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TECHNICAL PAPERS

Damage Identification Using Sensitivity-Enhancing Control and Identified Models

[+] Author and Article Information
Jason A. Solbeck1

Thayer School of Engineering,  Dartmouth College, 8000 Cummings Hall, Hanover NH 03755jsolbeck@sound-innovations.net

Laura R. Ray

Thayer School of Engineering,  Dartmouth College, 8000 Cummings Hall, Hanover NH 03755

1

Corresponding author.

J. Vib. Acoust 128(2), 210-220 (Jun 22, 2005) (11 pages) doi:10.1115/1.2159037 History: Received January 03, 2005; Revised June 22, 2005

This paper investigates a coherence approach for locating structural damage using modal frequencies and transfer function parameters identified from input-output data using Observer/Kalman filter identification (OKID). Autonomous damage identification using such forward methods generally require (i) a structural model by which to relate measured and predicted modal properties induced by damage, and (ii) good sensitivity of modal parameter changes to damage states. Using the coherence approach, a damage parameter vector comprised of a finite set of modal frequencies and transfer function parameters is hypothesized for each damage case using either identified or analytic structural models. Measured parameter vectors are extracted from experimental input-output data for a damaged structure using OKID and are compared to hypotheses to determine the most likely damage state. The richness of the parameter vector set, which is comprised of high-quality frequency measurements and lower-quality transfer function parameters, is evaluated in order to determine the ability to uniquely localize damage. The method is evaluated experimentally using a three-degree-of-freedom torsional system and a space-frame truss. Damage parameter hypotheses are generated from a model of the healthy structure developed by system identification in the torsional system, and an analytic model is used to generate damage hypotheses for the truss structure. Feedback control laws enhance the parameter vectors by including closed-loop modal frequencies in order to reduce noise sensitivity and improve uniqueness of parameter vector hypotheses to each damage case. Results show improvements in damage identification using damage parameter vectors comprised of open- and closed-loop modal frequencies, even when model error exists in structural models used to form damage parameter vector hypotheses.

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Copyright © 2006 by American Society of Mechanical Engineers
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References

Figures

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Figure 12

Stick diagrams summarizing coherence approach experimental damage identification for the space-frame truss for the damage cases when the large mass is attached at nodes 26, 32, and 36. A star indicates a node that is selected by the decision algorithm, and a circle indicates the actually damaged node.

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Figure 13

Coherence-approach experimental damage identification results for the space-frame truss for the special case when the small mass is attached at node 26 (circled, at left) and the large mass is attached at node 32 (circled, at right)

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Figure 2

Root-mean-square error in prediction of future outputs for four additional data sets at a variety of different values for p

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Figure 3

Proliferation of identified eigenvalues with increased OKID parameter, p

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Figure 4

Simple schematic for explanation of coherence method

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Figure 5

The space-frame truss structure in the T configuration on the left. The location of two of the proof-mass actuators is shown in the upper right. The mounting of two of the accelerometers is shown in the lower right.

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Figure 6

Experimental damage identification using the coherence approach with different combinations of modal parameters. Damage case is increase in rotational inertia of disk 1 (m1).

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Figure 7

Coherence approach experimental damage identification for the following damage cases, from top to bottom: an increase in rotational inertia of disk 2 (m2), disk 3 (m3), disks 1 and 2 (m12), disks 1 and 3 (m13), and disks 2 and 3 (m23)

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Figure 8

Coherence approach experimental damage identification results for the following damage cases, from top to bottom: an increase in stiffness of spring 1 (k1), spring 2 (k2), and springs 1 and 2 (k12)

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Figure 9

Coherence approach experimental damage identification results for the healthy case

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Figure 10

Coherence-approach experimental damage identification results for the space-frame truss when the structure is undamaged. A star on the stick diagram at right indicates a node that is selected by the decision algorithm.

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Figure 11

Coherence-approach experimental damage identification results for the space-frame truss when the large mass is attached at node 22 (circled on stick diagram)

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Figure 1

Schematic showing a simplified version of the damage identification process

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