A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibrat...A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibration amplitude.For this reason,the Operational Modal Analysis(OMA)was carried out in order to identify the pri-mary cause.According to the investigation,one of the harmonic components which was 18 times the motor’s running speed matched with a resonance frequency of 112 Hz.According to OMA study,the motor was vibrating in torsional motion because the compressor’s load had stimulated the entire motor-compressor unit at this reso-nance frequency.The analysis also demonstrates the bulging effect of the motor shaft’s axial vibration on the motor’s endplate.展开更多
A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experime...A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.展开更多
A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic response...A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm （NExT-ERA） is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies.展开更多
For some large-scale engineering structures in operating conditions, modal param- eters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few y...For some large-scale engineering structures in operating conditions, modal param- eters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few years. It is well known that the cross-correlation function between the measured responses is a sum of complex exponential functions of the same form as the impulse response function of the original system. So this paper presents a time-domain operating modal identifcation global scheme and a frequency-domain scheme from output-only by cou- pling the cross-correlation function with conventional modal parameter estimation. The outlined techniques are applied to an airplane model to estimate modal parameters from response-only data.展开更多
To develop modal macro-strain （ MMS ） identification techniques and improve their applicability in a continuous health monitoring system for civil infrastructures, the concept of operational macro-strain shape （OMS...To develop modal macro-strain （ MMS ） identification techniques and improve their applicability in a continuous health monitoring system for civil infrastructures, the concept of operational macro-strain shape （OMSS） and the corresponding identification method are proposed under unknown ever-changing loading conditions, and the MMS is then obtained. The core of the proposed technique is mainly based on the specific property that the macro-strain transmissibility tends to be independent of external excitations at the poles of the system and converges to a unique value. The proposed method is verified using the experimental data from a three-span continuous beam excited by an impact hammer at different locations. The identified results are also compared with the commonly used methods, such as the peak- picking （PP） method, the stochastic subspace identification （SSI） method, and numerical results, in the case of unknown input forces. Results show that the proposed technique has unique merits in accuracy and robustness due to its combining multiple tests under changing loading conditions, which also reveal the promising application of the distributed strain sensing system in identifying MMS of operational structures, as well as in the structural health monitoring （SHM） field.展开更多
Output-only structural identification is developed by a refined Frequency Domain Decomposition（rFDD） approach, towards assessing current modal properties of heavy-damped buildings（in terms of identification challe...Output-only structural identification is developed by a refined Frequency Domain Decomposition（rFDD） approach, towards assessing current modal properties of heavy-damped buildings（in terms of identification challenge）, under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type Ⅱ bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames（with variable structural features） are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 ＂Far-Field＂（22 NS, 22 WE） earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes.展开更多
文摘A case study of excessive vibration on a motor-compressor system is presented in this paper.After barely two months of operation,the reciprocating compressor motor’s routine monitoring revealed excessive axial vibration amplitude.For this reason,the Operational Modal Analysis(OMA)was carried out in order to identify the pri-mary cause.According to the investigation,one of the harmonic components which was 18 times the motor’s running speed matched with a resonance frequency of 112 Hz.According to OMA study,the motor was vibrating in torsional motion because the compressor’s load had stimulated the entire motor-compressor unit at this reso-nance frequency.The analysis also demonstrates the bulging effect of the motor shaft’s axial vibration on the motor’s endplate.
基金China Postdoctoral Science Foundation Under Grant No. 2004035215 Jiangsu Planned Projects for Postdoctoral Research Funds 2004 Aeronautical Science Research Foundation Under Grant No. 04152065
文摘A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.
基金Supported by the National Natural Science Foundation of China（51079027）
文摘A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm （NExT-ERA） is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies.
基金Project supported by the National Natural Science Foundation of China(No.50205012),Aeronautics Foundation(No.01152059)and Civil Aviation Foundation(No.1007-272001).
文摘For some large-scale engineering structures in operating conditions, modal param- eters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few years. It is well known that the cross-correlation function between the measured responses is a sum of complex exponential functions of the same form as the impulse response function of the original system. So this paper presents a time-domain operating modal identifcation global scheme and a frequency-domain scheme from output-only by cou- pling the cross-correlation function with conventional modal parameter estimation. The outlined techniques are applied to an airplane model to estimate modal parameters from response-only data.
基金The National Natural Science Foudation of China(No.51578140)the Natural Science Foundation of Jiangsu Province(No.BK20151092)Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXZZ12_0108)
文摘To develop modal macro-strain （ MMS ） identification techniques and improve their applicability in a continuous health monitoring system for civil infrastructures, the concept of operational macro-strain shape （OMSS） and the corresponding identification method are proposed under unknown ever-changing loading conditions, and the MMS is then obtained. The core of the proposed technique is mainly based on the specific property that the macro-strain transmissibility tends to be independent of external excitations at the poles of the system and converges to a unique value. The proposed method is verified using the experimental data from a three-span continuous beam excited by an impact hammer at different locations. The identified results are also compared with the commonly used methods, such as the peak- picking （PP） method, the stochastic subspace identification （SSI） method, and numerical results, in the case of unknown input forces. Results show that the proposed technique has unique merits in accuracy and robustness due to its combining multiple tests under changing loading conditions, which also reveal the promising application of the distributed strain sensing system in identifying MMS of operational structures, as well as in the structural health monitoring （SHM） field.
基金Public research funding from“Fondi di Ricerca d’Ateneo ex 60%” and a ministerial doctoral grantfunds at the ISA Doctoral School,University of Bergamo,Department of Engineering and Applied Sciences (Dalmine)
文摘Output-only structural identification is developed by a refined Frequency Domain Decomposition（rFDD） approach, towards assessing current modal properties of heavy-damped buildings（in terms of identification challenge）, under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type Ⅱ bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames（with variable structural features） are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 ＂Far-Field＂（22 NS, 22 WE） earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes.
文摘基于协方差驱动随机子空间识别(covariance-driven stochastic subspace identification,SSI-COV)方法的模态参数识别具有强鲁棒性、高精度的优势,在结构工作模态分析中应用广泛。为保证模态参数识别的准确性,新近提出的基于随机子空间(stochastic subspace identification,SSI)的模态参数不确定性量化方法,可有效估计模态参数的方差,但由于其计算各中间变量时,需显式表示出Jacobian矩阵,导致矩阵运算维度高、计算效率低。为此,提出一种基于SSI-COV的模态参数不确定度高效计算方法。首先,计算振动响应相关函数的方差,通过奇异值分解(singular value decomposition,SVD),选取合适的奇异值截断阶数,由每阶奇异向量组装出多组Hankel矩阵的扰动。其次,根据一阶矩阵摄动理论,隐式计算SSI-COV算法各中间变量的一阶扰动,最终,由多组模态参数的扰动叠加计算出方差。最后,以桁架结构模型为例,采用所提方法辨识结构模态参数并计算模态参数方差,分析了Hankel矩阵维度及相关函数奇异值截断阶数对辨识结果的影响,结果表明计算得到的模态参数方差与蒙特卡洛仿真(Monte Carlo simulation,MCS)结果非常接近,且模态参数不确定度可作为剔除虚假模态的有效依据。
