一种基于识别概率直方图的随机减量改进技术
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摘要
在采用随机减量技术进行工作模态分析过程中,触发条件和参考通道通常需要人为指定。受实际环境和测量误差等的影响,单一触发条件和特定参考通道导致模态辨识结果具有一定的偶然性。结合基于数据挖掘的识别概率直方图方法,对传统随机减量技术进行了改进。在遍历参考通道和多次触发取值的情况下获得多个结构模态辨识结果,并根据频率容差和模态置信度容差准则进行一致性聚类,继而绘制相应的识别概率直方图,最终选取识别概率大的聚类结果作为结构模态结果。通过结构算例和模型实验,显示了基于识别概率直方图的随机减量改进技术的有效性和抗噪性。
During the operational modal identification of structures with the Random Decrement Technique,the trigger condition and reference channel are chosen artificially.Subjected to the operational environment and the measurement errors,the identification results will exhibit uncertainties for the case of single trigger condition and specific reference channel.To avoid these problems,an identification-probability histogram(IpHist)method by using the data mining technique is proposed to improve the traditional RDT method.Firstly,a series of modal data is identified with different trigger conditions and reference channels.Then,all the alternative modes are clustered into several categories by using the criteria of frequency tolerance and MAC tolerance,and the identification probability of each category is obtained from the corresponding identification-probability histogram.Finally,the clustered modes with large identification probability are chosen to be the structural modes.By taking a3 DOF numerical model and an actual truss model,the modal identification results by RDT based on IpHist are shown and compared with considerating the measurement noise.
During the operational modal identification of structures with the Random Decrement Technique,the trigger condition and reference channel are chosen artificially.Subjected to the operational environment and the measurement errors,the identification results will exhibit uncertainties for the case of single trigger condition and specific reference channel.To avoid these problems,an identification-probability histogram(IpHist)method by using the data mining technique is proposed to improve the traditional RDT method.Firstly,a series of modal data is identified with different trigger conditions and reference channels.Then,all the alternative modes are clustered into several categories by using the criteria of frequency tolerance and MAC tolerance,and the identification probability of each category is obtained from the corresponding identification-probability histogram.Finally,the clustered modes with large identification probability are chosen to be the structural modes.By taking a3 DOF numerical model and an actual truss model,the modal identification results by RDT based on IpHist are shown and compared with considerating the measurement noise.
引文
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[2]Reynders E.System identification methods for(operational)modal analysis:review and comparison[J].Archives of Computational Methods in Engineering,2012,19(1):51-124.
[3]Cole H A.Method and apparatus for measuring the damping characteristics of a structure[P].US Patent No 3600069,1971.
[4]Cole H A.On-line failure detection and damping measurement of aerospace structure by random decrement signature[R].NASA CR-2205,1972.
[5]Morsy R,Marzouk H,Gu X,et al.Use of the random decrement technique for nondestructive detection of damage to beams[J].Materials&Structures,2016,49(11):4719-4727.
[6]黄铭枫,吴承卉,徐卿,等.基于实测数据的某高层建筑结构动力参数和气动阻尼识别[J].振动与冲击,2017,36(10):31-37.HUANG Mingfeng,WU Chenghui,XU Qing,et al.Structural dynamic and aerodynamic parameters identification for a tall building with full-scale measurements[J].Journal of Vibration and Shock,2017,36(10):31-37.
[7]Ibrahim S R,Mikulcik E C.A time domain modal vibration test technique[J].Shock and Vibration Bulletin,1973,43(4):21-37.
[8]Ibrahim S R,Mikulcil E C.The experimental determination of vibration parameters fro time response[J].Shock and Vibration Bulletin,1976,46(5):187-196.
[9]Wang S,Liu F.New accuracy indicator to quantify the true and false modes for eigensystem realization algorithm[J].Structural Engineering and Mechanics,2010,34(5):625-634.
[10]陈太聪,李盈盈,苏成,等.环境激励下结构模态辨识的识别概率直方图方法研究[J].振动工程学报,2016,29(4):561-567.CHEN Taicong,LI Yingying,SU Cheng,et al.Astudy on identification-probability histogram method for modal identification of structures subjected to ambient excitations[J].Journal of Vibration Engineering,2016,29(4):561-567.
[11]Ku C J.Random decrement based method for parameter identification of wind-excited building models using acceleration responses[D].Fort Collins:Colorado State University,2004
[12]李德葆,陆秋海.实验模态分析及其应用[M].北京:科学出版社,2001.LI Debao,LU Qiuhai.Concepts and Applications Of Experimental Modal Analysis[M].Beijing:Science Press,2001.
[13]Asmussen J C,Ibrahim S R,Brincker R.Application of vector triggering random decrement[C].Proceedings of the International Modal Analysis ConferenceIMAC,1997:1165-1171.
[14]刘彬,丁桦,时忠明.随机减量函数触发条件分析[J].振动与冲击,2007,26(7):27-31.LIU Bin,DING Hua,SHI Zhongming.Triggering condition analysis to random decrement technology[J].Journal of Vibration and Shock,2007,26(7):27-31.
[15]Ibrahim S R.Random decrement technique for modal identification of structures[J].Journal of Spacecraft&Rockets,2012,14(11):696.
[16]Asmussen J C.Modal analysis based on the random decrement technique-application to civil engineering structures[J].Journal of Dairy Science,1997,97(9):5497-5507.
[17]Wu W H,Chen C C,Liau J A.A multiple random decrement method for modal parameter identification of stay cables based on ambient vibration signals[J].Advances in Structural Engineering,2012,15(6):969-982.
[18]Lin C S,Tseng T C.Response-only modal identification using random decrement algorithm with time-varying threshold level[J].Journal of Mechanical Science and Technology,2014,28(6):2099-2109.
[19]Ding C,He X.K-nearest-neighbor consistency in data clustering:incorporating local information into global optimization[C].Proceedings of the 2004ACM Symposium on Applied Computing,ACM,2004:584-589.