Detection and Identification of Defects in 3D-Printed Dielectric Structures via Thermographic Inspection and Deep Neural Networks
In this paper, we propose a new method based on active infrared thermography (IRT) applied to assess the state of 3D-printed structures. The technique utilized here—active IRT—assumes the use of an external energy source to heat the tested material and to create a temperature difference between unda...
Main Authors: | Barbara Szymanik, Grzegorz Psuj, Maryam Hashemi, Przemyslaw Lopato |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-07-01
|
Series: | Materials |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1944/14/15/4168 |
Similar Items
-
Glass–Adhesive–Steel Joint Inspection Using Mechanic and High Frequency Electromagnetic Waves
by: Jakub Kowalczyk, et al.
Published: (2020-10-01) -
Generative Deep Learning-Based Thermographic Inspection of Artwork
by: Yi Liu, et al.
Published: (2023-07-01) -
Analysis and characterization of PV module defects by thermographic inspection
by: Sara Gallardo-Saavedra, et al.
Published: (2019-08-01) -
Strategy Based on Two Stages for IR Thermographic Inspections of Photovoltaic Plants
by: Germán Álvarez-Tey, et al.
Published: (2022-06-01) -
Thermographic Image of the Hoof Print in Leisure and Cross-Country Warmblood Horses: A Pilot Study
by: Cristian Zaha, et al.
Published: (2023-07-01)