Full Content is available to subscribers

Subscribe/Learn More  >

Modal Analysis of Systems Using a Neuro-Fuzzy Approach

[+] Author Affiliations
Farbod Khoshnoud

University of British Columbia, Vancouver, BC, Canada; California Institute of Technology, Pasadena, CA

Clarence W. de Silva

University of British Columbia, Vancouver, BC, Canada

Paper No. IMECE2010-37798, pp. 1085-1097; 13 pages
  • ASME 2010 International Mechanical Engineering Congress and Exposition
  • Volume 8: Dynamic Systems and Control, Parts A and B
  • Vancouver, British Columbia, Canada, November 12–18, 2010
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4445-8
  • Copyright © 2010 by ASME


A novel method of modal analysis for vibration modeling of systems is presented in this paper. In the developed method, first, mode shapes of the structure that is being analyzed are approximated. The approximate mode shapes are expressed by fuzzy sets where approximate deflections or displacement magnitudes of the mode shapes are described by fuzzy linguistic terms such as Zero, Medium, and Large. Fuzzy membership functions provide a means of dealing with the imprecisely defined system and it gives access to a large repertoire of tools available in the field of fuzzy reasoning. Second, fuzzy representations of the approximate mode shapes, called Fuzzy Mode Shapes in this paper, are updated using modal analysis data as obtained through experimentation. Finally, artificial neural networks are used as a tool to obtain an accurate version of the mode shape data by learning the target set of the data. An appropriate analogy of the application of Fuzzy Mode Shapes in the first step is the Starting Mode Shape Vectors in numerical eigenvector problem where the starting vector is updated through an iterative process. In this paper iterative updating process of mode shapes is carried out for the application of experimental modal testing. In this approach the differences between the fuzzy mode shapes and the corresponding measured modal testing data are minimized through an iterative process. In validating the developed technique for vibration modeling of one-dimensional and two-dimensional elastic bodies and structures, modeling of elastic beams, a clamped-free-clamped-free plate and a frame are used as illustrative examples. The solutions of the corresponding simulations are compared with the results from finite element computations and analytical model solutions. The good agreement of the results obtained for these models justifies the application of the developed method in experimental vibration modeling of systems. Use of the fuzzy-neural approach as developed in the paper expands the coverage of experimentally measured data, which is normally limited to a small number of measurement sets due to the limited number of available vibration sensors in the analyzed system. Neural networks provide a satisfactory interpolation of two sets of data including a) modal test data, which is accurate but is normally available only for a few measured points, and b) Fuzzy Mode Shapes, which are available for large number of points but are approximate.

Copyright © 2010 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In