基于冲击应力波测试法的阔叶材原木质量评估

摘要
图/表
参考文献(27)
相关文章 (15)

全文: PDF (3406 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要阔叶材原木的质量评估可以为行业提供最优的阔叶材资源利用价值，但低成本、便捷、快速地评估阔叶材原木质量一直是严峻的挑战。基于此，提出了一种冲击应力波测试的质量评估方法，利用矩分析和小波变换提取两种声评估参数——时间中心和阻尼比，并详细推导了基于连续小波变换的阻尼比提取过程。应用该方法对阔叶材样本原木进行分等，原木板材锯切结果对比表明，基于时间中心和阻尼比的原木质量预测分等中，高质量组中的实测高等级板材占有率分别为74.2%和74.0%，低等级板材占3.2%和3.3%；而低质量分组中实测高等级板材分别占21.8%和28.5%，低等级板材占11.2%和8.3%。与传统的声速分等相比，高质量分组中高等级板材占有率提高了约26%，而低质量组中高等级板材占有率降低了15%以上。鉴于木材的变异性和阔叶材缺陷的多样性，综合考虑多个参数的分等结果可能是最佳选择。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	杨扬
	瞿玉莹
	徐锋

关键词 ：阔叶材原木, 质量评估, 声速, 阻尼比, 时间中心, 连续小波变换

Abstract：Quality assessment of hardwood log can provide the best usage value of broad-leaved wood resources for industry, but a low-cost, convenient and fast method to evaluate quality of hardwood log is a serious challenge. Here, a quality evaluation method based on impact stress wave testing was proposed. The moment analysis and wavelet transform were used to extract two acoustic evaluation parameters of time centroid and damping ratio, and derive the extraction process of damping ratio based on the continuous wavelet transform in detail. The proposed method was applied to classify samples of hardwood log. The cutting results of log boards showed that for log quality’s predicted grade results based on time centroid and damping ratio, respectively, in high quality log groups, high-grade boards occupancies are 74.2% and 74.0%, respectively, while low-grade boards occupancies are 3.2% and 3.3%, respectively; however, in low-quality log groups, high-grade boards occupancies are 21.8% and 28.5%, respectively, while low-grade boards occupancies are 11.2% and 8.3%, respectively; compared with log quality’s predicted grade results according to the traditional acoustic velocity, in high quality log groups, high-grade boards occupancy is increased by about 26%, while in low-quality log groups, high-grade boards occupancy is decreased by more than 15%; in view of the variability of wood and the diversity of hardwood defects, comprehensively considering the predicted grade results according to various parameters may be the best choice.

Key words： hardwood log quality evaluation acoustic velocity damping ratio time centroid CWT

收稿日期: 2018-09-10 出版日期: 2019-06-28

引用本文:

杨扬，瞿玉莹，徐锋. 基于冲击应力波测试法的阔叶材原木质量评估[J]. 振动与冲击, 2019, 38(13): 126-134.
YANG Yang, QU Yuying, XU Feng. Quality evaluation of hardwood log based on impact stress wave testing. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(13): 126-134.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I13/126

[1] Wiedenbeck J, Wiemann M, Alderman D, et al. Defining hardwood veneer log quality attributes [R]. Gen. Tech. Rep. NE-313. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station, 2003, 36.
[2] Wang X, Wiedenbeck J, Liang S. Acoustic tomography for decay detection in black cherry trees [J]. Wood and Fiber Science, 2009, 41(2):127-137.
[3] Chang S. External and internal defect detection to optimize cutting of hardwood logs and lumber [R]. Transferring Technologies for Industry No. 3. Beltsville, MD: U.S. Department of Agriculture, National Agriculture Library, 1992, 24.
[4] Hyvärinen MJ. Measuring quality in standing trees-depth of knot-free wood and grain orientation under sugar maple bark distortions with underlying knots [D]. Doctoral Dissertation: University of Michigan, 1976, 142.
[5] Lemieux H, Beaudoin M, Zhang SY. Characterization and modeling of knots in black spruce (picea mariana) logs [J]. Wood and Fiber Science, 2001, 33(3):465-475.
[7] Carter P, Briggs D, Ross RJ, et al. Acoustic testing to enhance western forest values and meet customer wood quality needs [R]. PNW-GTR642. USDA Forest Service, Pacific Northwest Research Station, Portland, OR, 2005, 121-129.
[8] Wang X, Ross RJ, McClellan M, et al. Nondestructive evaluation of standing trees with a stress wave method[J]. Wood Fiber Sci, 2001, 33(4):522-533.
[9] Wang X, Ross RJ, Brashaw BK, et al. Diameter effect on stress-wave evaluation of modulus of elasticity of small-diameter logs [J]. Wood and Fiber Science, 2004, 36(3):368-377.
[10] Wang X. Acoustic measurements on trees and logs: a review and analysis [M]. Wood Science and Technology, 2013, 47:965-975
[11] Tiitta M, Biernacki JM, Beall FC. Acousto-ultrasonic assessment of internal decay in glulam beams [J]. Wood and Fiber Science, 1998, 30(3):24-37.
[12] Bayissa WL, Haritos N, Thelandersson S. Vibration-based structural damage identification using wavelet transform [J]. Mechanical Systems and Signal Processing, 2008, 22 (5):1194-1215.
[13] 滕军，朱焰煌，周峰，等. 基于Morlet小波变换的大跨空间结构模态参数识别研究[J]. 振动与冲击，2009, 28(8):25-29.
Teng J, Zhu Y, Zhou F, et al. Modal parameters identification of large-span spatial structures based on complex morlet wavelet transform [J]. Journal of Vibration and Shock, 2009, 28(8):25-29.
[14] Le TP, Paultre P, Modal identiﬁcation based on the time-frequency domain decomposition of unknown-input dynamic tests [J]. International Journal of Mechanical Sciences, 2013, 71: 41-50
[15] Staszewski WJ. Identification of damping in MDOF systems using time-scale decomposition [J]. Journal of Sound and Vibration, 1997, 203(2):283-305.
[16] Ülker-Kaustell M, Karoumi R. Application of the continuous wavelet transform on the free vibrations of a steel-concrete composite railway bridge [J]. Engineering Structures, 2011,33: 911-919.
[17] Beall FC. Overview of the use of ultrasonic technologies in research on wood properties [J]. Wood Science and Technology, 2002, 36(3):197-212.
[18] Senalik CA. Detection and assessment of wood decay glulam beams and wooden utility poles [D]. Doctor Dissertation, University of Illinois at Urbana-Champaign, Systems and Entrepreneurial Engineering in the Graduate College, USA, 2013.
[19] S.Mallat, A wavelet tour of signal processing [M], 2nd edition, Academic Press, New York, 1999.
[20] Staszewski WJ. Identification of damping in MDOF systems using time-scale decomposition [J]. Journal of Sound and Vibration, 1997, 203(2):283-305.
[21] R. Kronland-martinet, J. Morlet, A. Grossmann. Analysis of sound patterns through wavelet transforms [J]. International Journal of Pattern Recognition and Artificial Intelligence, 1987, 1(2):273-302.
[22] Delprat N, Escudié B, Guillemain P, et al. Asymptotic wavelet and Gabor analysis: extraction of instantaneous frequencies [J]. IEEE Trans Inf Theory, 1992, 38(2):644–64.
[23] Carmona R, Hwang W, Torrésani B. Practical time-frequency analysis: Gabor and wavelet transforms with an implementation in S (1st edition) [M]. Academic Press, Inc. San Diego, CA.1998.
[24] ASTM 2003. Standard test methods for direct moisture content measurement of wood and wood-base materials. ASTM D4442-92. America Society for Testing and Materials. Philadelphia, PA.
[25] National Hardwood Lumber Association. Rules for the measurement and inspection of hardwood and cypress [M]. Memphis, Tennessee, U.S.A. 2015:104.
[26] 徐锋，刘云飞，宋军.基于中值滤波-SVD和EMD的声发射信号特征提取[J].仪器仪表学报，2011,32(12): 2712-2719.
Xu F, Liu YF, Song J. Feature extraction of acoustic emission signals based on median filter-singular value decomposition and empirical mode decomposition[J]. Chinese Journal of Scientific Instrument, 2011, 32(12):2712-2719.
[27] Wang X, Stelzer HE, Wiedenbeck J, et al. Assessing wood quality of borer-infested red oak logs with a resonance acoustic technique [J]. Wood and Fiber Science, 2009, 41(2):180-193.