing systems based on a six degree of freedom robotic manipulators

• Autorzy: Dolmatov Dmitry , Zhvyrblya Vadim , Sednev Dmitry , Kroening Michael
• Języki publikacji: EN

Abstrakty

EN

Complex-shaped surface represents one of the challenges in ultrasonic testing of metal castings. This conditions the growing interest in development and application of the automated testing system based on a six degrees of freedom (DOF) robotic manipulators. This is due to their ability to provide ultrasonic scanning of the curved specimens with high speed. Higher reliability of the results can be obtained via implementation of the imaging algorithms based on Synthetic Aperture Focusing Technique (SAFT) in the named systems. This approach allows to obtain high-resolution imagery of the internal structure of controlled objects with reduced level of grain noise, the latter occurs due to the often encountered coarse-grained structure of metal castings. In this paper, we introduce the novel imaging algorithm for the automated ultrasonic testing system based on a six degree of freedom robotic manipulator. The capabilities of the algorithm were verified by the application of computer simulations in CIVA 2016 software and also via the in situ experiments. In all the cases analyzed the results revealed that the imaging algorithm allows to make precise imagery of the internal structure of the specimens with different curvature. The obtained research results confirmed the suggested algorithm effectiveness, thus making it acceptable for prospective industrial applications.

Słowa kluczowe

EN

ultrasonic nondestructive testing; ultrasonic imaging; synthetic aperture focusing technique

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Methods in Materials Science
• Rocznik: 2018
• Tom: Vol. 18, No. 2
• Strony: 49--57
• Opis fizyczny: Bibliogr. 19 poz., rys.

Twórcy

autor

Dolmatov Dmitry

• National Research Tomsk Polytechnic University, 30, Lenin Ave. Tomsk, Russia

autor

Zhvyrblya Vadim

• National Research Tomsk Polytechnic University, 30, Lenin Ave. Tomsk, Russia

autor

Sednev Dmitry

• National Research Tomsk Polytechnic University, 30, Lenin Ave. Tomsk, Russia

autor

Kroening Michael

• National Research Tomsk Polytechnic University, 30, Lenin Ave. Tomsk, Russia

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019)