基于模态柔度差曲率的云杉锯材梁缺陷检测

在机械和环境荷载作用下,木质构件和结构的局部缺陷如节疤、腐朽和裂缝等会导致使用寿命的缩减.在木结构工程领域,如果能够尽早对结构和构件的最薄弱位置进行检出和评估,可避免因突然破坏而导致的灾难性事故.在本研究中,通过振动测试获取前两阶模态振型,并利用锯材梁损伤前后的模态柔度矩阵差值曲率提出损伤识别指标.为了验证提案损伤指标的有效性,通过人工切除截面质量来模拟不同损伤程度、不同损伤位置和双数个损伤的情景,试验结果表明损伤指标对不同程度、不同位置和双数个损伤均能准确定位,并可对损伤轻重程度进行定性评价.     

Damage Detection of Picea asperata Sawn Timber Beams Using Modal Flexibility Curvature

The local damages such as knots,decay, and cracks can be translated into a reduction of service life due to mechanical and environmental loadings.In wood construction,it is very important to evaluate the weakest location and detect damage at the earliest possible stage to avoid the future catastrophic failure.In this study,the modal testing was operated on wood beams to generate the first two mode shapes.A novel statistical algorithm was proposed to extract the damage indicator by computing the modal flexibility curvature before and after damage in timbers.The different damage severities,damage locations,and damage counts were simulated by removing mass from intact beams to verify the algorithm.The results showed that the proposed statistical algorithm was effective and suitable to the designed damage scenarios.It was reliable to detect and locate local damages under different severities,locations,and counts.The peak values of the damage indicators computed from the first two mode shapes were sensitive to different damage severities and locations.They were also reliable to detect the multiple damages.     

Damage detection of wood beams using the differences in local modal flexibility

Local damage such as knots, decay, and cracks can result in a reduction of service life due to mechanical and environmental loadings. In wood construction, it is very important to evaluate the weakest location and to detect damage at the earliest possible stage to avoid future catastrophic failure. In this study, modal testing was carried out on wood beams to generate the first two mode shapes. A novel statistical algorithm was proposed to extract the damage indicator by computing the local modal flexibility before and after damage in timbers. Different damage severities, damage locations, and damage counts were simulated by removing mass from intact beams to verify the algorithm. The results indicated that the proposed statistical algorithm is effective and suitable for the damage scenarios considered. The algorithm was reliable for detecting and locating local damage under different damage scenarios. The peak values of the damage indicators computed from the first two mode shapes were sensitive to different damage severities and locations. This approach was also reliable for detecting multiple defects.     

A wavelet analysis-based approach for damage localization in wood beams

Free vibration testing was conducted to generate the first two mode shapes for damage detection in timbers. A wavelet transform was proposed to postprocess the mode shapes for damage pattern recognition. The wavelet used here was “db3.” The different damage severities, damage locations, and number of damaged areas were simulated by removing mass from intact beams. The results showed that the chosen wavelet db3 is suitable and that the wavelet coefficients are sufficiently sensitive to identify the existence of damage and its location in cases of different damage location, severity, and number. An edge distortion effect was apparent at the two computing edges where the wavelet coefficients were abnormally high. The wavelet coefficients showed dominant spikes around the damage locations and were zero everywhere else except the two computing edges. The dominant spikes coincided well with the damage location.     

Application of modal-based damage-detection method to locate and evaluate damage in timber beams

Modal-based damage-detection algorithms were used to identify the location of defects commonly found in timber and to estimate their severities. In this study, the authors propose modifications to an existing damage-detection algorithm for locating and evaluating damage by comparing the modal strain energy before and after damage using the first two flexural modes of vibration. Experimental verification was performed on pin-pin supported timber beams by employing the algorithms with extracted modal parameters using experimental modal analysis. Single and multiple cases of damage used to simulate pocket(s) of rot with various severities were inflicted by removing sections of timber beam specimens. The proposed damage indicator, computed from the first two flexural modes, was capable of detecting all damage locations. It was also able to estimate, with reasonable accuracy, the severity of damage in term of loss of sectional moment of inertia. The modified damage index method is generally reliable in detecting the location and estimating the severity of simulated defects in timber beams.     

Application of modal analysis by transfer function to nondestructive testing of wood I: determination of localized defects in wood by the shape of the flexural vibration wave

This study was intended to detect nondestructively some defects such as knots and grain deviations in wood using modal analysis. The shapes of flexural vibration waves at the first mode generated by the tapping of wooden beams were determined using the transfer function. The wave shapes obtained were compared with the theoretical wave shape for a uniform material; and the possibility of detecting defects in wood was examined. The results are summarized as follows: (1) The shapes of flexural vibration waves at the first mode of wooden beams free of defects coincided almost completely with the theoretical wave shape. (2) The shapes of flexural vibration waves of wooden beams containing defects such as knots clearly differed from the theoretical wave shape, especially near the defect. (3) Based on these results, it should be possible to detect the presence of defects and to determine their location in wood.Part of this report was presented at the 49th Annual Meeting of the Japan Wood Research Society, Tokyo, April 1999. This article is translated from the Japanese edition published inMokuzai Gakkaishi Vol. 47, No. 4, 1988     

声发射技术在木材加工领域的应用

作为一种主动无损检测方式, 声发射技术通过分析被测物体内部因能量变化所引发的弹性波的特征, 判断物体内部损伤程度并确定损伤位置。声发射技术为木材加工过程应力监测提供了一种主动无损检测模式, 但受木材自身各向异性等特点的限制, 目前声发射技术在木材工业中的应用尚处于探索阶段。为此, 文中重点介绍了目前声发射技术在木材切削加工、木材及木质结构、木材力学性能、木材干燥过程等木材加工过程的应用现状, 并在此基础上根据木材声发射信号特点, 提出一种基于LabView及高速采集设备的木材干燥过程声发射监测系统设计方案。     

含LT型裂纹木梁起裂载荷确定方法的试验研究

木材裂纹萌生的准确判定对木材损伤断裂的评估具有重要的意义,起裂载荷是标定裂纹萌生的关键参数。本试验以杉木为研究对象,利用声发射技术(AE)、数字图像相关法(DIC)和电测法(EM),对含LT型裂纹木梁的损伤断裂特性进行了试验研究。通过研究木梁在加载过程中声发射参数变化规律以及裂尖区域的表面应变信息的演变,分析木梁裂纹萌生规律并确定起裂载荷Pini。结果表明:声发射累计振铃计数、幅度可有效反映木梁内部损伤的产生和演化,利用声发射参数的变化规律能准确确定含LT型裂纹木梁的起裂载荷Pini;数字图像相关法、电测法可以实时监测木梁表面裂缝尖端区域的应变变化,根据应变演变特征可以有效监测木梁表面裂纹的萌生和扩展。声发射技术、数字图像相关法、电测法在确定木梁起裂载荷Pini方面有较好的适用性,所确定的起裂载荷大小为:电测法>数字图像相关法>声发射。试验结果为研究监测含LT型裂纹木材裂纹萌生的试验方法提供了依据,应用时可结合实际工况选择合适的测量方法。     

Relationship between near-infrared (NIR) spectra and the geographical provenance of timber

Since trees record all the environmental factors in the wood, many wood properties are related to the site characteristics. Despite of this fact, identifying the origin of a timber has always been considered a difficult task, and no effective tools are presently available for this purpose. The goal of this study was to verify whether significant differences among groups of the same wood species due to the provenance can be detected with Fourier transform near-infra-red spectroscopy (FT-NIR). Spruce (Picea abies L. Karst.) samples collected from stands in Finland, Northern and Southern Poland and Italy were analyzed using two different approaches: for the first approach samples were collected from four provenances scattered in a wide area throughout Europe, while for the second approach the samples were collected from provenances located in a narrow area within the same region in Italy. For the first approach, all the specimens were clearly divided into groups by using statistical methods. The separation among groups from the narrow local area was actual; even though less significant than in the previous case. It was concluded that trees growing in various locations have somewhat different chemical composition, and FT-NIR is sensitive enough to detect such differences. The presented method could be used for tracking wood provenances and as a technical tool for detecting logs harvested illegally from protected areas.     

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.