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3D Non-Destructive Evaluation Techniques for Wood Analysis

3D Non-Destructive Evaluation Techniques for Wood Analysis

M. Paulina Fernández, Cristian Tejos, Gerson Rojas, Iván Lillo, Andrés Guesalaga, Pablo Irarrázaval
Copyright: © 2014 |Pages: 34
ISBN13: 9781466645547|ISBN10: 1466645547|EISBN13: 9781466645554
DOI: 10.4018/978-1-4666-4554-7.ch007
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MLA

Fernández, M. Paulina, et al. "3D Non-Destructive Evaluation Techniques for Wood Analysis." Research Developments in Wood Engineering and Technology, edited by Alfredo Aguilera and J. Paulo Davim, IGI Global, 2014, pp. 247-280. https://doi.org/10.4018/978-1-4666-4554-7.ch007

APA

Fernández, M. P., Tejos, C., Rojas, G., Lillo, I., Guesalaga, A., & Irarrázaval, P. (2014). 3D Non-Destructive Evaluation Techniques for Wood Analysis. In A. Aguilera & J. Davim (Eds.), Research Developments in Wood Engineering and Technology (pp. 247-280). IGI Global. https://doi.org/10.4018/978-1-4666-4554-7.ch007

Chicago

Fernández, M. Paulina, et al. "3D Non-Destructive Evaluation Techniques for Wood Analysis." In Research Developments in Wood Engineering and Technology, edited by Alfredo Aguilera and J. Paulo Davim, 247-280. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4554-7.ch007

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Abstract

Non-destructive testing techniques allow the analysis of wood characteristics without altering its end-use capabilities. Wood morphology, wood density, moisture content, and wood decay are some of the features detectable by means of different non-destructive methods. Among them, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) stand out because of their ability to measure information in a three-dimensional fashion. This enables one to scan volumetrically an entire tree log, giving measurements of each location of the analyzed volume. The output data can provide information about internal structures or physiological features, which can then be used for optimizing industrial processing or for research purposes. In this chapter, the authors describe CT and MRI in terms of their operational principles, sampling conditions, data outputs, and advantages and disadvantages.

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