Substructure Vibration NARX Neural Network Approach for Statistical Damage Inference

A damage detection approach is developed using nonlinear autoregressive with exogenous inputs (NARX) neural networks and a statistical inference technique. Within a large spatially extended dynamic system, an instrumented local substructure may be represented by a neural network, to predict the dynamic response of a given sensor from that of its neighbors. Without change in the system properties, the network prediction error will follow a stable statistical distribution. To infer damage, change in the prediction error variance as evaluated by the statistical inference standard F test is utilized as a sensitive indicator. Validation of the described procedure is undertaken using two experimental data sets (from the Los Alamos National Laboratory in Los Alamos, NM). Reduced stiffness and nonlinear response of a mass-spring system is documented in the first set, while joint damage in a frame structure is explored in the second. Favorable results are obtained in both cases with linear/nonlinear and single/multidamage patterns. Overall, the proposed framework may be particularly efficient for large spatially extended sensor network situations, where local condition assessment may be conducted based on the response of a few neighboring sensors.

• Record URL:
  https://doi.org/10.1061/(ASCE)EM.1943-7889.0000363
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/07339399
• Supplemental Notes:
  • Copyright © 2013 American Society of Civil Engineers
• Authors:
  • Yan, Linjun
  • Elgamal, Ahmed
  • Cottrell, Garrison W
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Digital/other
• Features: References;
• Pagination: pp 737-747
• Serial:
  • Journal of Engineering Mechanics
  • Volume: 139
  • Issue Number: 6
  • Publisher: American Society of Civil Engineers
  • ISSN: 0733-9399
  • EISSN: 1943-7889
  • Serial URL: http://ascelibrary.org/journal/jenmdt

Subject/Index Terms

• TRT Terms: Neural networks; Statistical inference; Stiffness; Structural health monitoring; Substructures; Vibration
• Uncontrolled Terms: Damage detection
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation; I60: Maintenance;

Filing Info

• Accession Number: 01482059
• Record Type: Publication
• Files: TRIS, ASCE
• Created Date: May 9 2013 11:27AM