Abstract

There have been many investigations into structural health monitoring system performance for industrial deployment. However, extensive studies on long-term environmental effects, their effects on accurate damage detection, and the handling of large data sets have remained representative challenges. This paper discusses results from a long-term study of a guided wave structural monitoring system in outdoor conditions in Salt Lake City, Utah. We study the effects of environmental variations, compensation strategies on these variations, and how to handle the processing of such large data sets. We study correlation coefficients with baseline guided wave data and their relationship to environmental parameters. We study a data compression method based on random projections to efficiently manage and process the large guided wave data sets. The qualitatively analyzed environmental parameters and correlation coefficients confirm that temperature compensation is a key feature for accurate damage detection. The qualitative analysis of the random projection data compression suggests a promising method for working with a large wave data set.

How to Cite:

Kim, S. ., Adams, D. O. & Harley, J. B., (2019) “A study of environmental effects on long term guided wave structural health monitoring in outdoor conditions”, Review of Progress in Quantitative Nondestructive Evaluation .