Paper
1 August 2003 Excitation considerations for attractor property analysis in vibration-based damage detection
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Abstract
In past work, we have presented a methodology for vibration based damage detection derived from the characterization of changes in the geometric properties of the time domain response of a structure. In brief, input forcing signals and output response signals can be transformed into state space geometrical representations. When allowed to evolve to a steady state, the geometric object is called an attractor. Certain properties of the attractor, such as the local variance of neighborhoods of points or prediction errors between attractors, have been shown to correlate directly with damage. While most inputs will generate some type of attracting geometric object, prescribing a low dimensional input forcing signal helps to maintain a low dimensional output signal which in turn simplifies the calculation of attractor properties. Work to date has incorporated the use of a chaotic input forcing signal based on its low dimensionality yet useful frequency content. In this work we evaluate various forms of shaped noise as alternative effectively low dimensional inputs. We assess whether the intrinsic properties of the chaotic input leads to better damage detection capabilities than various shaped noise inputs. The experimental structure considered is a thin plate with weld line damage.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen T. Trickey, Michael D. Todd, Mark E. Seaver, and Jonathan M. Nichols "Excitation considerations for attractor property analysis in vibration-based damage detection", Proc. SPIE 5047, Smart Nondestructive Evaluation and Health Monitoring of Structural and Biological Systems II, (1 August 2003); https://doi.org/10.1117/12.483988
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Cited by 6 scholarly publications.
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KEYWORDS
Damage detection

Linear filtering

Interference (communication)

Principal component analysis

System identification

Complex systems

Electronic filtering

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