The University of Southampton
University of Southampton Institutional Repository

Efficient computation of spectral moments for determination of random response statistics

Efficient computation of spectral moments for determination of random response statistics
Efficient computation of spectral moments for determination of random response statistics
This paper will first review the use of temporal spectral moments, and then propose an efficient running sum technique to determine the spectral moments frequency by frequency. Combining this summation process with modal superposition techniques allow a significant reduction in input and output file sizes and computational time.
The proposed technique uses finite element analysis (FEA) to generate modal vectors that are post processed using mode superposition techniques to calculate the power spectral density (PSD) moments, eliminating the need to form PSD response functions. This requires storage of only the modal response and force vectors and the running sum of the PSD moments. Once the moments of the PSD are determined, the random response statistic calculations are a straightforward problem. Two example problems are given: a simple cantilever beam and a detailed optical telescope. These examples show how different problems can be solved using the proposed technique.
9073802822
2677-2692
ISMA
Sweitzer, Karl A.
520762dc-9a0b-44fb-a05f-b196c7d4a48f
Bishop, Neil W.M.
bf6a0492-1478-41bf-923b-d338264fa8bb
Genberg, Victor L.
0943e9c6-a169-4daf-bff7-2eeeb38f4f81
Sweitzer, Karl A.
520762dc-9a0b-44fb-a05f-b196c7d4a48f
Bishop, Neil W.M.
bf6a0492-1478-41bf-923b-d338264fa8bb
Genberg, Victor L.
0943e9c6-a169-4daf-bff7-2eeeb38f4f81

Sweitzer, Karl A., Bishop, Neil W.M. and Genberg, Victor L. (2004) Efficient computation of spectral moments for determination of random response statistics. In Proceedings of ISMA. ISMA. pp. 2677-2692 .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper will first review the use of temporal spectral moments, and then propose an efficient running sum technique to determine the spectral moments frequency by frequency. Combining this summation process with modal superposition techniques allow a significant reduction in input and output file sizes and computational time.
The proposed technique uses finite element analysis (FEA) to generate modal vectors that are post processed using mode superposition techniques to calculate the power spectral density (PSD) moments, eliminating the need to form PSD response functions. This requires storage of only the modal response and force vectors and the running sum of the PSD moments. Once the moments of the PSD are determined, the random response statistic calculations are a straightforward problem. Two example problems are given: a simple cantilever beam and a detailed optical telescope. These examples show how different problems can be solved using the proposed technique.

This record has no associated files available for download.

More information

Published date: 2004
Additional Information: Signal processing and instrumentation - SP1
Venue - Dates: ISMA 2004 International Conference on Noise and Vibration Engineering, Katholieke Universiteit Leuven, Belgium, 20-22 September 2004, Leuven, 2004-09-20 - 2004-09-22

Identifiers

Local EPrints ID: 28167
URI: http://eprints.soton.ac.uk/id/eprint/28167
ISBN: 9073802822
PURE UUID: 2d06885b-f22b-4422-aff4-64a135d6412f

Catalogue record

Date deposited: 02 May 2006
Last modified: 07 Mar 2024 18:11

Export record

Contributors

Author: Karl A. Sweitzer
Author: Neil W.M. Bishop
Author: Victor L. Genberg

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×