Structural Stiffness Identification of Traditional Mortise-Tenon Joints Based on Statistical Process Control Chart
Publication: Journal of Aerospace Engineering
Volume 31, Issue 5
Abstract
This paper proposes a novel index, the extreme value of the largest principal component scores of the generalized likelihood ratio based on the statistical process control chart, to develop a structural stiffness identification method for assessing traditional Chinese mortise-tenon joints. The proposed method involves four stages. First, a generalized likelihood ratio test is conducted by transforming the collected acceleration signals into the generalized likelihood ratio matrix. Second, principal component analysis (PCA) is used to reduce data dimensionality and extract the extreme values of the first principle component scores as a novel control index. Subsequently, a statistical process control chart is drawn via the proposed control index. Finally, the ratio of the structural stiffness reduction can be evaluated by establishing the relationship between the stiffness and number of control indices outside the upper and lower control limits in the statistical process control chart. The proposed method is validated by vibration test data acquired from a traditional timber frame under reversed cyclic loads and vibration in a laboratory. The results show that (1) the proposed index performed in the statistical process control chart is able to monitor the novelty of the mortise-tenon timber joint; and (2) the proposed method can be used to assess the states of the timber structure and even predict further structural stiffness.
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Acknowledgments
The work described in this paper was partially supported by the National Natural Science Foundation of China (No. 51678156). In addition, the authors appreciate the sincere help of Professor G. Song and Dr. Q. Kong from the University of Houston and also thank the anonymous referees for their constructive comments and suggestions.
References
Au, S. K., and F. L. Zhang. 2015. “Fundamental two-stage formulation for Bayesian system identification. I: General theory.” Mech. Syst. Sig. Process. 66 (1): 31–42. https://doi.org/10.1016/j.ymssp.2015.04.025.
Cavalli, A., and M. Togni. 2015. “Monitoring of historical timber structures: State of the art and prospective.” J. Civ. Struct. Health Monit. 5 (2): 107–113. https://doi.org/10.1007/s13349-014-0081-8.
Chang, W. S., J. Shanks, A. Kitamori, and K. Komatsu. 2009. “The structural behaviour of timber joints subjected to bi-axial bending.” Earthquake Eng. Struct. Dyn. 38 (6): 739–757. https://doi.org/10.1002/eqe.854.
Chinese Standard. 1997. Specification of test methods for earthquake resistant building. [In Chinese.] JGJ101-96. Beijing: Architecture Industry Press.
Choi, F. C., J. Li, B. Samali, and K. Crews. 2007. “An experimental study on damage detection of structures using a timber beam.” J. Mech. Sci. Technol. 21 (6): 903–907. https://doi.org/10.1007/BF03027066.
Döhler, M., L. Mevel, and F. Hille. 2014. “Subspace-based damage detection under changes in the ambient excitation statistics.” Mech. Syst. Sig. Process. 45 (1): 207–224. https://doi.org/10.1016/j.ymssp.2013.10.023.
Fugate, M. L., H. Sohn, and C. R. Farrar. 2001. “Vibration-based damage detection using statistical process control.” Mech. Syst. Sig. Process. 15 (4): 707–721. https://doi.org/10.1006/mssp.2000.1323.
Gozdecki, C., and J. Smardzewski. 2005. “Detection of failures of adhesively bonded joints using the acoustic emission method.” Holzforschung 379 (9): 115–229. https://doi.org/10.1515/HF.2005.035.
He, K., and W. D. Zhu. 2011. “Detection of damage in space frame structures with L-shaped beams and bolted joints using changes in natural frequencies.” In Vol. 6 of Sensors, instrumentation and special topics. New York: Springer.
He, W. Y., and S. Zhu. 2015. “Moving load-induced response of damaged beam and its application in damage localization.” J. Sound Vib. 22 (16): 3601. https://doi.org/10.1177/1077546314564587.
Hu, C., M. Xiao, H. Zhou, W. Wei, and Y. Hong. 2011. “Damage detection of wood beams using the differences in local modal flexibility.” J. Wood Sci. 57 (6): 479–483. https://doi.org/10.1007/s10086-011-1200-3.
Jiang, Z. H., and Z. H. Pang. 2001. Wood properties of the global important tree species, 30–300. [In Chinese.] Beijing: Science Press.
Jin, C., S. Jang, and X. Sun. 2017. “An integrated real-time structural damage detection method based on extended Kalman filter and dynamic statistical process control.” Adv. Struct. Eng. 20 (4): 549–563. https://doi.org/10.1177/1369433216658484.
King, W. S., J. Y. R. Yen, and Y. N. A. Yen. 1996. “Joint characteristics of traditional Chinese wooden frames.” Eng. Struct. 18 (8): 635–644. https://doi.org/10.1016/0141-0296(96)00203-9.
Korenius, T., J. Laurikkala, and M. Juhola. 2007. “On principal component analysis, cosine and Euclidean measures in information retrieval.” Inf. Sci. 177 (22): 4893–4905. https://doi.org/10.1016/j.ins.2007.05.027.
Kullaa, J. 2010. “Sensor validation using minimum mean square error estimation.” Mech. Syst. Sig. Process. 24 (5): 1444–1457. https://doi.org/10.1016/j.ymssp.2009.12.001.
Kullaa, J. 2011. “Distinguishing between sensor fault, structural damage, and environmental or operational effects in structural health monitoring.” Mech. Syst. Sig. Process. 25 (8): 2976–2989. https://doi.org/10.1016/j.ymssp.2011.05.017.
Kullaa, J. 2013. “Detection, identification, and quantification of sensor fault in a sensor network.” Mech. Syst. Sig. Process. 40 (1): 208–221. https://doi.org/10.1016/j.ymssp.2013.05.007.
Liang, S. C. 1983. The annotation of Ying-tsao fa-shih, 89–90. [In Chinese.] Beijing: China Architecture and Building Press.
Ma, S. L., L. Q. Weng, and S. F. Jiang. 2013. “Distinguishing between sensor deterioration and structural damage.” [In Chinese] Chin. J. Southwest Jiaotong Univ. 48 (6): 1024–1030.
Montgomery, D. C. 2009. “Introduction to statistical quality control (second edition).” Technometrics 49 (1): 108–109. https://doi.org/10.1002/qre.4680070316.
Mujica, L. E., J. Rodellar, A. Fernandez, and A. Guemes. 2011. “Q-statistic and t2-statistic PCA-based measures for damage assessment in structures.” Struct. Health Monit. 10 (5): 539–553. https://doi.org/10.1177/1475921710388972.
Noh, H., R. Rajagopal, and A. S. Kiremidjian. 2013. “Sequential structural damage diagnosis algorithm using a change point detection method.” J. Sound Vib. 332 (24): 6419–6433. https://doi.org/10.1016/j.jsv.2013.07.005.
Rao, P. S., and C. Ratnam. 2012. “Health monitoring of welded structures using statistical process control.” Mech. Syst. Sig. Process. 27 (1): 683–695. https://doi.org/10.1016/j.ymssp.2011.09.023.
Samali, B., J. Li, F. C. Choi, and K. Crews. 2010. “Application of the damage index method for plate-like structures to timber bridges.” Struct. Control Health Monit. 17 (8): 849–871. https://doi.org/10.1002/stc.347.
Schubert, S., D. Gsell, R. Steiger, and G. Feltrin. 2010. “Influence of asphalt pavement on damping ratio and resonance frequencies of timber bridges.” Eng. Struct. 32 (10): 3122–3129. https://doi.org/10.1016/j.engstruct.2010.05.031.
Sklarczyk, C., F. Porsch, B. Wolter, C. Boller, and J. H. Kurz. 2013. “Nondestructive characterization of and defect detection in timber and wood.” Adv. Mater. Res. 778: 295–302. https://doi.org/10.4028/www.scientific.net/AMR.778.295.
Sohn, H., J. A. Czarnecki, and C. R. Farrar. 2000. “Structural health monitoring using statistical process control.” J. Struct. Eng. 126 (11): 1356–1363. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:11(1356).
Tibaduiza, D. A., L. E. Mujica, and J. Rodellar. 2014. “Damage classification in structural health monitoring using principal component analysis and self-organizing maps.” Struct. Control Health Monit. 20 (10): 1303–1316. https://doi.org/10.1002/stc.1540.
Wang, X., and W. Qu. 2009. “Long-term cumulative damage model of historical timber member under varying hygrothermal environment.” Wuhan Univ. J. Nat. Sci. 14 (5): 430–436. https://doi.org/10.1007/s11859-009-0512-2.
Zapico-Valle, J. L., M. García-Diéguez, M. P. González-Martínez, and K. Worden. 2011. “Experimental validation of a new statistical process control feature for damage detection.” Mech. Syst. Sig. Process. 25 (7): 2513–2525. https://doi.org/10.1016/j.ymssp.2011.02.007.
Zhang, F. L., H. B. Xiong, W. X. Shi, and X. Ou. 2016. “Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach.” Struct. Control Health Monit. 23 (11): 1366–1384. https://doi.org/10.1002/stc.1840.
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©2018 American Society of Civil Engineers.
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Received: Aug 2, 2017
Accepted: Mar 14, 2018
Published online: Jun 20, 2018
Published in print: Sep 1, 2018
Discussion open until: Nov 20, 2018
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