19 April 2012 Cointegration as a data normalization tool for structural health monitoring applications
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Abstract
The structural health monitoring literature has shown an abundance of features sensitive to various types of damage in laboratory tests. However, robust feature extraction in the presence of varying operational and environmental conditions has proven to be one of the largest obstacles in the development of practical structural health monitoring systems. Cointegration, a technique adapted from the field of econometrics, has recently been introduced to the SHM field as one solution to the data normalization problem. Response measurements and feature histories often show long-run nonstationarity due to fluctuating temperature, load conditions, or other factors that leads to the occurrence of false positives. Cointegration theory allows nonstationary trends common to two or more time series to be modeled and subsequently removed. Thus, the residual retains sensitivity to damage with dependence on operational and environmental variability removed. This study further explores the use of cointegration as a data normalization tool for structural health monitoring applications.
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Dustin Y. Harvey, Dustin Y. Harvey, Michael D. Todd, Michael D. Todd, } "Cointegration as a data normalization tool for structural health monitoring applications", Proc. SPIE 8348, Health Monitoring of Structural and Biological Systems 2012, 834810 (19 April 2012); doi: 10.1117/12.915226; https://doi.org/10.1117/12.915226
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