Prediction error of Johansen cointegration residuals for structural health monitoring

Repository Testing for cointegration using the Johansen approach

The Wold Representation, Cointegration and the Johansen Trace Test +,*

This paper considers the importance of moving average errors for the Johansen trace test of cointegrating rank based upon approximating vector autoregressions (VARs). Two cases are emphasized and explored, both taking as their starting point the Wold decomposition. Though each case defined satisfies the same cointegrating vector, one is a case of multicointegration while the other, based on res...

Fatigue Life Prediction Using Hybrid Prognosis for Structural Health Monitoring

A reliable prognostics framework is essential to address failure mode mitigation and life cycle cost of aerospace systems. Metallic aircraft components are subject to a variety of inservice loading conditions and prediction of fatigue life remains a critical challenge. A hybrid prognostic model, which can accurately predict the crack growth regime and the residual useful life estimate (RULE) of...

Cointegration and Error Correction

1 The Background Elementary courses in statistics introduce at an early stage the key assumption of “random sampling”. In more technical language, the data set is assumed to be identically and independently distributed (i.i.d.). In this framework a range of simple and elegant results can be derived, for example, that the variance of the mean of n observations is 1/n times the variance of the ob...

Wireless Monitoring Techniques for Structural Health Monitoring

Recently, a variety of wireless structural health monitoring systems have been demonstrated as viable substitutes for traditional high-cost tethered monitoring systems. In this study, a prototype wireless sensing system is deployed on the Voigt Bridge (La Jolla, CA) and a historical theatre (Detroit, MI) to validate its performance against cabled monitoring systems. Acceleration time history re...