Wood Nondestructive Testing Research Articles

Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign.

This study systematically developed a deep transfer network for near-infrared spectrum detection using convolutional neural network modules as key components. Through meticulous evaluation, specific modules and structures suitable for constructing the near-infrared spectrum detection model were identified, ensuring its effectiveness. This study extensively analyzed the basic network components and explored three unsupervised domain adaptation structures, highlighting their applications in the nondestructive testing of wood. Additionally, five transfer networks were strategically redesigned to substantially enhance their performance. The experimental results showed that the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network outperformed the Direct Standardization, Piecewise Direct Standardization, and Spectral Space Transformation models. The coefficients of determination for the Conditional Domain Adversarial Network and Globalized Loss Optimization Transfer network are 82.11% and 83.59%, respectively, with root mean square error prediction values of 12.237 and 11.582, respectively. These achievements represent considerable advancements toward the practical implementation of an efficient and reliable near-infrared spectrum detection system using a deep transfer network.

Research on stress wave wood nondestructive testing technology

As a kind of nondestructive testing technology, stress wave technology has the advantages of long propagation distance, strong anti-interference ability and convenient use, and has become one of the important means to detect wood properties and defects at home and abroad. This paper introduces several stress wave wood testing equipment commonly used in the field of wood non-destructive testing at this stage, and analyzes its characteristics. The research status of stress wave wood nondestructive testing technology is analyzed from three aspects: mechanical property testing, internal defect testing and factors affecting stress wave propagation velocity. Finally, the existing problems and development trends of stress wave technology in wood nondestructive testing are discussed to provide reference for further research in this field.

The effect of the changes in chemical composition due to thermal treatment on the mechanical properties of Pinus densiflora

Wood’s chemical composition has a close relationship to its mechanical properties. Therefore, chemical analysis such as FTIR spectroscopy offers a reasonable non-destructive method to predict wood strength. Pine (Pinus densiflora) specimens were thermal-treated in different conditions (aerobic and anaerobic) and evaluated by 3-point bending test for modulus of rupture (MOR) and by FTIR spectroscopy for chemical composition. Density and moisture content changes were also assessed in this study. The result showed that both density and equilibrium moisture content at 20 °C with 65 % humidity change little at low treatment temperatures, but they decrease at high treatment temperatures and when treated in the presence of oxygen. The MOR was improved by the reactions that occurred, including cellulose crystallisation, lignin condensation and cross-linking, whereas it was decreased by degradation reactions. The MOR were well predicted by two FTIR peak at 1318 cm−1 (relating to CH2 bond and condensation of G-ring of lignin), and at 1730 cm−1 (pertaining to changes to carbonyl groups in hemicelluloses) and density. It was concluded that FTIR spectroscopy provides a suitable method for wood non-destructive mechanical testing.

Scientific Computational Visual Analysis of Wood Internal Defects Detection in View of Tomography Image Reconstruction Algorithm

With the development of non-destructive testing technology and computer technology, wood non-destructive testing technology will develop towards intelligence and automation. The primary condition for development is to be able to carry out the testing of various physical properties of wood without destroying the wood itself. Wood defects refer to abnormal wood structure. Its existence will affect the quality of wood, change the normal performance of wood, and reduce the utilization rate and use value of wood. The purpose of this article is to try to find an effective detection method without damaging the original structure of the wood. It can accurately and quickly determine the defect information on the wood surface. This research mainly discusses the visual analysis of wood internal defect detection based on tomographic image reconstruction algorithm. According to the analysis of the planks to be tested, this paper determines the structural characteristics, the types of defects to be tested, and the classification standards. To analyze the principle of machine vision imaging, this paper designs a hardware experiment system for wood board imaging, by observing the collected Biyun Temple building wood images and summarizing the Biyun Temple building wood defects, surface texture features, and various appearance features in the image. Based on digital image processing technology, this paper designs a complete set of real-time timber classification and detection algorithms. The algorithm realizes the extraction of Biyun Temple’s architectural wood region, texture region extraction, and the comprehensive feature vector extraction of Biyun Temple’s architectural wood. In the image preprocessing stage, the color image is converted into a grayscale image through the grayscale processing of the image. Through the equalization processing of the histogram, the defect features in the defect image are highlighted. Through image smoothing and denoising processing, the noise points that may exist in the image are removed. The signal-to-noise ratio of the Marching Cube algorithm is maintained at a relatively high level under different noise conditions, which is about 3-4db higher than the Gaussian method with OPED. This research is helpful for the continuation and inheritance of ancient architectural attainments.

Wood species identification using terahertz time-domain spectroscopy

A new method for wood identification using terahertz (THz) time-domain spectroscopy (TDS) is presented. THz-TDS technology is an emerging method of spectral analysis method that shows great advantages in wood non-destructive testing. Wood is opaque in the optical and near infrared spectrum, and relatively transparent in the THz band. In this experiment, four wood species (Pinus densiflora, Pinus sylvestris, Pseudotsuga menziesii, and Cunninghamia lanceolata) were selected as samples. Optical parameters such as absorption coefficient and refractive index of the measured samples can be extracted from THz time-domain spectra. Principal component analysis was introduced to reduce the dimensionality of the THz spectral data of the wood. The principal component score matrix of the wood was obtained and used as a characteristic matrix. A wood classification model was established using a support vector machine. The experimental results showed that THz-TDS had excellent performance in wood recognition. This research lays a theoretical and application foundation for the application of THz technology in the field of wood detection and recognition. It also provides a new direction and technical scheme in the wood identification field.

The Detection of Structure in Wood by X-Ray CT Imaging Technique

Medical computed tomography (CT) has been used in forestry science and the wood industry to explore the internal structures of trees in a non-destructive way. The wood material has great diversity in structure, density, and size. The software system for medical CT is not applicable to analyze and process sectional images of wood. In order to solve this problem, a CT imaging system, based on the principle of X-ray fan-beam scanning, was constructed for this study. The computer tomography technique was applied in the non-destructive testing of wood. Four kinds of representative specimens—laminated wood, multi knot logs, large diameter logs, and small diameter logs—were selected as scanned objects. The sinusoidal images and sectional images were reconstructed with scanning data. The results showed that the accuracy of CT images is determined by the information in the sinusoidal images, from which the shapes and locations of cracks and knots can be identified. The internal properties of wood in some tomography, such as the size, number, and location of cracks and knots, the number of tree rings, and the growth law of early wood and late wood can be visually observed. Finally, the feasibility and validity of the CT imaging system was tested as a non-destructive method for verifying the internal structures of wood.

激光超声在木材无损检测中的仿真研究

激光超声在木材无损检测中的仿真研究

Development of Testing Platform and Comparison Studies for Wood Nondestructive Testing

Stress wave based techniques have been developed for evaluating the quality of the wooden materials nondestructively. However the existing techniques have some shortcomings due to the significant variation of the wood properties and are now in need of updating. There are also stress wave based instruments which have been widely used for nondestructive testing of wood. But most of them are inflexible and unsuitable for the tentative studies. This paper proposed and implemented a wood nondestructive testing platform based on NI virtual instrument. Three wood nondestructive testing methods, including peak time interval measurement, cross-correlation, and spectrum analysis, were also tested on this platform with serious decay sample, early decay sample, and defect-free sample. The results show that new methods can be verified easily and the researches of wood nondestructive testing will be accelerated with the designed platform.

ORIENTATION AND POSITION EFFECTS OF A LOCAL HETEROGENEITY ON FLEXURAL VIBRATION FREQUENCIES IN WOODEN BEAMS

Studying the influence of defect on the dynamic behavior of wood in order to detect the local heterogeneities is of great importance in non-destructive testing of wood. The natural heterogeneities in wood are oriented in a volume. However, one-dimensional models are still used in dynamic characterization of wooden beams. The aim of this study was to experimentally investigate the effects of the orientation and position of an artificial defect on the flexural vibration frequencies. Different batches of Fagus orientalis specimens were drilled in the radial direction at five positions along the specimen. Dynamic tests in free flexural vibration were performed on the specimens before and after drilling both in the longitudinal-radial (LR) and longitudinal-tangential (LT) bending plan. The behavior in free flexural vibration was found to be different depending on the position and orientation of heterogeneity. When the drilling axis lies in the bending plane (LR), the weakening of frequency was maximal at the location of an antinode of vibration. On the contrary, the frequency offset was maximal in the place of a vibration node when the drilling axis was orthogonal to the bending plane (LT).

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

The quality of acoustic tomographic images in standing trees is mainly function of the accuracy of the acoustic velocity computation. Improving the acoustic velocity determination is, furthermore, of great interest because acoustic tools are widely used in nondestructive testing of wood. 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 between a homogeneous material and wood. The experiments were performed using the conventional experimental protocol for the ultrasonic characterization 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. 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. A combination of the Fisher and Hinkley methods in the same algorithm would yield the most accurate acoustic velocity determinations in the tomography of standing trees. Wood acoustic velocity determination is affected by the wavelength and the detection algorithm used. The Fisher algorithm is optimal with high signal attenuation; otherwise, the Hinkley algorithm should be used.

Utilizing wave polarization in microwave characterization of heterogeneous anisotropic materials with application to the wood industry

Abstract This paper presents a novel approach to microwave non-contact, non-destructive testing of wood, investigating additional indicators of wood structure, in particular the significance of wave polarization in transmission measurements. Contribution of wave polarization to wood characterization is studied, considering detection of rapid and gradual variations in wood structure, determination of moisture content and density distribution along the sample, as well as bulk properties detection. A set of microwave sensors in a collinear arrangement was used in two orthogonal linear polarizations. Significant findings are reported, in particular polarization dependence of moisture related attenuation, as well as improved defect detection accuracy when measurements in two orthogonal linear polarizations are considered. In addition, sorting wood samples into categories is considered and the advantages of this approach are presented.

Non-destructive testing of wood and wood-based materials

Abstract Methods of non-destructive wood testing continue to gain importance. Online tools, for example to control production, have effectually been in use for years. Based on a measuring systematics (physically active principle and important influencing factors), a summary of methods to assess cultural heritage objects is given. To adopt methods based on physical effects, profound knowledge of wood physics is essential, particularly knowledge of interdependencies.

A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals

Ensemble empirical mode decomposition (EEMD) has been recently used to recover a signal from observed noisy data. Typically this is performed by partial reconstruction or thresholding operation. In this paper we describe an efficient noise reduction method. EEMD is used to decompose a signal into several intrinsic mode functions (IMFs). The time intervals between two adjacent zero-crossings within the IMF, called instantaneous half period (IHP), are used as a criterion to detect and classify the noise oscillations. The undesirable waveforms with a larger IHP are set to zero. Furthermore, the optimum threshold in this approach can be derived from the signal itself using the consecutive mean square error (CMSE). The method is fully data driven, and it requires no prior knowledge of the target signals. This method can be verified with the simulative program by using Matlab. The denoising results are proper. In comparison with other EEMD based methods, it is concluded that the means adopted in this paper is suitable to preprocess the stress wave signals in the wood nondestructive testing.

Denoising Method of Wood Defect Images Based on Wavelet Packet Combined with Gray-Scale Morphological Filtering

Excessive noise was joined with the acquiring wood defect images process in wood non-destructive testing. The image quality was affected. Wavelet packet transform could decompose high frequency and low frequency of signal at the same time. There were characteristics of open and closed in Gray-scale Morphology. Denoising method of wood defect images based on wavelet packet combined with gray-scale morphological filtering was proposed. Compared with the traditional denoising method, the method received better Peak Signal to Noise Ratio (PSNR) and visual effect. Experimental results verified the feasibility and effectiveness of this method.

Using Stress Wave Based Technology for Wood Material Nondestructive Testing

Stress wave based technology has its special advantages in the field of wood nondestructive testing and quality evaluation. To analysis the propagating properties of stress wave in the wood material, a transmitting model in anisotropic material was introduced in rectangular and cylindrical polar coordinate system. The relationship between stress wave propagation and elastic constants was shown. The propagating of stress wave in wood material and the possible solutions with different parameters were studied. The transmitting character of stress wave in symmetry planes was analyzed, and the elastic constants of woods were used to compute the stress wave propagation in wood material.

Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition

Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood.

Non-destructive testing of wood using ultrasonic technique

Non-Destructive Testing (NDT) identifies the physical and mechanical properties of material without altering its end-use capabilities. NDT for wood is used to measure natural and environmentally induced irregularities to determine its mechanical properties. This paper discusses the basic operation, design and experimental technique for contact-type ultrasonic NDT method to find the wood properties. The experiment was performed using two piezoelectric ultrasonic transducers. The received time signal was analysed by getting the Fast Fourier Transform (FFT) and Power Spectral Density (PSD) using MATLAB and results are shown. The wood sample was also applied with compressive test (Destructive Testing) to find the strength of the wood sample.

Effect of sensor quantity on measurement accuracy of log inner defects by using stress wave

Wood nondestructive testing (NDT) is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on defect testing results by using stress wave in terms of image fitting degree and error rate. The results showed that for logs with diameter ranging from 20 to 40 cm, at least 12 sensors were needed to meet the requirement which ensure a high testing accuracy of roughly 90% of fitness with 0.1 of error rate. And 10 sensors were recommended to judge the possible locations of defects and 6 sensors were sufficient to decide whether there were defects or not.

Application of the Fourier analysis to determine the demarcation between juvenile and mature wood

Juvenile wood produced in the crown has features that distinguish it from the older, more mature wood of the bole. Juvenile wood has important wood quality attributes because, depending on the species, it can have lower density and has shorter tracheids, thin-walled cells, larger fibrial angles, high – more than 10% – lignin and hemicellulose content, and a slightly lower cellulose content than mature wood. Wood juvenility can be established by examining a number of different physical or chemical properties. Juvenile wood is not desirable for solid wood products because of warpage during drying, low strength properties, and other factors considered critical for producing high-stiffness veneer. Fourier transformation is an extremely useful mathematical tool that has been applied in the quantitative analysis of many physical processes. Fourier transformation can be represented as a series of sine and cosine functions. Density spectra derived from X-ray imaging provide new information in the nondestructive testing of wood. Until recently, testing for wood juvenility required wood samples to be milled, dissolved in acids, and painstakingly analyzed for certain anatomical features. The new method proposed in this report opens a new possibility for minimizing the time required to analyze wood formation. The main purpose of this report is thus to demonstrate how to distinguish juvenile wood from mature wood by Fourier analysis of density distribution curves. It is also the first study to employ Fourier analysis-assisted assays of the boundary line between juvenile and mature wood.

Log scanning through combination of ultrasonics and artificial intelligence : Han, W.; Birkeland, R. Proceedings of the 8th Symposium on the Nondestructive Testing of Wood, Vancouver, Washington (United States), 23–25 Sep. 1991. pp. 163–187. Conferences and Institutes Washington State University (1992)

Log scanning through combination of ultrasonics and artificial intelligence : Han, W.; Birkeland, R. Proceedings of the 8th Symposium on the Nondestructive Testing of Wood, Vancouver, Washington (United States), 23–25 Sep. 1991. pp. 163–187. Conferences and Institutes Washington State University (1992)