scholarly journals Monitoring fungus infestation of common beech wood using terahertz radiation

Holzforschung ◽  
2020 ◽  
Vol 74 (7) ◽  
pp. 635-641
Author(s):  
Kirsti Krügener ◽  
Jan Ornik ◽  
Roksana Jachim ◽  
Bettina Kietz ◽  
Karin Petersen ◽  
...  
Keyword(s):  
Trametes Versicolor ◽  
Construction Projects ◽  
Beech Wood ◽  
Cultural Property ◽  
Thz Radiation ◽  
Furniture Industry ◽  
Thz Imaging ◽  
Common Beech ◽  
Destructive Analysis ◽  
Non Destructive

AbstractWood is one of the most widely used materials for construction projects, in the furniture industry, as well as in the field of cultural property of valuable objects. Terahertz (THz) radiation has great potential for non-contact and non-destructive analysis of wooden materials. This article reports a study of the degree of growth of Trametes versicolor in wood samples, using THz radiation. The analysis compares the THz results to microscopic examinations of the samples, common beech incubated with T. versicolor, at different growth times. The results indicate a strong correlation between the parameters extracted from THz measurements and the progress of the fungal infestation, suggesting that THz imaging may be a valuable tool for non-contact inspection of wood.

scholarly journals Non Destructive Analysis of Fsw Welds using Ultrasonic Signal Analysis

2017 ◽  
Vol 225 ◽  
pp. 012060 ◽  
Author(s):  
T. Pavan Kumar ◽  
P. Prabhakar Reddy
Keyword(s):  
Signal Analysis ◽  
Ultrasonic Signal ◽  
Destructive Analysis ◽  
Non Destructive

Non-destructive analysis the dating of paper based on convolutional neural network

2021 ◽  
Vol 248 ◽  
pp. 119290
Author(s):  
Jingjing Xia ◽  
Xiayu Du ◽  
Weixin Xu ◽  
Yun Wei ◽  
Yanmei Xiong ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Destructive Analysis ◽  
Non Destructive

scholarly journals Improvement of the Non-Destructive Testing of Heritage Mural Paintings Using Stimulated Infrared Thermography and Frequency Image Processing

2019 ◽  
Vol 5 (9) ◽  
pp. 72
Author(s):  
Kamel Mouhoubi ◽  
Vincent Detalle ◽  
Jean-Marc Vallet ◽  
Jean-Luc Bodnar
Keyword(s):  
Infrared Thermography ◽  
Cultural Property ◽  
Wall Paintings ◽  
Non Destructive Testing ◽  
Property A ◽  
Destructive Testing ◽  
Mural Paintings ◽  
Works Of Art ◽  
Optical Effects ◽  
Non Destructive

Within the framework of conservation and assistance for the restoration of cultural property, a method of analysis assistance has been developed to help in the restoration of cultural heritage. Several collaborations have already demonstrated the possibility of defects detection (delamination, salts) in murals paintings using stimulated infrared thermography. One of the difficulties encountered with infrared thermography applied to the analysis of works of art is the remanence of the pictorial layer. This difficulty can sometimes induce detection artifacts and false positives. A method of thermograms post-processing called PPT (pulse phase thermography) is described. The possibilities offered by the PPT in terms of reducing the optical effects associated with the pictorial layer are highlighted first with a simulation, and then through experiments. This approach can significantly improve the study of painted works of art such as wall paintings.

Non-destructive analysis and appraisal of paper-like objects

1998 ◽  
Vol 136-138 ◽  
pp. 897-901 ◽  
Author(s):  
Huansheng Cheng ◽  
Ding Yanfang ◽  
He Wenquan ◽  
Yang Fujia
Keyword(s):  
Destructive Analysis ◽  
Non Destructive

Non-destructive analysis

1989 ◽  
Vol 36 (3) ◽  
pp. 265-265
Keyword(s):  
Destructive Analysis ◽  
Non Destructive

scholarly journals Non-destructive analysis of flake properties in automotive paints with full-field optical coherence tomography and 3D segmentation

2017 ◽  
Vol 25 (16) ◽  
pp. 18614 ◽  
Author(s):  
Jinke Zhang ◽  
Bryan M. Williams ◽  
Samuel Lawman ◽  
David Atkinson ◽  
Zijian Zhang ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Optical Coherence ◽  
3D Segmentation ◽  
Full Field ◽  
Destructive Analysis ◽  
Non Destructive

Development of Deep Learning Algorithms to Discriminate Giant Cell Tumor of Bone from Adjacent Normal Tissues by Confocal Raman Spectroscopy

The Analyst ◽  
2022 ◽  
Author(s):  
Carol PY Lau ◽  
Wenao Ma ◽  
Kwan Yau Law ◽  
Maribel Lacambra ◽  
Kwok Chuen Wong ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Giant Cell Tumor ◽  
Giant Cell ◽  
Chemical Structure ◽  
Cell Tumor ◽  
Confocal Raman Spectroscopy ◽  
Normal Tissues ◽  
Analysis Technique ◽  
Destructive Analysis ◽  
Non Destructive

Raman spectroscopy is a non-destructive analysis technique that provides detailed information about the chemical structure of the tumor. Raman spectra of 52 giant cell tumor of bone (GCTB), and 21...

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