Development of Ultrasonic Time-of-Flight Computed Tomography for Hard Wood with Anisotropic Acoustic Property

Yanagida, Hirotaka; Tamura, Yasutaka; Kim, Kwang-Mo; Lee, Jun-Jae

doi:10.1143/jjap.46.5321

Cited by 16 publications

(15 citation statements)

References 5 publications

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“…In this context, little information has been reported concerning time of flight (TOF) measurements in the acoustic and ultrasonic tomography of wood. TOF in the ultrasonic NDT of wood is usually determined from a userfixed threshold (Kanda et al 1998;Beall 2002;Bucur 2006;Yanagida et al 2007). However, statistical techniques such as the Akaike information criterion have also been used as a travel time picker in acoustic tomography (Maurer et al 2006;Schubert 2007;Schubert et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Tomography in standing trees: revisiting the determination of acoustic wave velocity

Arciniegas¹,

Brancheriau

Lasaygues³

2014

Annals of Forest Science

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Context The quality of acoustic tomographic images in standing trees is mainly function of the accuracy of the acous- tic velocity computation. Improving the acoustic velocity determination is, furthermore, of great interest because acous- tic tools are widely used in nondestructive testing of wood. • Aims Four different signal processing algorithms were used (1) to study the effect of the signal dynamic on the velocity determination, (2) to determine the validity range of each computation method, and (3) to compare the behavior be- tween a homogeneous material and wood. • Methods The experiments were performed using the con- ventional experimental protocol for the ultrasonic characteri- zation of materials in a tank (normal incidence transmission at 500 kHz). A polyurethane resin (homogeneous material) and two wood species ( Bagassa guianensis Aubl., Milicia excelsa (Welw.) C.C. Berg) were used for the experiments. • Results Computed velocity increased as the noise level increased. The Hinkley method appeared to be the most exact when the noise level exceeded 10 dB. The Fisher method was that most suitable for very noisy signals. No difference was found between the resin and the wood samples. • Conclusion A combination of the Fisher and Hinkley methods in the same algorithm would yield the most accurate acoustic velocity determinations in the tomography of stand- ing trees. Key message Wood acoustic velocity determination is affect- ed by the wavelength and the detection algorithm used. The Fisher algorithm is optimal with high signal attenuation; oth- erwise, the Hinkley algorithm should be used. (Résumé d'auteur

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Section: Introductionmentioning

confidence: 99%

Tomography in standing trees: revisiting the determination of acoustic wave velocity

Arciniegas¹,

Brancheriau

Lasaygues³

2014

Annals of Forest Science

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“…1). Another approach is to determine a threshold proportional to the maximum amplitude of the Yanagida et al 2007). In general, this question of signal processing was not addressed in the literature reviewed for the specific case of acoustic and ultrasonic tomography.…”

Section: Travel Time Determinationmentioning

confidence: 99%

Literature review of acoustic and ultrasonic tomography in standing trees

Arciniegas

Prieto

Brancheriau

et al. 2014

Trees

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Key message High-resolution imaging is possible if high-frequency sensors are used together with a signalprocessing and inversion algorithm that is well suited to a low signal-to-noise ratio and the effect of wood anisotropy. Wood is a biological growth medium, and given that standing trees adapt themselves in their growth to environmental conditions, their material properties vary with age. These changes result in variations that are far more complex than anisotropy. Wood quality and intraspecific variability can thus be studied to gain an understanding of the development mechanisms of trees, and this can be useful for clonal selection and the management of tree communities. A number of techniques are available to determine wood properties in standing trees, but the signal-processing approaches currently used are not always robust and do not always provide the image resolution needed in the particular cases of acoustic or ultrasonic tomography. This review paper thus aims to present important aspects that should be taken into account when using tomography techniques and addresses a number of open problems. A brief review of current non-destructive wood imaging techniques is initially presented followed by a comparison of the protocols, methods and models used in acoustic and ultrasonic tomography. The devices cited were studied in terms of measurement systems and signal processing. The analysis aimed to highlight and analyze the advantages and disadvantages of each device and describe challenges and trends. The effect of various parameters is discussed: frequency, signal-to-noise ratio, number of sensors and inversion algorithm. General conclusions are then drawn in relation to future signal-processing work in the acoustic and ultrasonic tomography of standing trees. (Résumé d'auteur

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“…In our system, the method of measurement of TOF data was same as the method that was explained in the report of Yanagida et.al [1].…”

Section: B Measurement Of Tof Datamentioning

confidence: 99%

“…Yanagida et.al reported that the ring shaped artifact in the CT image of wood was caused by orthotropic acoustic property of wood. The filtered back projection (FBP) algorithm was used for reconstruction method in their report [1]. When the acoustic impedance changes remarkably between normal part and decay part, the image quality decreases from the influence of refraction and reflection of sound wave.…”

Section: Introductionmentioning

confidence: 99%

Time of flight ultrasonic CT based on ML-EM for wooden pillars

Fan

Guo

Tamura

et al. 2008

2008 IEEE Ultrasonics Symposium

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The ML-EM method was applied to ultrasonic TOF CT. The numerical phantom and the wood phantom were prepared. In the experiments, the number of obtained TOF data is 306. Considering the measurement time and phantom size, it often becomes an upper bound in our ultrasonic system. When the image was reconstructed by only 306 data, the image had many artifacts. To obtain clear image, the interpolation was used. After interpolation, the defect was clearly recognized by CT image.

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Development of Ultrasonic Time-of-Flight Computed Tomography for Hard Wood with Anisotropic Acoustic Property

Cited by 16 publications

References 5 publications

Tomography in standing trees: revisiting the determination of acoustic wave velocity

Tomography in standing trees: revisiting the determination of acoustic wave velocity

Literature review of acoustic and ultrasonic tomography in standing trees

Time of flight ultrasonic CT based on ML-EM for wooden pillars

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