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Liu J.M.,China Orient Institute of Noise and Vibration | Liu F.,Beijing Institute of Technology | Zhu W.D.,University of Maryland Baltimore County
Conference Proceedings of the Society for Experimental Mechanics Series | Year: 2016

There is common denominator for the FRFs of mode test which determine the modal frequency and damping. For the modal parameter identification of SIMO or MISO, one row or one column of FRF matrix is known, by applying pure normal mode test technology which is often used in the Ground Vibration Test (GVT) of aeroplane, a group of real coefficients can be computed out, each coefficient corresponds to one FRF, the sum of all the FRF multiplying the computed coefficient constructs one new FRF which includes only one mode. By this way, the precise modal frequency and modal damping can be identified. Changing the coefficients, the other mode’s frequency and damping can also be identified. For MIMO test, one new group FRFs which include only one mode can be constructed in similar way. The precise modal frequency, modal damping and modal shape can be identified. Changing the coefficients, the other mode’s parameter can also be identified. Even if the number of FRF groups for MIMO is not enough, one new group FRFs can be obtained which greatly deleting the nearest mode’s influence, improve the preciseness of identified modal parameters, especially the modal shape. In this paper, the method of computing the coefficients are introduced for SIMO, MISO and MIMO test. The real engineering example is given to verify the effective and correct of new algorithm. For mode test with very big damping, the coupling of different modes is very seriously, the new algorithm can realize the decoupling easily and obtain the precise modal parameters. © The Society for Experimental Mechanics, Inc. 2016. Source


Xu Y.F.,University of Maryland Baltimore County | Liu J.M.,China Orient Institute of Noise and Vibration | Zhu W.D.,University of Maryland Baltimore County | Zhu W.D.,Harbin Institute of Technology
Journal of Sound and Vibration | Year: 2015

Operational modal analysis (OMA), or output-only modal analysis, has been widely conducted especially when excitation applied on a structure is unknown or difficult to measure. Discrete cross-correlation functions and cross-power spectra between a reference data series and measured response data series are bases for OMA to identify modal properties of a structure. Such functions and spectra can be efficiently transformed from each other using the discrete Fourier transform (DFT) and inverse DFT (IDFT) based on the cross-correlation theorem. However, a direct application of the theorem and transforms, including the DFT and IDFT, can yield physically erroneous results due to periodic extension of the DFT on a function of a finite length to be transformed, which is false most of the time. Padding zero series to ends of data series before applying the theorem and transforms can reduce the errors, but the results are still physically erroneous. A new methodology is developed in this work to calculate discrete cross-correlation functions of non-negative time delays and associated cross-power spectra, referred to as half spectra, for OMA. The methodology can be extended to cross-correlation functions of any time delays and associated cross-power spectra, referred to as full spectra. The new methodology is computationally efficient due to use of the transforms. Data series are properly processed to avoid the errors caused by the periodic extension, and the resulting cross-correlation functions and associated cross-power spectra perfectly comply with their definitions. A coherence function, a convergence function, and a convergence index are introduced to evaluate qualities of measured cross-correlation functions and associated cross-power spectra. The new methodology was numerically and experimentally applied to an ideal two-degree-of-freedom (2-DOF) mass-spring-damper system and a damaged aluminum beam, respectively, and OMA was conducted using half spectra to estimate their natural frequencies, damping ratios, and mode shapes. Natural frequencies, damping ratios, and mode shapes of the 2-DOF system obtained from OMA agree well with theoretical ones from complex modal analysis; natural frequencies, damping ratios, and mode shapes of the beam from OMA agreed well with those from experimental modal analysis. © 2015 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved. Source


Yao Y.,Changan University | Wei S.,China Orient Institute of Noise and Vibration | Zhao J.,Changan University | Chen S.,Changan University | And 2 more authors.
Research Journal of Applied Sciences, Engineering and Technology | Year: 2013

A conventional muffler used in vibratory rollers is usually designed based on experience and its performance could be enhanced in a large degree through structure optimization. In order to evaluate performance of reactive muffler and its effect on power loss of engine, flow field of muffler was discussed by CFD comparing with experimental test and the structure of reactive muffler was optimized. Based on results of simulation and optimization, the reactive muffler used in vibratory rollers with weight of 13t was fabricated and its field test was carriedon. The simulate results showed that velocity field coincided with the pressure field basically, which indicates that the optimized muffler -2# has excellent aerodynamic characteristics and rational design of damping units. The results of field tests showed that 2# muffler had better acoustic insertion loss with little pressure loss. Acoustic insertion loss was 17~18.4 dB (A) at engine speed of 2450 rpm, which meets the designing goal. © Maxwell Scientific Organization, 2013. Source


Qian W.,University of Shanghai for Science and Technology | Pan S.,University of Shanghai for Science and Technology | Mei J.,University of Shanghai for Science and Technology | Ying H.,China Orient Institute of Noise and Vibration
2013 3rd International Conference on Consumer Electronics, Communications and Networks, CECNet 2013 - Proceedings | Year: 2013

It is proposed that a kind of WI-FI wireless architecture based on cloud smart data acquisition device is designed in this paper. Hardware structure of wireless WI-FI based on data acquisition device is designed and Wi-Fi driver is developed in the Linux system under the cloud smart device architecture. When designing the application program, the point-to-point AP mode and the multipoint connection at the same time STATION mode can be chosen as the WI-FI mode of cloud smart data acquisition device. With test case showing, low power consumption, data fidelity, high throughput of wireless Wi-Fi technology is suitable for communication of the cloud smart data acquisition device. © 2013 IEEE. Source


Li Y.,Northeastern University China | Zhang J.,Shenyang University of Chemical Technology | Dai L.,Northeastern University China | Zhang Z.,China Orient Institute of Noise and Vibration
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2012

The human auditory system possesses excellent capability to analysis non-stationary signal. In auditory system, before a signal is recognized by the auditory cortex, it is sequentially processed by the basilar membrane, which can be seen as a bandpass filterbank, and other elements in auditory system. Therefore, to describe the structure features of signal in time-frequency space, an auditory model is proposed based on Wang-Brown model and the auditory nerve fiber oscillatory network with single layer. This model consists of basilar membrane, inner hair cells, middle auditory stage and auditory cortex, and the auditory cortex model is a single layer auditory nerve fiber oscillatory network. According to the characteristic of mechanical vibration signal, the random term and lateral inhibitor in Wang-Brown model are ignored, and the inner hair cells model is simplified. Furthermore, the active rule of neuron and the connection mode between neurons are designed. In proposed model, the oscillatory network synthesizes the output of the preceding submodels. The oscillation of neurons corresponding to similar time-frequency structure is synchronized. Therefore the distribution of synchronized neurons is utilized to describe the time-frequency structure feature of the analyzed signal. The proposed model is evaluated by using the run-up vibration signals of a rotor with different fault and of a gear box used on wind turbine. The results show that the proposed model can effectively describe the structure features and evolvement of a signal with low data quantity, and is sensitive to the instantaneous change of the signal. Then the model is convenient to be applied in intelligent recognition. © 2012 Journal of Mechanical Engineering. Source

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