An examination of the ARX as a residual generator for damage detection

Dionisio Bernal; Daniele Zonta; Matteo Pozzi

doi:10.1117/12.816211

10 April 2009 An examination of the ARX as a residual generator for damage detection

Dionisio Bernal, Daniele Zonta, Matteo Pozzi

Proceedings Volume 7295, Health Monitoring of Structural and Biological Systems 2009; 729521 (2009) https://doi.org/10.1117/12.816211
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2009, San Diego, California, United States

Abstract

Residuals that capture the difference between anticipated behavior and actual observations are often used to identify damage. Wanting to control the influence of unmeasured disturbances and noise in residuals, it is common to generate reference signals using feedback from measured outputs. Since there is much flexibility in the gains a wide range of models that react differently to changes are possible. This paper examines two questions: 1) how damage residuals generated by different closed loop models relate to each other and 2) how to rank the expected efficiency of alternative models. On the first question examination shows that the residuals from any model can be viewed as sums of filtered open loop residuals where the filter coefficients depend on the model structure but not on the damage. On the second item a general procedure based on Bayesian decision-making is proposed to quantify the economical benefit in adopting a specific autoregressive model.

Citation Download Citation

Dionisio Bernal, Daniele Zonta, and Matteo Pozzi "An examination of the ARX as a residual generator for damage detection", Proc. SPIE 7295, Health Monitoring of Structural and Biological Systems 2009, 729521 (10 April 2009); https://doi.org/10.1117/12.816211

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available