一种拱坝泄流振动响应降噪与特征提取方法
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摘要
基于高拱坝在泄流激励下的实测振动响应,提出了一种基于经验模态分解和固有模态函数小波降噪的信号处理和模态特征提取方法。首先,利用经验模式分解将含有噪声的高拱坝泄洪振动响应信号分解成一系列的固有模态函数;然后,基于对每个固有模态函数的特性分析选取相应的小波基对固有模态函数进行降噪;最后,利用Hilbert-Huang变换识别降噪后的各阶拱坝模态特征参数。通过拱坝室内模型试验验证了该方法识别模态参数的可靠性,并应用于某原型拱坝的实测振动响应降噪和模态特征提取中。该方法可避免传统原始信号先降噪带来的部分高阶模态信息丢失问题,有效降低了噪声对固有模态函数的影响,提高了高拱坝实时模态参数识别的阶次和精度。
A signal processing and mode feature extraction method for arch dam flood discharge vibration response based on empirical mode decomposition and wavelet de-noising of intrinsic mode functions was presented in this paper.Firstly,the signal with noise of the arch dam flood discharge was decomposed into a series of intrinsic mode function.Secondly,wavelet de-noising technology was used to reduce noise on the intrinsic mode function.Finally,the modal parameter was identified by Hilbert-Huang Transform.The reliability of this method was verified on the hydro-elastic arch dam experiment and was applied to the modal parameter identification and noise reduction of a prototype arch dam.This method avoids the problem of higher mode information lost because of the original signal noise reduction,reduces the impact of noise on the intrinsic mode functions effectively,and improves the order and accuracy of real-time modal parameter identification of high arch dam.
A signal processing and mode feature extraction method for arch dam flood discharge vibration response based on empirical mode decomposition and wavelet de-noising of intrinsic mode functions was presented in this paper.Firstly,the signal with noise of the arch dam flood discharge was decomposed into a series of intrinsic mode function.Secondly,wavelet de-noising technology was used to reduce noise on the intrinsic mode function.Finally,the modal parameter was identified by Hilbert-Huang Transform.The reliability of this method was verified on the hydro-elastic arch dam experiment and was applied to the modal parameter identification and noise reduction of a prototype arch dam.This method avoids the problem of higher mode information lost because of the original signal noise reduction,reduces the impact of noise on the intrinsic mode functions effectively,and improves the order and accuracy of real-time modal parameter identification of high arch dam.
引文
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[12]练继建.二滩拱坝及地下厂房结构振动测试与反馈分析[R].天津:天津大学,2009.
[2]LIAN Jijian,LI Huokun,ZHANG Jianwei.ERA Modal Identification Method forHydraulic Structures Based on Order Determination and Noise Reduction of Sin-gular Entropy[J].Sci China Ser E-Tech Sci,2009,52(2):400-412.
[3]李火坤,练继建,杨敏,等.强震后基于泄流激励的映秀湾水电站拦河闸动态检测与损伤评估研究[J].振动与冲击,2010,29(9):64-68.
[4]李火坤,练继建.高拱坝泄流激励下基于频域法的工作模态参数识别[J].振动与冲击,2008,27(7):149-153.
[5]练继建,张建伟,李火坤,等.泄洪激励下高拱坝模态参数识别研究[J].振动与冲击,2007,26(12):101-105.
[6]李火坤,练继建.三峡左导墙泄洪振动原型观测及其动态识别与安全评估[J].水利水运工程学报,2010(9):59-64.
[7]Yang J N,Lei Y.System Identification of Linear Structures Using Hilbert Trans-form and Empirical Mode Decomposition[C]∥Proc of 18th IMAC.A Confer-ence on Structural Dynamics.San Antonio:Society for Experimental Mechan-ics,2000:213-219.
[8]陈隽,徐幼麟.HHT方法在结构模态参数识别中的应用[J].振动工程学报,2003,16(3):383-388.
[9]Norden E Huang,Zheng Shen,Steven R Long.The Empirical Mode Decomposi-tion and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series A-nalysis[C]∥Proc Roy S Lond A454.London:The Royal Society,1998:903-995.
[10]翟伟廉,刘少兵,王锦文.弧形闸门流激振动脉动压力HHT分析[J].武汉理工大学学报,2006,28(9):68-71.
[11]马斌.高拱坝及反拱水垫塘结构泄洪安全分析与模拟[D].天津:天津大学,2006.
[12]练继建.二滩拱坝及地下厂房结构振动测试与反馈分析[R].天津:天津大学,2009.
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