Please use this identifier to cite or link to this item:
Title: Fault detection and isolation using neural networks in structural dynamic systems
Authors: Pandian Thirupura Sundari
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies
Issue Date: 2006
Abstract: In general, there is a possibility of degradation in stiffness due to environmental loadings such as earthquakes, for multi-storey steel frame structures, which are designed with enough stiffness and strength. Study on the identification of failure of such systems and taking corrective actions will go a long way in improving the safety of the systems. In this dissertation, the above structural dynamic system represented by a spring mass damper system (two masses) is considered here for the ease and understanding of solving this problem.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
  Restricted Access
5.6 MBAdobe PDFView/Open

Page view(s) 50

Updated on Dec 4, 2020


Updated on Dec 4, 2020

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.