Novel event identification for SHM systems using unsupervised neural computation

Loren Card; Dean K. McNeill

doi:10.1117/12.548114

20 July 2004 Novel event identification for SHM systems using unsupervised neural computation

Loren Card, Dean K. McNeill

Proceedings Volume 5393, Nondestructive Evaluation and Health Monitoring of Aerospace Materials and Composites III; (2004) https://doi.org/10.1117/12.548114
Event: NDE for Health Monitoring and Diagnostics, 2004, San Diego, CA, United States

Abstract

This paper explores the use of unsupervised neural networks and frequency sensitive competitive learning for novel event identification in structural health monitoring (SHM) systems. Our approach assigns a novelty metric based upon the output states of an SHM system. The technique can be applied in data decimation schemes, to enhance the monitoring of such systems, and as an aide to SHM data analysis. Learning units provide a means of characterizing an SHM system, and are subsequently used to assign a novelty metric to new SHM data. The system has been evaluated using data from the Taylor Bridge and Golden Boy statue in Winnipeg, Canada and the Portage Creek bridge in Victoria, Canada. The system is capable of analyzing SHM data from a 14-channel system, recording data at 32 Hz, using 32 learning units at approximately 30 times real-time on an AMD AthlonXP 2500+ based computer. The event identification system is most sensitive to SHM data which exhibits unusual power spectra, including data which shows abrupt changes in sensor outputs. The system may be cascaded in order to perform basic classification of events after identification.

Citation Download Citation

Loren Card and Dean K. McNeill "Novel event identification for SHM systems using unsupervised neural computation", Proc. SPIE 5393, Nondestructive Evaluation and Health Monitoring of Aerospace Materials and Composites III, (20 July 2004); https://doi.org/10.1117/12.548114

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Structural health monitoring

Sensors

System identification

Bridges

Computing systems

Neural networks

Data modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years