Sensitivity and calibration of nondestructive evaluation method that uses neural-net processing of characteristic fringe patterns

Arthur J. Decker; Kenneth E. Weiland

doi:10.1117/12.501265

10 November 2003 Sensitivity and calibration of nondestructive evaluation method that uses neural-net processing of characteristic fringe patterns

Arthur J. Decker, Kenneth E. Weiland

Author Affiliations +

Proceedings Volume 5191, Optical Diagnostics for Fluids, Solids, and Combustion II; (2003) https://doi.org/10.1117/12.501265
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors usded for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

Citation Download Citation

Arthur J. Decker and Kenneth E. Weiland "Sensitivity and calibration of nondestructive evaluation method that uses neural-net processing of characteristic fringe patterns", Proc. SPIE 5191, Optical Diagnostics for Fluids, Solids, and Combustion II, (10 November 2003); https://doi.org/10.1117/12.501265

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