Statistical Damage Classification Using Sequential Probability Ratio Tests

By Hoon Sohn, D. Allen, Keith Worden, Charles R. Farrar. 2002

83 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/297aa45bb14a32d4b51e1339d227596c555fe69e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Fotis P. Kopsaftopoulos
2. Spilios D. Fassois
3. Ahmed Elgamal
4. Linjun Yan
5. Garrison W. Cottrell

In Mechanics of Materials

1. Ahmed Elgamal
2. Spilios D. Fassois
3. Fotis P. Kopsaftopoulos
4. Linjun Yan
5. Garrison W. Cottrell

Citations in the corpus

• Substructure Vibration NARX Neural Network Approach for Statistical Damage Inference (2013, methodology): “Experimental setup of the 3-story frame model [Sohn et al. 2003b; Sohn, H., Allen, D. W., Worden, K., and Farrar, C. R., Structural Health Monitoring (Vol. 2, Issue 1), pp. 57–74, copyright © 2003 by Sage Publications, Reprinted by Permission of SAGE] JOURNAL OF ENGINEERING MECHANICS © ASCE / JUNE…”
• Vibration based health monitoring for a lightweight truss structure: experimental assessment of several statistical time series methods (2010, methodology): “[17, 18] use the prediction errors of a so–called AutoRegressive and AutoRegressive with eXogenous inputs (AR– ARX) model, a sequential hypothesis testing technique (sequential probability ratio test), and extreme value statistics for damage diagnosis.”