Archives of Acoustics, 48, 2, pp. 201–218, 2023
10.24425/aoa.2023.144271

Study on the Effectiveness of Monte Carlo Filtering when Correcting Negative SEA Loss Factors

Paweł NIERADKA
Wrocław University of Science and Technology; KFB Acoustics, Acoustic Research and Innovation Center
Poland

Andrzej DOBRUCKI
Wrocław University of Science and Technology
Poland

The power injection method (PIM) is an experimental method used to identify the statistical energy analysis (SEA) parameters (called loss factors – LFs) of a vibroacoustic system. By definition, LFs are positive real numbers. However, it is not uncommon to obtain negative LFs during experiments, which is considered a measurement error. To date, a recently proposed method, called Monte Carlo filtering (MCF), of correcting negative coupling loss factors (CLFs) has been validated for systems that meet SEA assumptions. In this article, MCF was validated for point connections and in conditions where SEA assumptions are not met (systems with low modal overlap, non-conservative junctions, strong coupling). The effect of removing MCF bias on the results was also examined. During the experiments, it was observed that the bias is inversely proportional to the damping loss factor of the examined subsystems. The obtained results confirm that the PIM, combined with MCF, allows to determine non-negative SEA parameters in all considered cases.
Keywords: statistical energy analysis; coupling loss factor; Monte Carlo filtering; power injection method
Full Text: PDF
Copyright © The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

References

Bhagwan M.M., Popuri B. (2019), Estimation of coupling loss factors for rectangular plates with different materials and

junctions, Noise & Vibration Worldwide, 50(9–11): 306–312, doi: 10.1177/0957456519883264.

Bies D.A., Hamid S. (1980), In situ determination of loss and coupling loss factors by the power injection method, Journal of Sound and Vibration, 70(2): 187–204, doi: 10.1016/0022-460X(80)90595-7.

Borello G. (2018), Prediction of sound transmission in aircraft over the mid and high frequency range, [in:] Inter-Noise and Noise-Con Congress and Conference Proceedings, 258(2): 5115–5124.

Bouhaj M., von Estorff O., Peiffer A. (2017), An approach for the assessment of the statistical aspects of the SEA coupling loss factors and the vibrational energy transmission in complex aircraft structures: Experimental investigation and methods benchmark, Journal of Sound and Vibration, 403: 152–172, doi: 10.1016/j.jsv.2017.05.028.

Cacciolati C., Guyader J.L. (1994), Measurement of SEA coupling loss factors using point mobilities, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 346(1681): 465–475, doi: 10.1098/rsta.1994.0029.

Chen X.,Wang D., Ma Z. (2012), Simulation on a car interior aerodynamic noise control based on statistical energy analysis, Chinese Journal of Mechanical Engineering, 25(5): 1016–1021.

Cimerman B., Bharj T., Borello G. (1997), Overview of the experimental approach to statistical energy analysis, [in:] SAE Noise and Vibration Conference and Exposition, doi: 10.4271/971968.

Craik R.J.M. (1982), The prediction of sound transmission through buildings using statistical energy analysis, Journal of Sound and Vibration, 82(4): 505–516, doi: 10.1016/0022-460X(82)90404-7.

Culla A., Sestieri A. (2006), Is it possible to treat confidentially SEA the wolf in sheep’s clothing?, Mechanical Systems and Signal Processing, 20(6): 1372–1399, doi: 10.1016/j.ymssp.2005.02.007.

de las Heras M.J.F., Chimeno M., Millán E.R., Hidalgo F.S. (2018), On the influence of the condition number on the resolution of an ESEA model, [in:] Inter-Noise and Noise-Con Congress and Conference Proceedings, 257(1): 153–161.

de las Heras M.J.F., Manguán M.C., Millán E.R., de las Heras L.J.F., Hidalgo F.S. (2020), Determination of SEA loss factors by Monte Carlo Filtering, Journal of Sound and Vibration, 479: 115348, doi: 10.1016/j.jsv.2020.115348.

Fahy F.J., Ruivo H.M. (1997), Determination of statistical energy analysis loss factors by means of an input power modulation technique, Journal of Sound and Vibration, 203(5): 763–779, doi: 10.1006/jsvi.1996.0892.

Finnveden S. (2011), A quantitative criterion validating coupling power proportionality in statistical energy analysis, Journal of Sound and Vibration, 330(1): 87–109, doi: 10.1016/j.jsv.2010.08.003.

Gu J., Sheng M. (2015), Improved energy ratio method to estimate coupling loss factors for series coupled structure, Journal of Mechanical Engineering, 45(1): 37–40, doi: 10.3329/jme.v45i1.24382.

Hattori K., Nakamachi K., Sanada M. (1985), Prediction of underwater sound radiated from ship’s hull by using statistical energy analysis, Proceedings of Inter-Noise 85, Vol. II, p. 645.

Hodges C.H., Nash P., Woodhouse J. (1987), Measurement of coupling loss factors by matrix fitting: An investigation of numerical procedures, Applied Acoustics, 22(1): 47–69, doi: 10.1016/0003-682X(87)90015-6.

Hopkins C. (2002), Statistical energy analysis of coupled plate systems with low modal density and low modal overlap, Journal of Sound and Vibration, 251(2): 193–214, doi: 10.1006/jsvi.2001.4002.

Hwang H.J. (2002), Prediction and validation of high frequency vibration responses of NASA Mars Pathfinder spacecraft due to acoustic launch load using statistical energy analysis, NASA Technical Reports Server.

Ji L., Sheng X., Xiao X., Wen Z., Jin X. (2015), A review of mid-frequency vibro-acoustic modelling for high-speed train extruded aluminium panels as well as the most recent developments in hybrid modelling techniques, Journal of Modern Transportation, 23(3): 159–168, doi: 10.1007/s40534-015-0080-4.

Lafont T., Totaro N., Le Bot A. (2014), Review of statistical energy analysis hypotheses in vibroacoustics, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 470(2162): 20130515, doi: 10.1098/rspa.2013.0515.

Lalor N. (1990), Practical Consideration for the Measurement of Internal and Coupling Loss Factors on Complex Structures, ISVR Technical Report.

Lalor N. (1996), Experimental statistical energy analysis: A tool for the reduction of machinery noise, The Journal of the Acoustical Society of America, 99(4): 2568–2574, doi: 10.1121/1.415057.

Le Bot A. (2015), Foundation of Statistical Energy Analysis in Vibroacoustics, Oxford University Press, United Kingdom.

Lyon R.H., DeJong R.G., (1995), Theory and Application of Statistical Energy Analysis, Elsevier.

Mandale M.B., Bangaru Babu P., Sawant S.M. (2016), Statistical energy analysis parameter estimation for different structural junctions of rectangular plates, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 230(15): 2603–2610, doi: 10.1177/0954406215615628.

Ming R. (1998), The measurement of coupling loss factors using the structural intensity technique, The Journal of the Acoustical Society of America, 103(1): 401–407, doi: 10.1121/1.421096.

Nieradka P., Dobrucki A. (2018), Insertion loss of enclosures with lined slits, [in:] Euronoise 2018-Conference Proceedings.

Pankaj A.C. (2019), Numerical and Experimental Investigations on Damage Detection in Joints Based on Statistical Energy Analysis like Approach, Ph.D. Thesis, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal.

Panuszka R., Wiciak J., Iwaniec M. (2005), Experimental assessment of coupling loss factors of thin rectangular plates, Archives of Acoustics, 30(4): 533–551.

Price A.J., Crocker M.J. (1970), Sound transmission through double panels using statistical energy analysis, The Journal of the Acoustical Society of America, 47(3A): 683–693, doi: 10.1121/1.1911951.

Smith Jr. P.W. (1979), Statistical models of coupled dynamical systems and the transition from weak to strong coupling, The Journal of the Acoustical Society of America, 65(3): 695–698, doi: 10.1121/1.382481.

Yap F.F., Woodhouse J. (1996), Investigation of damping effects on statistical energy analysis of coupled structures, Journal of Sound and Vibration, 197(3): 351–371, doi: 10.1006/jsvi.1996.0536.

Yoganandh M., Nagaraja J., Venkatesham B. (2019), Prediction of insertion loss of lagging in rectangular duct using statistical energy analysis, Noise Control Engineering Journal, 67(6): 438–446, doi: 10.3397/1/376740.

Zarate R., Matus E., Lopez M., Ballesteros L. (2017), Design of quieter kitchen appliances: Sound pressure level modeling and validation of a household refrigerator using statistical energy analysis, [in:] Proceedings of Meetings on Acoustics, 30(1): 030009, doi: 10.1121/2.0000632.




DOI: 10.24425/aoa.2023.144271