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A review of the nondestructive testing of wood based on acoustics |
ZHANG Qinghui1, DAI Yang1, LI Junqiu1, ZHONG Lihui1, LAN Zengquan2 |
1. College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming 650224, China;
2. Ecological Tea(Forest Tea) Research Center, Southwest Forestry University, Kunming 650224, China |
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Abstract: Due to its advantages of low cost, portability and easy field operation, no radiation, and fast detection speed, the acoustic-based non-destructive testing method has been widely applied in the area of wood materials. In this paper, we present first the basic principles of common acoustic-based nondestructive testing methods, including the impact stress wave method, the ultrasonic method, the resonance method, the acoustic emission, the acousto-ultrasonics, and the tomography technology, and analyze and compare their characteristics. Then, we review the applications of these methods in the wood industry, such as the evaluation of physical and mechanical properties of wood and the detection of wood internal defects, and the studies of improving the detection accuracy, and analyze the difficulties in the acoustic-based wood non-destructive testing. Finally, we discuss the development trend of the wood non-destructive testing equipment in terms of signal source, signal transmission mechanism, signal analysis and processing, portability and real-time performance, and point out that the emergence of new theories and technologies will greatly promote the development of non-destructive detection for wood.
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Received: 26 June 2019
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[1] Bucur V. Acoustics of wood[M]. Second Edition. New York:Springer Science & Business Media, 2006:217-240.
[2] 王礼立. 应力波基础[M]. 2版. 北京:国防工业出版社, 2005:1-4.
[3] 杨洋, 申世杰. 木材无损检测技术研究历史、现状和展望[J]. 科技导报, 2010, 28(14):113-117.
[4] Vary A. The acousto-ultrasonic approach[M]//Duke J C ed. Acousto-Ultrasonics. Boston:Springer, 1988:1-21.
[5] Bucur V. Nondestructive characterization and imaging of wood[M]. New York:Springer Science & Business Media, 2003:181-214.
[6] Paschalis P. Bestimmung der korrelation zwischen ausgewahlten festigkeitseigenschaften und strukturmerkmalen von holz mit anwendung des resonanz und ultraschallverfahrens[J]. Holztechnologie, 1978:14-17.
[7] Bucur V, Archer R R. Elastic constants for wood by an ultrasonic method[J]. Wood Science & Technology, 1984, 18(4):255-265.
[8] Hasegawa M, Sasaki Y. Acoustoelastic birefringence effect in wood I:Effect of applied stresses on the velocities of ultrasonic shear waves propagating transversely to the stress direction[J]. Journal of Wood Science, 2004, 50(1):47-52.
[9] Dzbeński W, Wiktorski T. Ultrasonic evaluation of mechanical properties of wood in standing trees[C]//COST E 53 Conference-Quality Control for Wood and Wood Products, Warsaw 15-17 Oct, 2007:15-17.
[10] Yin Y, Nagao H, Liu X, et al. Mechanical properties assessment of Cunninghamia lanceolata plantation wood with three acoustic-based nondestructive methods[J]. Journal of Wood Science, 2009, 56(1):33-40.
[11] 张训亚. 兴安落叶松木材性质的声-超声技术预测[D]. 北京:中国林业科学研究院, 2011.
[12] Kohlhauser C, Hellmich C. Determination of Poisson's ratios in isotropic, transversely isotropic, and orthotropic materials by means of combined ultrasonic-mechanical testing of normal stiffnesses:Application to metals and wood[J]. European Journal of Mechanics-A/Solids, 2012(33):82-98.
[13] Ruy M, Gonçalves R, Pereira D M, et al. Ultrasound grading of round Eucalyptus timber using the Brazilian standard[J]. European Journal of Wood and Wood Products, 2018, 76(3):889-898.
[14] McDonald K, Cox R, Bulgrin E. Locating lumber defects by ultrasonics[M]. Wisconsin:US Forest Products Laboratory, 1969.
[15] Dunlop J I. Testing of poles by using acoustic pulse method[J]. Wood Science & Technology, 1981, 15(4):301-310.
[16] Bucur V. Technique ultrasonore de caractérisation du degré d'altération des bois de hêtre et de pin Soumis à l'Attaque de différents champignons:Holzforschung[J]. Holzforschung-International Journal of the Biology, Chemistry, Physics and Technology of Wood, 1991, 45(1):41-46.
[17] Bütler R, Patty L, Le Bayon R C, et al. Log decay of Picea abies in the Swiss Jura Mountains of central Europe[J]. Forest Ecology and Management, 2007, 242(2/3):791-799.
[18] Kazemi-Najafi S, Shalbafan A, Ebrahimi G. Internal decay assessment in standing beech trees using ultrasonic velocity measurement[J]. European Journal of Forest Research, 2009, 128(4):345-350.
[19] 张甜, 程小武, 陆伟东, 等. 超声波法检测木材内部孔洞缺陷的研究[J]. 西南林业大学学报, 2016, 36(1):121-125.
[20] El-Hadad A. Using acoustic emission technique with Matlab® analysis to detect termites in timber-in-service[D]. Melbourne:The University of Melbourne, 2017.
[21] Tomikawa Y, Iwase Y, Arita K, et al. Nondestructive inspection of a wooden pole using ultrasonic computed tomography[J]. IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control, 1986, 33(4):354-8.
[22] Nicolotti G, Socco L, Martinis R, et al. Application and comparison of three tomographic techniques for detection of decay in trees[J]. Journal of Arboriculture, 2003, 29(2):66-78.
[23] Brazee N J, Marra R E, Gocke L, et al. Non-destructive assessment of internal decay in three hardwood species of northeastern North America using sonic and electrical impedance tomography[J]. Forestry, 2010, 84(1):33-39.
[24] 刘铁男. 基于超声波活立木内部腐朽衰减成像的研究[D]. 哈尔滨:东北林业大学, 2010.
[25] 王娜. 基于超声波传播场的原木及板材空洞缺陷定量检测[D]. 哈尔滨:东北林业大学, 2012.
[26] de Oliveira F G R, Candian M, Lucchette F F, et al. A technical note on the relationship between ultrasonic velocity and moisture content of Brazilian hardwood (Goupia glabra)[J]. Building and Environment, 2005, 40(2):297-300.
[27] Wang L H, Xu H D, Zhou C L, et al. Effect of sensor quantity on measurement accuracy of log inner defects by using stress wave[J]. Journal of Forestry Research, 2007, 18(3):221-225.
[28] Wang N, Wang L H. Response of ultrasonic wave velocity to wood structure defect of Korean Pine[C]//Advanced Materials Research. Zurich:Trans Tech Publications Ltd, 2011, 311:1609-1613.
[29] Wang N, Wang L H, Xu H D. Effect of emission points on ultrasonic testing accuracy of log internal decay[J]. Advanced Materials Research, 2011(337):682-685.
[30] Wang N, Wang L H, Xu H D. The prediction on the size and location of internal defects of standing trees using ultrasonic technology[C]//Key Engineering Materials.Zurich:Trans Tech Publications Ltd, 2011(467):1838-1845.
[31] Gao S, Wang N, Wang L H, et al. Application of an ultrasonic wave propagation field in the quantitative identification of cavity defect of log disc[J]. Computers and Electronics in Agriculture, 2014(108):123-129.
[32] 高珊. 环境温度对美国红松活立木及原木声波传播及力学特性的影响[D]. 哈尔滨:东北林业大学, 2012.
[33] 高珊, 王立海, 杨冬辉, 等. Sylvatest-Duo装置的探针触式与计示压强对木材超声波测量精度的影响[J]. 浙江农林大学学报, 2016(5):875-880.
[34] Gonçalves R, Lorensani R G M, Negreiros T O, et al. Moisture-related adjustment factor to obtain a reference ultrasonic velocity in structural lumber of plantation hardwood[J]. Wood Material Science & Engineering, 2017, 13(5):254-261.
[35] El-Hadad A, Brodie G I, Ahmed B S. The Effect of wood condition on sound wave propagation[J]. Open Journal of Acoustics, 2018, 8(3):37-51.
[36] 冯海林, 李光辉. 木材无损检测中的应力波传播建模和仿真[J]. 系统仿真学报, 2009(8):258-261.
[37] 余斌, 高珊, 王立海, 等. 超声波在原木内部传播理论研究[J]. 森林工程, 2014, 30(1):92-95.
[38] Liu L, Li G H. Acoustic tomography based on hybrid wave propagation model for tree decay detection[J]. Computers and Electronics in Agriculture, 2018(151):276-285.
[39] Sarnaghi A K, van de Kuilen J W G. Strength prediction of timber boards using 3D FE-analysis[J]. Construction and Building Materials, 2019(202):563-573.
[40] Esteban L G, Fernández F G, Palacios P D. MOE prediction in Abies pinsapo Boiss. timber:Application of an artificial neural network using non-destructive testing[J]. Computers & Structures, 2009, 87(21/22):1360-1365.
[41] Wang L, Li L, Qi W, et al. Pattern recognition and size determination of internal wood defects based on wavelet neural networks[J]. Computers and Electronics in Agriculture, 2009, 69(2):142-148.
[42] Saadat-Nia M, Brancheriau L, Gallet P, et al. Ultrasonic wave parameter changes during propagation through poplar and spruce reaction wood[J]. BioResources, 2011, 6(2):1172-1185.
[43] Brancheriau L, Ghodrati A, Gallet P, et al. Application of ultrasonic tomography to characterize the mechanical state of standing trees(Picea abies)[J]. Journal of Physics:Conference Series, 2012, 353(1):012007.
[44] Moreno L F E, Arciniegas A, Prieto F A, et al. Standing tree decay detection by using acoustic tomography images[C]//Twelfth International Conference on Quality Control by Artificial Vision 2015. Le Creusot:International Society for Optics and Photonics, 2015(9534):4.
[45] Metwally K, Lefevre E, Baron C, et al. Measuring mass density and ultrasonic wave velocity:A wavelet-based method applied in ultrasonic reflection mode[J]. Ultrasonics, 2016(65):10-17.
[46] Miguel E P, Melo R R, Serenini Junior L, et al. Using artificial neural networks in estimating wood resistance[J]. Maderas. Ciencia y tecnología, 2018, 20(4):531-543.
[47] Berndt H. Propagation of elastic waves in wood:Modeling and measurement[D]. California:University of California at Berkeley, 1998.
[48] Berndt H, Johnson G C. Examination of wave propagation in wood from a microstructural perspective[M]//Thompson DO, Chimenti DE, eds. Review of Progress in Quantitative Nondestructive Evaluation. Boston:Springer, 1995:1661-1668.
[49] Berndt H, Schniewind A, Johnson G. High-resolution ultrasonic imaging of wood[J]. Wood Science and Technology, 1999, 33(3):185-198.
[50] Ramalli A, Guidi F, Boni E, et al. A real-time chirpcoded imaging system with tissue attenuation compensation[J]. Ultrasonics, 2015(60):65-75.
[51] Rouyer J, Mensah S, Vasseur C, et al. The benefits of compression methods in acoustic coherence tomography[J]. Ultrasonic Imaging, 2015, 37(3):205-223.
[52] Lim H J, Sohn H, Kim Y. Data-driven fatigue crack quantification and prognosis using nonlinear ultrasonic modulation[J]. Mechanical Systems and Signal Processing, 2018(109):185-195. |
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