Full Text:   <2860>

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CLC number: TU192

On-line Access: 2015-02-03

Received: 2014-06-05

Revision Accepted: 2014-10-13

Crosschecked: 2015-01-12

Cited: 0

Clicked: 5954

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Xing-huai Huang

http://orcid.org/0000-0001-9989-577X

Zhao-dong Xu

http://orcid.org/0000-0003-0544-8253

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Journal of Zhejiang University SCIENCE A 2015 Vol.16 No.2 P.105-116

http://doi.org/10.1631/jzus.A1400163


An in-time damage identification approach based on the Kalman filter and energy equilibrium theory


Author(s):  Xing-huai Huang, Shirley Dyke, Zhao-dong Xu

Affiliation(s):  Key Laboratory of C&PC Structures of the Ministry of Education, Southeast University, Nanjing 210096, China; more

Corresponding email(s):   xuzhdgyq@seu.edu.cn

Key Words:  In-time model updating, Kalman filter, Energy equilibrium theory, Damage identification, Anti-noise capacity, Structure health monitoring


Xing-huai Huang, Shirley Dyke, Zhao-dong Xu. An in-time damage identification approach based on the Kalman filter and energy equilibrium theory[J]. Journal of Zhejiang University Science A, 2015, 16(2): 105-116.

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author="Xing-huai Huang, Shirley Dyke, Zhao-dong Xu",
journal="Journal of Zhejiang University Science A",
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pages="105-116",
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doi="10.1631/jzus.A1400163"
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%T An in-time damage identification approach based on the Kalman filter and energy equilibrium theory
%A Xing-huai Huang
%A Shirley Dyke
%A Zhao-dong Xu
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%I Zhejiang University Press & Springer
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T1 - An in-time damage identification approach based on the Kalman filter and energy equilibrium theory
A1 - Xing-huai Huang
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DOI - 10.1631/jzus.A1400163


Abstract: 
In research on damage identification, conventional methods usually face difficulties in converging globally and rapidly. Therefore, a fast in-time damage identification approach based on the kalman filter and energy equilibrium theory is proposed to obtain the structural stiffness, find the locations of damage, and quantify its intensity. The proposed approach establishes a relationship between the structural stiffness and acceleration response by means of energy equilibrium theory. After importing the structural energy into the kalman filter algorithm, unknown parameters of the structure can be obtained by comparing the predicted energy and the measured energy in each time step. Numerical verification on a highway sign support truss with and without damage indicates that the updated Young’s modulus can converge to the true value rapidly, even under the effects of external noise excitation. In addition, the calculation time taken for each step of the approach is considerably shorter than the sampling period (1/256 s), which means that, this approach can be implemented in-time and on-line.

一种基于Kalman滤波和能量原理的实时损伤识别方法

目的:建立一种损伤识别方法,能够实时地监测多自由度复杂结构中构件的损伤情况。
方法:1. 用能量原理对结构刚度进行解构,建立结构单元刚度和节点响应之间的关系;2. 用Kalman滤波原理分析结构刚度的预测值和测量值,迅速对结构的刚度进行识别(图6-9);3. 对每一步计算进行耗时监测,确保算法的实时性(图10)。
结论:1. 该方法能够较准确地得到结构的刚度信息,同时得出损伤单元的损伤位置和损伤量;并且收敛速度快,计算量小,具有很强的实时性和抗噪能力;2. 对于本文的桁架结构,所有杆件刚度均能在0.4 s内收敛,平均每一荷载步计算时间约为0.0012 s,小于采样周期1/256 s,说明该方法可以迅速、准确地对结构进行实时的监测。

关键词:实时模型修正;能量平衡原理;Kalman滤波原理;损伤识别;健康监测

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Chatzi, E.N., Smyth, A.W., 2009. The unscented Kalman filter and particle filter methods for nonlinear structural system identification with non-collocated heterogeneous sensing. Structural Control & Health Monitoring, 16(1):99-123.

[2]Erdogan, Y.S., Bakir, P.G., 2013. Evaluation of the different genetic algorithm parameters and operators for the finite element model updating problem. Computers and Concrete, 11(6):541-569.

[3]Feng, X.L., He, G.L., Abdurishit, 2008. Estimation of parameters of the Makeham distribution using the least squares method. Mathematics and Computers in Simulation, 77(1):34-44.

[4]Garcia-Perez, A., Amezquita-Sanchez, J.P., Dominguez-Gonzalez, A., et al., 2013. Fused empirical mode decomposition and wavelets for locating combined damage in a truss-type structure through vibration analysis. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 14(9):615-630.

[5]Ghanem, R., Shinozuka, M., 1995. Structural-system identification. I: Theory. Journal of Engineering Mechanics, 121(2):255-264.

[6]Groeneboom, P., Jongbloed, G., Wellner, J.A., 2001. Estimation of a convex function: characterizations and asymptotic theory. Annals of Statistics, 29(6):1653-1698.

[7]Hoshiya, M., Saito, E., 1984. Structural identification by extended Kalman filter. Journal of Engineering Mechanics, 110(12):1757-1770.

[8]Iwasaki, A., Todoroki, A., Shimamura, Y., et al., 2004. Unsupervised structural damage diagnosis based on change of response surface using statistical tool. JSME International Journal Series A, 47(1):1-7.

[9]Kalman, R.E., 1960. A new approach to linear filtering and prediction problems. Journal of Fluids Engineering, 82(1):35-45.

[10]Khoo, L.M., Mantena, P.R., Jadhav, P., 2004. Structural damage assessment using vibration modal analysis. Structural Health Monitoring, 3(2):177-194.

[11]Kim, J.T., Ryu, Y.S., Cho, H.M., et al., 2003. Damage identification in beam-type structures: frequency-based method vs mode-shape-based method. Engineering Structures, 25(1):57-67.

[12]Krishnan, S.S., Sun, Z.X., Irfanoglu, A., et al., 2011. Evaluating the performance of distributed approaches for modal identification. Proceeding of SPIE 7981, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, USA, p.79814M-79814M.

[13]Lee, Y.S., Chung, M.J., 2000. A study on crack detection using eigenfrequency test data. Computers & Structures, 77(3):327-342.

[14]Lei, Y., Wang, H.F., Shen, W.A., 2012. Update the finite element model of canton tower based on direct matrix updating with incomplete modal data. Smart Structures and Systems, 10(4-5):471-483.

[15]Li, T.Y., Zhang, T., Liu, J.X., et al., 2004. Vibrational wave analysis of infinite damaged beams using structure-borne power flow. Applied Acoustics, 65(1):91-100.

[16]Liu, Y., Duan, Z.D., 2012. Fuzzy finite element model updating of bridges by considering the uncertainty of the measured modal parameters. Science China Technological Sciences, 55(11):3109-3117.

[17]Liu, Y., Sun, H., Wang, D.J., 2013. Updating the finite element model of large-scaled structures using component mode synthesis technique. Intelligent Automation and Soft Computing, 19(1):11-21.

[18]López-Díez, J., Torrealba, M., Güemes, A., et al., 2005. Application of statistical energy analysis for damage detection in spacecraft structures. Key Engineering Materials, 293-294:525-532.

[19]Nadauld, J.D., Pantelides, C.P., 2007. Rehabilitation of cracked aluminum connections with GFRP composites for fatigue stresses. Journal of Composites for Construction, 11(3):328-335.

[20]Park, J.S., Stallings, J.M., 2006. Fatigue evaluations of variable message sign structures based on AASHTO specifications. KSCE Journal of Civil Engineering, 10(3):207-217.

[21]Park, N.G., Park, Y.S., 2005. Identification of damage on a substructure with measured frequency response functions. Journal of Mechanical Science and Technology, 19(10):1891-1901.

[22]Sadr, M.H., Astaraki, S., Salehi, S., 2007. Improving the neural network method for finite element model updating using homogenous distribution of design points. Archive of Applied Mechanics, 77(11):795-807.

[23]Shinozuka, M., Ghanem, R., 1995. Structural system-identification. II: experimental-verification. Journal of Engineering Mechanics, 121(2):265-273.

[24]Sinha, J.K., Friswell, M.I., 2003. The use of model updating for reliable finite element modelling and fault diagnosis of structural components used in nuclear plants. Nuclear Engineering and Design, 223(1):11-23.

[25]Song, W., Dyke, S., 2014. Real-time dynamic model updating of a hysteretic structural system. Journal of Structural Engineering, 140(3):04013082.

[26]van der Merwe, R., Wan, E., Julier, S.J., 2004. Sigma-point Kalman filters for nonlinear estimation and sensor fusion: applications to integrated navigation. Proceedings of the AIAA Guidance Navigation & Control Conference, Providence, Rhode Island, USA, p.1735-1764.

[27]Xu, Z.D., Wu, Z.S., 2007. Energy damage detection strategy based on acceleration responses for long-span bridge structures. Engineering Structures, 29(4):609-617.

[28]Xu, Z.D., Liu, M., Wu, Z.S., et al., 2011. Energy damage detection strategy based on strain responses for long-span bridge structures. Journal of Bridge Engineering, 16(5):644-652.

[29]Yan, A.M., Golinval, J.C., 2005. Structural damage localization by combining flexibility and stiffness methods. Engineering Structures, 27(12):1752-1761.

[30]Yan, G.R., Dyke, S.J., Irfanoglu, A., 2012. Experimental validation of a damage detection approach on a full-scale highway sign support truss. Mechanical Systems and Signal Processing, 28:195-211.

[31]Yang, J.N., Lin, S.L., Huang, H.W., et al., 2006. An adaptive extended Kalman filter for structural damage identification. Structural Control & Health Monitoring, 13(4):849-867.

[32]Zhao, X., Sun, H.H., Zheng, Y.M., 2009. Identification and updating for the three-dimensional finite element model of a long span steel skybridge. Structural Design of Tall and Special Buildings, 18(6):625-646.

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