Parameter identification of linear time-varying systems based on chirplet transform under environmental excitation
-
摘要: 提出了针对时变系统响应的短时频率线性时变假设,通过将时变响应拟合成多分量线调频信号,根据线调频信号互相关理论推导了随机白噪声激励下时变系统的物理参数识别方法。该识别方法只需基于结构的加速度响应,便能识别结构的时变质量和刚度。由于引入了调频斜率刻画响应信号的短时频率线变特征,该方法相比传统识别方法能更好地追踪快变甚至突变参数,对实际工程中的时变问题具有重要的应用价值。仿真算例中构造了1个3自由度时变结构模型,针对线性时变、周期时变和突变等情况进行了物理参数的识别,误差分析显示识别误差均在5%以内,仿真结果验证了方法的正确性和适用性。Abstract: The assumption that frequencies of responses of linear time-varying systems vary linearly in a short-time was proposed. By fitting the time-varying responses to multi-component line frequency modulation signals, a physical parameter identification method of time-varying systems under random white noise excitation was obtained according to the cross-correlation theory of line frequency modulation signals. The mass and stiffness coefficients of time-varying structures were identified only using the acceleration response. Due to the introduction of frequency modulation factor to describe the variation of frequencies of response signals in a short-time, this method could track fast changes or even abrupt changes of parameters better than traditional identification method, so it had important application value for time-varying structures in practical engineering. In the simulation example, a 3-degress of freedom time-varying structure model was constructed to identify linear, periodic and abrupt changes of physical parameters. The error analysis showed that the identification errors were all within 5%. The results verified the correctness and applicability of the method.
-
[1] 周传荣,赵淳生.机械振动参数识别及其应用[M].北京:科学出版社,1989. [2] 于开平,庞世伟,赵婕.时变线性/非线性结构参数识别及系统辨识方法研究进展[J].科学通报,2009,54(20):3147-3156. YU Kaiping,PANG Shiwei,ZHAO Jie.Advances in method of time-varying linear/nonlinear structural system identification and parameter estimate[J].Chinese Science Bulletin,2009,54(20):3147-3156.(in Chinese) [3] 程军圣,张亢,杨宇,等.局部均值分解与经验模式分解的对比研究[J].振动与冲击,2009,28(5):13-16. CHENG Junsheng,ZHANG Kang,YANG Yu,et al.Comparison between the methods of local mean decomposition and empirical mode decomposition[J].Journal of Vibration and Shock,2009,28(5):13-16.(in Chinese) [4] 徐晴晴,史治宇.基于改进EMD分解的时变结构密集模态的瞬时参数识别[J].机械科学与技术,2015,34(8):1161-1165. XU Qingqing,SHI Zhiyu.Identifying parameters of time varying structures with spaced modes based on improved EMD method[J].Mechanical Science and Technology for Aerospace Engineering,2015,34(8):1161-1165.(in Chinese) [5] LIU K.Identification of linear time-varying systems[J].Journal of Sound and Vibration,1997,204(4):487-500. [6] 庞世伟,于开平,邹经湘.识别时变结构模态参数的改进子空间方法[J].应用力学学报,2005,22(2):184-188. PANG Shiwei,YU Kaiping,ZOU Jingxiang.Improved subspace method with application in linear time-varying structural modal parameter identification[J].Chinese Journal of Applied Mechanics,2005,22(2):184-188.(in Chinese) [7] TASKER F,BOSSE A,FISHER S.Real-time modal parameter estimation using subspace methods:theory[J].Mechanical Systems and Signal Processing,1998,12(6):797-808. [8] DZIEDZIECH K,STASZEWSKI W J,BASU B,et al.Wavelet-based detection of abrupt changes in natural frequencies of time-variant systems[J].Mechanical Systems and Signal Processing,2015,64-65:347-359. [9] 郑红,周雷,杨浩.基于小波包分析与多核学习的滚动轴承故障诊断[J].航空动力学报,2015,30(12):3035-3042. ZHENG Hong,ZHOU Lei,YANG Hao.Rolling bearing fault diagnosis based on wavelet packet analysis and multi kernel learning[J].Journal of Aerospace Power,2015,30(12):3035-3042.(in Chinese) [10] 许鑫,史治宇,龙双丽.基于小波状态空间法的时变结构瞬时频率识别[J].中国机械工程,2011,22(8):901-904. XU Xin,SHI Zhiyu,LONG Shuangli.Instantaneous frequency identification of a time-varying structure using wavelet-based state space method[J].China Mechanical Engineering,2011,22(8):901-904.(in Chinese) [11] 于开平,邹经湘,杨炳渊.小波函数的性质及其应用研究[J].哈尔滨工业大学学报,2000,32(2):36-39. YU Kaiping,ZOU Jingxiang,YANG Bingyuan.Study on performance and application of the wavelet function[J].Journal of Harbin Institute of Technology,2000,32(2):36-39.(in Chinese) [12] ZHOU S D,MA Y C,LIU L,et al.Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine[J].Mechanical Systems and Signal Processing,2018,98:722-755. [13] 谢旭,李季隆,赵俊亮,等.基于遗传算法的车辆动力参数识别方法[J].浙江大学学报(工学版),2010,44(9):1818-1824. XIE Xu,LI Jilong,ZHAO Junliang,et al.Identification method of vehicle parameters based on genetical gorithms[J].Journal of Zhejiang University (Engineering Science),2010,44(9):1818-1824.(in Chinese) [14] 王宏禹,邱天爽.非平稳确定性信号与非平稳随机信号统一分类法的探讨[J].通信学报,2015,36(2):66-68. WANG Hongyu,QIU Tianshuang.Unified classification methods for determinate nonstationary signals and random nonstationary signals[J].Journal on Communications,2003,36(2):66-68.(in Chinese) [15] DENG Y,CHENG C M,YANG Y,et al.Parametric identification of nonlinear vibration systems via polynomial chirplet transform[J].Journal of Vibration and Acoustics,2016,138(5):051014.1-051014.18. [16] 徐亚军,于德介,刘坚.基于线调频小波路径追踪阶比循环平稳解调的滚动轴承故障诊断[J].航空动力学报,2013,28(11):2600-2608. XU Yajun,YU Dejie,LIU Jian.Fault diagnosis of roller bearings based on chirplet path pursuit and order cyclostationary demodulation[J].Journal of Aerospace Power,2013,28(11):2600-2608.(in Chinese) [17] 陈关宝,于德介,吴雪明.基于多尺度线调频基稀疏信号分解的时变系统模态参数识别[J].机械工程学报,2013,49(13):69-76. CHEN Guanbao,YU Dejie,WU Xueming.Modal parameters identification of time-varying systems based on multi-scale chirplet sparse signal decomposition[J].Journal of Mechanical Engineering,2013,49(13):69-76.(in Chinese) [18] 姚山峰,严航,曾安军,等.线性调频信号的相关检测性能分析[J].计算机工程,2012,38(1):77-80. YAO Shanfeng,YAN Hang,ZENG Anjun,et al.Correlation detection performance analysis for linear frequency modulation signal[J].Computer Engineering,2012,38(1):77-80.(in Chinese) [19] YU G,ZHOU Y.General linear chirplet transform[J].Mechanical Systems and Signal Processing,2015,70-71:958-973. [20] 刘波.MIMO雷达正交波形设计及信号处理研究[D].成都:电子科技大学,2008. LIU Bo.Research on generation of orthogonal waveform and signal processing for mimo radar[D].Chengdu:University of Electronic Science and Technology of China,2008.(in Chinese)
点击查看大图
计量
- 文章访问数: 381
- HTML浏览量: 2
- PDF量: 468
- 被引次数: 0