Substructure Vibration NARX Neural Network Approach for Statistical Damage Inference-Reference-Cited by-同舟云学术

Substructure Vibration NARX Neural Network Approach for Statistical Damage Inference

Published:2013-06 Issue:6 Volume:139 Page:737-747
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Yan Linjun¹,Elgamal Ahmed²,Cottrell Garrison W.³

Affiliation:

1. Project Engineer, Tobolski Watkins Engineering, 9246 Lightwave Ave., Suite 140, San Diego, CA 92123.

2. Professor, Dept. of Structural Engineering, Univ. of California-San Diego, La Jolla, CA 92093-0085 (corresponding author).

3. Professor, Dept. of Computer Science and Engineering, Univ. of California-San Diego, La Jolla, CA 92093-0404.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0000363

Reference44 articles.

1. Adams D. R. and Farrar C. R. (2002). “Application of frequency domain ARX features for linear and nonlinear structural damage identification.” Proc. Society of Photographic Instrumentation Engineers (SPIE) 9th Annual Int. Symp. on Smart Structures and Materials SPIE Bellingham WA.

2. Signal versus Noise in Damage Detection by Experimental Modal Analysis

3. Casciati F. Casciati S. and Faravelli L. (2003a). “Damage detection via response surface approximations.” Proc. Applications of Statistics and Probability in Civil Engineering (ICASP)9 Millpress Rotterdam Netherlands.

4. Casciati S. Colabrese E. and Magonette G. (2003b). “Damage detection and localization by statistical comparison of response time histories.” Proc. Int. Workshop on Structural Health Monitoring (IWSHM)4 Stanford Univ. Stanford CA.

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