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  • 1.
    Feng, Leping
    et al.
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, MWL Structural and vibroacoustics.
    Ramanathan, Sathish Kumar
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, MWL Structural and vibroacoustics.
    On application of radiation loss factor in the prediction of sound transmission loss of a honeycomb panel2012In: International Journal of Acoustics and Vibration, ISSN 1027-5851, Vol. 17, no 1, p. 47-51Article in journal (Refereed)
    Abstract [en]

    The application of the radiation loss factor in the prediction of sound transmission loss of a lightweight, orthotropic sandwich panel is investigated in this paper. Comparisons with measurements show that predictions often underestimate the sound transmission loss of the panel around the corresponding critical frequency when the measured loss factor, which in principle includes the radiation loss factor, is used. This is due to the measurement methods used for the loss factor and the band average. It is thus recommended to use the loss factor measured at low frequencies plus the theoretical radiation loss factor in order to improve the prediction of the sound transmission loss of a honeycomb panel around the critical frequency.

  • 2.
    Henriksson, Mats
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Analysis of Gear Noise and Dynamic Transmission Error Using a Recursive Kalman Filter AlgorithmIn: International Journal of Acoustics and Vibration, ISSN 1027-5851Article in journal (Other academic)
    Abstract [en]

    Measurements of dynamic transmission error (DTE) and gear noise have been usedto investigate the relation between DTE and noise. A Kalman filter order trackingmethod was used to calculate the amplitudes of the gear mesh orders. The DTE showsnon-linear behaviour with rotating speed , which decreases as the torque is increased.There seems to be a linear relationship between noise and DTE for the higher torquesmeasured. This indicates that for the higher torques measured, a linear model can beused to predict the dynamic behaviour of the gear system.

  • 3.
    Henriksson, Mats
    et al.
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Feng, Leping
    KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
    Pang, Yuet-Yan
    On Transmission Error, Shuttling Forces and Friction Forces as Gear Noise ExcitationIn: International Journal of Acoustics and Vibration, ISSN 1027-5851Article in journal (Other academic)
    Abstract [en]

    Traditionally, transmission error (TE) has been used to asses the noise propertiesof gears. Measurements of gear noise for a complete truck gearbox have been used tocorrelate noise from a gear pair with calculated static transmission error, shuttling forceand friction forces. Two gear pairs with very similar macro geometry but differentmicro geometry was used. The measurement results show that there is a limitationif transmission error is considered as the only excitation mechanism when designingquiet gears. Often TE is multiplied with the gear mesh stiffness in order to calculatean excitation force. For gear not operating above the critical gear mesh resonance,this often overestimates the importance of TE, thus underestimating the importance ofother sources such as shuttling and friction forces.

  • 4. Scholte, R.
    et al.
    Lopez Arteaga, Ines
    Eindhoven University of Technology.
    Roozen, N. B.
    Nijmeijer, H.
    Experimental application of high precision k-space filters and stopping rules for fully automated near-field acoustical holography2008In: International Journal of Acoustics and Vibration, ISSN 1027-5851, Vol. 13, no 4, p. 157-164Article in journal (Refereed)
    Abstract [en]

    In general, inverse acoustics problems are ill-posed. Without proper regularization action taken noisy measurements result in an increasingly disturbed solution of the inverse acoustics wave equation as the distance from the measurement plane to the desired source grows. Two distinctive steps take place in the regularization process for planar near-field acoustical holography (PNAH): first, a low-pass filter function is defined and secondly a stopping rule is applied to determine the parameter settings of the filter. In acoustical imaging practice, it turns out to be very hard to determine the right filter for a certain case, ideally by means of an automatic search for the (near-) optimal parameters. This paper presents the practical application of a novel automated method that combines fitted filters for a broad number of possible experimental sources combined with highly efficient stopping rules by taking advantage of k-space. Also, a number of well-known and newly developed filter functions and stopping rules are discussed and compared with one another. Results based on actual measurements demonstrate the effectiveness, applicability, and precision of the fully implemented and automated regularization process for PNAH. Practical results even show acoustic source visualization below one millimeter primarily by successful application of k-space regularization. Implementations include modifications of Tikhonov, exponential and truncation low-pass filters, L-curve Generalised Cross-Validation (GCV) and the novel Cut-Off and Slope (COS) parameter selection methods for PNAH COS iteration in combination with either a modified exponential or Tikhonov low-pass filter results in an automated selection of the regularization parameters and eventually a fully automated PNAH system.

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