Investigation of Inverse Analysis and Neural Network Approaches for Identifying Distributed Load using Distributed Strains-Reference-Cited by-同舟云学术

Investigation of Inverse Analysis and Neural Network Approaches for Identifying Distributed Load using Distributed Strains

Published:2019 Issue:3 Volume:62 Page:151-161
ISSN:0549-3811
Container-title:TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
language:en
Short-container-title:Trans. Japan Soc. Aero. S Sci.

Author:

WADA Daichi¹,SUGIMOTO Yohei²,MURAYAMA Hideaki³,IGAWA Hirotaka¹,NAKAMURA Toshiya¹

Affiliation:

1. Aeronautical Technology Directorate, Japan Aerospace Exploration Agency

2. Research and Development Directorate, Japan Aerospace Exploration Agency

3. Graduate School of Frontier Sciences, The University of Tokyo

Publisher

Japan Society for Aeronautical and Space Sciences

Subject

Space and Planetary Science,Aerospace Engineering

Link

https://www.jstage.jst.go.jp/article/tjsass/62/3/62_T-18-30/_pdf

Reference26 articles.

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2. 2) Molent, L. and Aktepe, B.: Review of Fatigue Monitoring of Agile Military Aircraft, Fatigue Fract. Eng. Mater. Struct., 23 (2000), pp. 767–785.

3. 3) Farrar, C. R. and Worden, K.: An Introduction to Structural Health Monitoring, Phil. Trans. R. Soc. A, 365 (2007), pp. 303–315.

4. 4) Molent, L. and Inan, S.: Specifications for an Unified Strain and Flight Parameter Based Aircraft Fatigue Usage Monitoring System, DSTO International Conference on Health and Usage Monitoring, Melbourne, Australia, 2001, pp. 53–67.

5. 5) Farrar, C. R. and Lieven, N. A. J.: Damage Prognosis: the Future of Structural Health Monitoring, Phil. Trans. R. Soc. A, 365 (2007), pp. 623–632.

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