中山大学航空航天学院,广东 广州 510006
杨达豪(1995年生),男;研究方向:参数识别;E-mail: yangdh5@mail2.sysu.edu.cn
汪利(1988年生),男;研究方向:计算力学;E-mail: wangli75@mail.sysu.edu.cn
纸质出版日期:2021-11-25,
网络出版日期:2020-11-11,
收稿日期:2020-06-08,
录用日期:2020-07-08
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杨达豪,吕中荣,汪利.基于快速稀疏正则化的旋转梁损伤识别[J].中山大学学报(自然科学版),2021,60(06):142-149.
YANG Dahao,LÜ Zhongrong,WANG Li.Damage detection of rotating beam with fast sparse regularization[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2021,60(06):142-149.
杨达豪,吕中荣,汪利.基于快速稀疏正则化的旋转梁损伤识别[J].中山大学学报(自然科学版),2021,60(06):142-149. DOI: 10.13471/j.cnki.acta.snus.2020.06.08.2020B062.
YANG Dahao,LÜ Zhongrong,WANG Li.Damage detection of rotating beam with fast sparse regularization[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2021,60(06):142-149. DOI: 10.13471/j.cnki.acta.snus.2020.06.08.2020B062.
将旋转叶片简化为旋转梁,文章提出了一种基于快速稀疏正则化的旋转梁损伤识别方法。该方法将结构损伤识别简化成非线性最小二乘问题,即寻找损伤参数,使得模态残差最小。损伤识别是典型的反问题,通常具有非适定性,即识别结果对测量误差十分敏感。为克服非适定性并快速求解损伤识别反问题,提出了一种快速稀疏正则化方法。该方法将稀疏正则化简化成一个摩擦模型,模型中的静摩擦力即为正则化参数。数值算例表明,该方法不仅能准确识别出旋转梁的损伤程度和位置,还可以快速地确定正则化参数,从而有效地减少迭代次数,提高计算效率。
In this paper, the rotor blade is simplified to rotating beam for which the proposed fast sparse regularization approach is applied to realize the damage detection. The damage detection can be formulated as a nonlinear least squares problem that finds the damage parameters to minimize the residuals between the calculated modal data and the measured modal data. Damage detection is a typical inverse problem which is usually ill-pose, i.e., the identification is sensitive to the noise. To overcome such ill-posedness and quickly deal with the inverse problem, the fast sparse regularization approach is proposed, which transforms the sparse regularization into a frictional-model,whose regularization parameter is the static friction force. Numerical example demonstrates the accuracy and efficiency of the proposed approach for it enable to select the suitable regularization parameter quickly.
旋转梁损伤识别灵敏度分析稀疏正则化正则化参数
rotating beamdamage detectionsensitivity analysissparse regularizationregularization parameter
LI L, LI Y H, LIU Q K, et al. A mathematical model for horizontal axis wind turbine blades[J]. Applied Mathematical Modelling, 2014, 38(11/12): 2695-2715.
ROY N, GANGULI R. Helicopter rotor blade frequency evolution with damage growth and signal processing[J]. Journal of Sound and Vibration, 2005, 283(3): 821-851.
YOO H H, RYAN R R, SCOTT R A. Dynamics of flexible beams undergoing overall motions[J]. Journal of Sound and Vibration, 1995, 181(2): 261-278.
VALVERDE J, GARCÍA-VALLEJO D. Stability analysis of a substructured model of the rotating beam[J]. Nonlinear Dynamics, 2009, 55(4): 355-372.
蹇开林, 殷学纲. 旋转梁的固有频率计算[J]. 重庆大学学报, 2001, 24(6):36-39.
CHUNG J, YOO H H. Dynamic analysis of a rotating cantilever beam by using the finite element method[J]. Journal of Sound and Vibration, 2002,249(1): 147-164.
TIKHONOV A N. On the solution of ill-posed problems and the method of regularization[J]. Dokl Akad Nauk SSSR, 1963, 151: 501-504.
ZHANG C D, XU Y L. Comparative studies on damage identification with Tikhonov regularization and sparse regularization: damage detection with Tikhonov regularization and sparse regularization[J]. Structural Control and Health Monitoring, 2016, 23(3): 560-579.
ZHOU X Q, XIA Y, L1 W S.Regularization approach to structural damage detection using frequency data[J]. Structural Health Monitoring, 2015, 14(6): 571-582.
SCHMIDT M. Least squares optimization with L1-norm regularization[R]. CS542B Project Report, 2005, 504: 195-221.
WANG L, ZHOU J, LU Z R. A fast friction-model-inspired sparse regularization approach for damage identification with modal data[J]. Computers & Structures,2020, 227: 106-142.
KIM H, HEE Y H, CHUNG J. Dynamic model for free vibration and response analysis of rotating beams[J]. Journal of Sound and Vibration, 2013, 332(22): 5917-5928.
YANG D H ,LU Z R , WANG L. Detection of structural damage in rotating beams using modal sensitivity analysis and sparse regularization[J/OL]. International Journal of Structural Stability and Dynamics.https://doi.org/10.1142/S0219455420500868https://doi.org/10.1142/S0219455420500868.
ITO K, KUNISCH K. Lagrange multiplier approach to variational problems and applications[M]. SIAM Philadelphia, 2008.
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