Non-destructive characterization of maritime pine sawn timber dielectric anisotropy by means of GPR

Abad, Isabel Rodríguez; Martínez‐Sala, R.; García‐García, Francisco J.; Capuz-Lladró, R.; Barra, Rafael Díez

doi:10.1109/iwagpr.2011.5963860

Cited by 8 publications

(2 citation statements)

References 12 publications

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“…timber was analyzed, a slight difference was observed in the D. The relationship between the A D with the antenna at the edge and the squared-end was found to be A DE /A DS = 1.10, regardless of the samples cross section [40]. However, not all the samples analyzed in this research followed the same pattern, since the relation was found to range A DE /A DS = [0.8-1.2] (Tab.…”

Section: Test 2: Transverse Testmentioning

confidence: 93%

Assessment of the dielectric anisotropy in timber using the nondestructive GPR technique

Martínez‐Sala

Abad

Barra

et al. 2013

Construction and Building Materials

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ElsevierRodríguez Abad, I.; Martínez Sala, RM.; Díez Barra, R.; Capuz Lladró, R. (2013 AbstractIn the realm of architecture Ground-penetrating radar has been used as nondestructive technique to assess physical properties of wood structures in situ. However, a better understanding of the dielectric anisotropy of timber is needed to develop this application. An experiment was conducted on samples of sawn timber of different species (densities) to study their dielectric responses according to the grain directions using a GPR with a 1,6 GHz antenna. Interesting differences were found: the propagation velocities, as well as the amplitudes of the direct and reflected waves always presented lesser when the electric field was longitudinal to the grain than when transverse. But when the field was propagated in whatever transverse direction some of those parameters not differ greatly.

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Section: Test 2: Transverse Testmentioning

confidence: 93%

Assessment of the dielectric anisotropy in timber using the nondestructive GPR technique

Martínez‐Sala

Abad

Barra

et al. 2013

Construction and Building Materials

Self Cite

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“…Currently, different structural health monitoring (SHM) methods have been employed to detect the MC of timber, mainly including the acoustic emission method [8][9][10], the piezoceramic stress wave method [11][12][13][14], the fiber optic sensor method [15], the Conductance/electrical resistance method [16][17][18], the ultrasonic-based process [19][20][21], the ground-penetrating radar (GPR) method [22], among others. Most of the methods mentioned above are suitable for the evaluation of timber MC.…”

Section: Introductionmentioning

confidence: 99%

Timber moisture detection using wavelet packet decomposition and convolutional neural network

Yuan

Zhang

Chen

et al. 2021

Smart Mater. Struct.

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As timber structures are vulnerable to degradation due to the tendency to trap moisture, the present study proposed a new percussion-based method to replace the existing constant contact between structures and sensors. A total of two approaches have been proposed to automated detect the moisture content (MC) of timber: (a) the random forest classifier (machine learning-based) was employed to classify the wavelet packet decomposition (WPD) features extracted from excitation-induced sound signals (WPD + RF); and (b) the 2D-CNN framework (deep learning-based) was employed to classify the Mel frequency cepstral coefficient (MFCC) features extracted from excitation-induced sound signals (MFCC + 2DCNN). The proposed automatic detection methods are covered from 1D time-domain signal classification to 2D image classification. To verify the effectiveness of both two approaches, an experimental study was conducted. The MC of two types of timber specimens (i.e. softwood and hardwood) was gradually increased from 0% to 60% with 10% increments. The change of MC of timber material caused different material properties, resulting in a measurable differential in forced vibration among the various specimens used. The results demonstrated that MFCC + 2DCC outperformed the RF + WPD in MC classification of timber material. Overall, the percussion-based method proposed in this study can provide an outstanding classification performance.

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Zerstörungsfreie/‐arme Prüfmethoden für Bestandsuntersuchungen im Holzbau: Wellenbasierte Methoden – Stand der Technik und Untersuchungsergebnisse

Perria¹,

Böhler²,

Sieder³

2022

Bauphysik Kalender 2022

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Non-destructive characterization of maritime pine sawn timber dielectric anisotropy by means of GPR

Cited by 8 publications

References 12 publications

Assessment of the dielectric anisotropy in timber using the nondestructive GPR technique

Assessment of the dielectric anisotropy in timber using the nondestructive GPR technique

Timber moisture detection using wavelet packet decomposition and convolutional neural network

Zerstörungsfreie/‐arme Prüfmethoden für Bestandsuntersuchungen im Holzbau: Wellenbasierte Methoden – Stand der Technik und Untersuchungsergebnisse

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