基于监测数据的岸桥模态参数识别

PDF(1857 KB)

振动与冲击 ›› 2019, Vol. 38 ›› Issue (20) : 216-221.

论文

基于监测数据的岸桥模态参数识别

秦仙蓉，余传强，孙远韬，宗瑞，张氢

作者信息 +

Modal parameter identification of a quayside container crane based on monitoring data

QIN Xianrong, YU Chuanqiang, SUN Yuantao, ZONG Rui, ZHANG Qing

Author information +

文章历史 +

摘要

针对岸桥的模态参数识别问题，基于监测数据，采用协方差驱动的随机子空间方法对监测岸桥的模态参数进行了识别。归纳了随机子空间法的理论及算法过程，基于协方差驱动随机子空间法结合稳定图对不同工作状态下的岸桥进行参数识别，识别出了监测岸桥在不同工作状态下1Hz以内的五阶模态。识别得到的岸桥的阻尼比在3%以内，小车（吊重）质量对不同的工作状态下岸桥的非工作平面内模态影响较小，对起升平面，即工作平面内的模态有一定的影响。

Abstract

Aiming at modal parameter identification of a quayside container crane (QCC), based on monitoring data, the modal parameters of the QCC were identified by a covariance-driven stochastic subspace identification method (CSSI) in this paper.The main theory of this method and its algorithm were summarized, then, the parameters of the QCC were identified by the CSSI method with the stabilization diagram.The results reveal that this method can effectively identify the five modes of QCC within 1 Hz, the identified damping ratios are less than 3%, and the trolley (loading) has negligible effects on the modal results of the monitored QCC under different working states in an unworking plane, but has certain effects on the modal results in the working plane, i.e.lifting plane.

导出引用

秦仙蓉，余传强，孙远韬，宗瑞，张氢 . 基于监测数据的岸桥模态参数识别[J]. 振动与冲击, 2019, 38(20): 216-221

QIN Xianrong, YU Chuanqiang, SUN Yuantao, ZONG Rui, ZHANG Qing. Modal parameter identification of a quayside container crane based on monitoring data[J]. Journal of Vibration and Shock, 2019, 38(20): 216-221

参考文献

[1] 刘宇飞, 辛克贵, 樊健生, 等. 环境激励下结构模态参数识别方法综述[J]. 工程力学, 2014, 31(4): 46-53.
Liu Yufei, Xin Kegui, Fan Jiansheng, etal. A review of structure modal identification methods through ambient excition[J]. Engineering Mechanics, 2014, 31(4): 46-53.
[2] 辛峻峰, 王树青, 刘福顺. 数据驱动与协方差驱动随机子空间法差异化分析[J]. 振动与冲击, 2013, 32(9):1-4.
Xin Junfeng, Wang Shuqing, Liu Fushun. Performance comparison for data-driven and covariance-driven stochastic subspace identification method[J]. Journal of Vibration and Shock, 2013, 32(9): 1-4.
[3] Lew J.S, Juang J.N, Longman R.W. Comparison of several system identification methods for flexible structures[J]. Journal of Sound and Vibration, 1993, 167(3): 461-480.
[4] 常军,张启伟,孙利民. 稳定图方法在随机子空间识别模态参数中的应用[J]. 工程力学, 2007, 24(2) :39-44.
Chang Jun, Zhang Qiwei, Sun Limin. Application of stabilization diagram for modal parameter identification using stochastic subspace method [J]. Engineering Mechanics, 2007, 24(2) :39-44.
[5] 常军,张启伟,孙利民.随机子空间方法在桥塔模态参数识别中的应用[J]. 地震工程与工程振动, 2006, 26(5):183-197.
Chang Jun, Sun Qiwei, Sun Limin. Application of stochastic subspace identification in modal parameter identification of bridge tower [J]. Earthquake Engineering and Engineering Vibration, 2006, 26(5):183-197.
[6] 徐良,江见鲸,过静珺. 随机子空间识别在悬索桥试验模态分析中的应用[J]. 工程力学, 2002, 19(4): 46-49.
Xu Liang, Jiang Jianjing, Guo Jingjun. Application of stochastic subspace method to experimental modal analysis of suspension bridge[J].Engineering Mechanics,2002,19(4):46-49.
[7] 秦世强,蒲黔辉,施洲. 环境激励下大型桥梁模态参数识别的一种方法[J]. 振动与冲击, 2012, 31(02): 95-100.
Qin Shiqiang, Pu Qianhui, Shi Zhou. A method of modal parameters identification using ambient vibration measurements for a large-scale bridge [J]. Journal of Vibration and Shock, 2012, 31(02): 95-100.
[8] 臧延朋, 王凤仁, 温广瑞, 等. 运行工况下转子系统模态参数识别技术研究[J]. 振动与冲击, 2018, 37(5): 120-125.
Zang Tingpeng, Wang Fengren, Wen Guangrui, et al. Identification technique for modal parameters of rotor systems under operation condition [J]. Journal of Vibration and Shock, 2018, 37(5): 120-125.
[9] 谢伟平, 曹晓宇, 肖伯强, 等. 基于模态测试的宽幅钢箱梁桥有限元模型建立、修正与分析[J]. 振动与冲击, 2018, 37(1): 98-105.
Xie Weiping, Cao Xiaoyu, Xiao Boqiang, et al. Finite element modelling, modification and analysis for wide steel box-girder bridges, based on modal tests [J]. Journal of Vibration and Shock, 2018, 37(1): 98-105.
[10] 杨风利, 张宏杰, 杨靖波, 等. 脉动风激励下格构式输电塔动力特征识别[J]. 振动与冲击, 2017, 36(21): 144-149.
Yang Fengli, Zhang Hongjie, Yang Jingbo, et al. Identification of the dynamic properties of a transmission line lattice tower under ambient excitations [J]. Journal of Vibration and Shock, 2017, 36(21): 144-149.
[11] Dazhi Liu, Shuhong Xiang, Shichao Fan, etal. Stochastic Subspace Method for Experimental Modal Analysis[J]. Matec Web of Conferences,2016,77(1): 1-6.
[12] Dai K, Wang Y, Huang Y, etal. A modified stochastic subspace identification method for estimating natural frequencies[J]. ASME International Mechanical Engineering Congress and Exposition, 2016, 13(1): 1-8.
[13] Peeters B, De Roeck G. Reference-based stochastic subspace identification for output-only modal analysis[J]. Mechanical systems and signal processing, 1999, 13(6): 855-878.