Abstract
This paper deals with the statistical aspects of the Power Injection Method (PIM), a well-established technique to experimentally derive the SEA loss factor model. It is outlined how the variances of the energies measured in the power injection process can be obtained and how approximate analytical expressions describing the propagation of the energy variances through the loss factor calculation can be derived based on a first order Taylor expansion. The expressions giving the loss factor variances as functions of the energy variances offer the practical advantage that they can be quickly evaluated during the acquisition process. Subsequently, it is discussed how the confidence levels of the SEA predictions can be obtained. The practical usefulness and limitations of the derived analytical expressions are investigated based on a Monte-Carlo variability analysis. The statistical theory is then applied to a railway carriage of a high-speed train, illustrating how the effectiveness of loss factor modifications can be evaluated in terms of confidence levels.
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References
R.H. Lyon, “Statistical Energy Analysis of Dynamical Systems: Theory and Practice”, MIT Press, Cambridge, 1975.
D.A. Bies and S. Hamid, “In situ determination of loss and coupling loss factors by the power injection method, Journal of Sound and Vibration”, 70(2), pp. 187–204, 1980.
N. Lalor, “The experimental determination of vibrational energy balance in complex structures”, Proc. SIRA Conference on Stress and Vibration — Recent Developments in Industrial Measurements and Analysis, London, 1989.
L. Hermans, K. Wyckaert, K. De Langhe, “The Process to Experimentally Identify the Statistical Energy Analysis Parameters of Industrial Structures : Step by Step”, Proc. of ISMA2 l, Leuven, 1996.
N. Lalor, “Practical considerations for the measurements of intermal and coupling loss factors on complex structures”, ISVR Technical Report No. 182, June 1990.
Stephen B. Vardeman, “Statistics for Engineering Problem Solving”, IEEE Press — PWS Publishing Company, New York — Boston, 1994.
L. Hermans, K. De Langhe and L. Demeestere, “Methods to Estimate the Confidence Level of the Experimentally Derived Statistical Energy Analysis Model: Application to Vehicles”, Proc. SAE Noise and Vibration, Traverse City, 1997.
L. Hermans, “On the Influence of the Subsystem Mass or Volume in Experimental Statistical Energy Analysis”, to be published in Proc. Inter-Noise 97, Budapest, August, 1997.
K. Delanghe, “High Frequency Vibrations : Contributions to Experimental and Computational SEA Parameter ldentification Techniques”, Ph.D. dissertation, Department PMA, K.U.Leuven, 1996.
L. Hermans, K. Wyckaert, “Experimental Statistical Energy Analysis : Internal and Coupling Loss Factor Matrix Validation”, Proc. Inter-noise, Inter-Noise 96, Liverpool, July-August 1996.
K. De Meester, L. Hermans, K. Wyckaert, N. Cuny, “Experimental SEA on a Highspeed Train Camiage”. Proc. of ISMA21, Leuven, 1996.
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© 1999 Springer Science+Business Media Dordrecht
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Hermans, L., de Langhe, K., Demeestere, L. (1999). On the Calculation of Confidence Levels of the Experimentally Derived Internal and Coupling Loss Factors. In: Fahy, F.J., Price, W.G. (eds) IUTAM Symposium on Statistical Energy Analysis. Solid Mechanics and Its Applications, vol 67. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9173-7_22
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DOI: https://doi.org/10.1007/978-94-015-9173-7_22
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5131-8
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