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Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai

Abstract

The method to obtain a joint stiffness value from displacements of jointed part using hierarchical neural networks in case of a jointed part composed of two beams were proposed. First, the sample data of displacements of jointed part vs. joint stiffness are prepared as learned data. Second, the relations between displacements of jointed part and joint stiffness are constructed from these learned data using a hierarchical neural networks. It was found that the value of joint stiffness can be obtained from displacement of jointed part by the trained neural network. 4 refs., 9 figs., 2 tabs.
Authors:
Okabe, A; Tomioka, N [1] 
  1. Nihon University, Tokyo (Japan)
Publication Date:
Oct 01, 1997
Product Type:
Conference
Report Number:
ETDE/JP-98753688; CONF-9710216-
Reference Number:
SCA: 330600; 990200; PA: JP-98:0G1176; EDB-98:074095; SN: 98001948840
Resource Relation:
Conference: 1997 Fall Japan Society of Automotive Engineers (JSAE) meeting science lecture, JSAE 1997 nen shuki taikai gakujutsu koenkai, Hiroshima (Japan), 21-23 Oct 1997; Other Information: PBD: 1 Oct 1997; Related Information: Is Part Of Preprint of the Fall 1997 JSAE (Japan Society of Automotive Engineers) Meeting Science Lecture. No. 974; PB: 264 p.; Jidosha gijutsukai 1997 nen shuki taikai gakujutsu koenkai maezurishu. 974
Subject:
33 ADVANCED PROPULSION SYSTEMS; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; MECHANICAL STRUCTURES; NEURAL NETWORKS; VEHICLES; JOINTS; NUMERICAL ANALYSIS; MECHANICAL PROPERTIES; IDENTIFICATION SYSTEMS; ROTATION
OSTI ID:
625199
Research Organizations:
Society of Automotive Engineers of Japan, Tokyo (Japan)
Country of Origin:
Japan
Language:
Japanese
Other Identifying Numbers:
Other: ON: DE98753688; TRN: JN98G1176
Availability:
Available from Society of Automotive Engineers of Japan Inc., Gobancho 10-2, Chiyoda-ku, Tokyo, (Japan); OSTI as DE98753688
Submitting Site:
NEDO
Size:
pp. 197-200
Announcement Date:

Citation Formats

Okabe, A, and Tomioka, N. Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai. Japan: N. p., 1997. Web.
Okabe, A, & Tomioka, N. Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai. Japan.
Okabe, A, and Tomioka, N. 1997. "Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai." Japan.
@misc{etde_625199,
title = {Joint stiffness identification of body structure using neural network. Jointed part composed of 2 beams; Neural network ni yoru shatai kozo no ketsugo gosei dotei. Buzai 2 hon kara naru ketsugobu no baai}
author = {Okabe, A, and Tomioka, N}
abstractNote = {The method to obtain a joint stiffness value from displacements of jointed part using hierarchical neural networks in case of a jointed part composed of two beams were proposed. First, the sample data of displacements of jointed part vs. joint stiffness are prepared as learned data. Second, the relations between displacements of jointed part and joint stiffness are constructed from these learned data using a hierarchical neural networks. It was found that the value of joint stiffness can be obtained from displacement of jointed part by the trained neural network. 4 refs., 9 figs., 2 tabs.}
place = {Japan}
year = {1997}
month = {Oct}
}