Velocity Error Correction Based Tomographic Imaging for Stress Wave Nondestructive Evaluation of Wood

Huan, Zhan; Zhi, Jiao; Li, Guanghui; Wu, Xi

doi:10.15376/biores.13.2.2530-2545

Cited by 12 publications

(8 citation statements)

References 22 publications

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“…Lin et al [23] analyzed the envelope peak value of the first arrival wave in the stress wave signal, determined the location of the defect, drew the general outline of the cavity, and verified the reliability of the method by experiments on camphor trees. Zhan et al [24] collected stress wave velocity signals of tree cross-sections using professional equipment, and proposed a stress wave imaging algorithm named IABLE, which calculated the grid distribution of wave velocity in tree faults by an iterative inversion method. Du et al [25] proposed a stress save tomography method of wood internal defects using ellipse-based spatial interpolation and velocity compensation.…”

Section: Introductionmentioning

confidence: 99%

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Feng

et al. 2018

Applied Sciences

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In order to detect the size and shape of defects inside wood, an image reconstruction method based on segmented propagation rays of stress waves is proposed. The method uses sensors to obtain the stress wave velocity data by hanging around the timber equally, visualizes those data, and reconstructs the image of internal defects with the visualized propagation rays. The basis of the algorithm is precisely segmenting the rays to benefit the spatial interpolation. First, a ray segmentation algorithm using the elliptical neighborhood technique is proposed, which can be used to segment the rays and estimate the velocity values of segmented rays by the nearby original rays using elliptical zones. Second, a spatial interpolation algorithm utilizing a segmented ellipse according to the segmented rays is also proposed, which can be used to estimate the velocity value of a grid cell by the segmented ellipses corresponding to the nearby segmented rays. Then, the image of the internal defect inside the wood is reconstructed. Both simulation and experimental data were used to evaluate the proposed method, and the area and shape of the imaging results were analyzed. The comparison results show that the proposed method can produce high quality reconstructions with clear edges and high accuracy.

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Section: Introductionmentioning

confidence: 99%

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Feng

et al. 2018

Applied Sciences

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“…Contact methods require good contact between the sensor and the material. Topographic imaging using a stress wave detected and visualized defect areas inside trees [10]. A tomographic imaging algorithm (IABLE) with a velocity error correction mechanism was developed for the high-resolution evaluation of wood [11].…”

Section: Introductionmentioning

confidence: 99%

“…When the current path is deformed by anomalies in the wood, the input impedance of the antenna is impacted. This technique has many advantages, including providing sensor hardware simplicity, low power consumption, and high reliability of detection [10]; more importantly, access to only one flat face of the beam is required.…”

Section: Introductionmentioning

confidence: 99%

Single-Sided Microwave Near-Field Scanning of Pine Wood Lumber for Defect Detection

Radwan

Thiel

Espinosa

2021

Forests

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Defects and cracks in dried natural timber (relative permittivity 2–5) may cause structural weakness and enhanced warping in structural beams. For a pine wood beam (1200 mm × 70 mm × 70 mm), microwave reflection (S11) and transmission (S21) measurements using a cavity-backed slot antenna on the wood surface showed the variations caused by imperfections and defects in the wood. Reflection measurements at 4.4 GHz increased (>5 dB) above a major knot evident on the wood surface when the E-field was parallel to the wood grain. Similar results were observed for air cavities, independent of depth from the wood surface. The presence of a metal bolt in an air hole increased S11 by 2 dB. In comparison, transmission measurements (S21) were increased by 6 dB for a metal screw centered in the cavity. A kiln-dried pine wood sample was saturated with water to increase its moisture content from 17% to 138%. Both parallel and perpendicular E-field measurements showed a difference of more than 15 dB above an open saw-cut slot in the water-saturated beam. The insertion of a brass plate in the open slot created a 7 dB rise in the S11 measurement (p < 0.0003), while there was no significant variation for perpendicular orientation. By measuring the reflection coefficient, it was possible to detect the location of a crack through a change in its magnitude without a noticeable change (<0.01 GHz) in resonant frequency. These microwave measurements offer a simple, single-frequency non-destructive testing method of structural timber in situ, when one or more plane faces are accessible for direct antenna contact.

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“…Du et al (2018) proposed a three-dimensional stress wave imaging method based on TKriging to reconstruct internal defect images of wood. Huan et al (2018) proposed a stress wave tomography algorithm with a velocity error correction mechanism based on the wave velocity data set measured via stress waves. Finally, a sectional image of the test sample image was generated.…”

Section: Introductionmentioning

confidence: 99%

A case-based reasoning method for discriminating damage levels in ancient wood components based on fuzzy similarity priority

Wang

et al. 2021

BioRes

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In order to rapidly identify internal damage levels accurately in ancient wood components, stress wave detection technology was used to perform simulated damage tests on pine specimens. Based on the detected wave velocity data, the diameter of the specimen, the attenuation coefficient, and the ratio of the wave velocities on the four paths were selected as the discriminant factors for identifying the level of internal damage in the specimens. A case-based reasoning method for discriminating internal damage levels in ancient wood components based on fuzzy similarity priority was proposed. A fuzzy similarity priority relationship between the target case and the source case was established. By introducing the idea of variable weights, the weight of each discriminant factor was determined via the “penalize-excitation” variable weight function. The comprehensive similarity sequences between the target case and the source case were obtained. The source case that was most similar to the target case was used to determine the damage level of the target case. The results showed that this method can quickly and accurately identify the damage levels in ancient wood components, which provides a new method for the safe evaluation of ancient wood buildings.

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Velocity Error Correction Based Tomographic Imaging for Stress Wave Nondestructive Evaluation of Wood

Cited by 12 publications

References 22 publications

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

Single-Sided Microwave Near-Field Scanning of Pine Wood Lumber for Defect Detection

A case-based reasoning method for discriminating damage levels in ancient wood components based on fuzzy similarity priority

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