This paper deals with the development of optimal procedures for nondestructive testing (NDT) inspections using shearography. In the new proposed method a parameter is adopted, the contrast-to-noise ratio (CNR), which allows the quantification of the contrast of the defect to the background in the image. During the calibration of the technique, on samples with known defects, the CNR also takes into account the size and location of the identified defects, compared to those expected. The optimal measurement and loading conditions (e.g., excitation temperature level, time between image acquisitions) are determined by experimental parametric analyses aimed at maximizing the CNR on specimens with known defects. In the present work the developed methodology is described and applied to the definition of best practices for the NDT analysis of aeronautical sandwich composites structures (used in the production of helicopters) by shearography inspection with thermal excitation. In this case the attention is focused on optimizing the thermal loading procedures, but it can be clearly extended to other types of excitation methods.
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http://dx.doi.org/10.1063/1.3002423 | DOI Listing |
Sci Rep
January 2025
Crop and Horticultural Science Research Department, Mazandaran Agricultural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tajrish, Iran.
Plum fruit fresh weight (FW) estimation is crucial for various agricultural practices, including yield prediction, quality control, and market pricing. Traditional methods for estimating fruit weight are often destructive, time-consuming, and labor-intensive. In this study, we addressed the problem of predicting plum FW using artificial intelligence (AI) methods based on fruit dimensions.
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January 2025
Advanced Manufacturing and Materials Centre, WMG, University of Warwick, Coventry, CV4 7AL, UK.
Sci Rep
January 2025
Łukasiewicz Research Network, Krakow Institute of Technology, Zakopiańska 73 Str, Krakow, 30-418, Poland.
Compr Rev Food Sci Food Saf
January 2025
School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China.
Raman spectroscopy, a nondestructive optical technique that provides detailed chemical information, has attracted growing interest in the food industry. Complementary spectroscopic methods, such as near-infrared (NIR) spectroscopy, nuclear magnetic resonance (NMR), terahertz (THz) spectroscopy, laser-induced breakdown spectroscopy (LIBS), and fluorescence spectroscopy (Flu), enhance Raman spectroscopy's capabilities in various applications. The integration of Raman with these techniques, termed "Raman plus X," has shown significant potential in agri-food analysis.
View Article and Find Full Text PDFAnalyst
January 2025
Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK.
The seed coat plays a pivotal role in seed development and germination, acting as a protective barrier and mediating interac-tions with the external environment. Traditional histochemical techniques and analytical methods have provided valuable insights into seed coat composition and function. However, these methods often suffer from limitations such as indirect chemical signatures and lack of spatial resolution.
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