An Experimental Study of Structural Health Monitoring Using Incomplete Measurements

[+] Author and Article Information
D. C. Zimmerman

Mechanical Engineering Department, University of Houston, Houston, TX

S. W. Smith

Engineering Mechanics, University of Kentucky, Lexington, KY

H. M. Kim, T. J. Bartkowicz

McDonnell Douglas Aerospace—Space & Defense Systems, Houston, TX

J. Vib. Acoust 118(4), 543-550 (Oct 01, 1996) (8 pages) doi:10.1115/1.2888333 History: Received May 01, 1994; Revised December 01, 1994; Online February 26, 2008


In this paper, algorithmic approaches to enhance structural health monitoring capability when faced with incomplete measurements are addressed. The incomplete measurement problem has two aspects: (i) experimental measurement of a lesser number of modes of vibration than that of the analytical model and (ii) experimental measurement of a lesser number of degrees of freedom than that of the analytical model. Studies comparing model reduction, eigenvector expansion, and a hybrid model reduction/eigenvector expansion to address the second contribution are performed using experimental data. These approaches to the incomplete measurement problem are evaluated within the frameworks of multiple-constraint matrix adjustment (both sparsity and nonsparsity preserving algorithms) and minimum rank perturbation theory, which are both applicable for model refinement as well as damage location. Experimental evaluation of the proposed approaches utilize data from the NASA Langley Research Center 8-bay truss and McDonnell Douglas Aerospace 10-bay truss facilities.

Copyright © 1996 by The American Society of Mechanical Engineers
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