标题: 类神经网路及振动讯号在结构破坏检测之应用
The Application of Neural Networks and Vibration Signal in Examining Structure Damage
作者: 夏韵玲
Yunn-Ling Shia
郑复平
Fu-Ping Chen
土木工程学系
关键字: 类神经网路、振动、破坏;Neural Networks、Vibration、Damage
公开日期: 1993
摘要: 结构物设计及施工完成后,常因许多原因而导致结构物发生破坏,当结构发
生破坏时,如果有适当的检测设备,检验出其破坏,并发出警讯,可使工作人
员作适当的补强与修护,以减少结构之损害,达到预防胜于治疗的目的。本
文主要是以含裂缝之金属杆件进行模态振动实验,将量测到的时域讯号转
换为频域讯号,并将讯号做特征化处理,以类神经网路建立金属杆件受损型
式 (位置.深度) 与振动讯号之关连性,而后一旦获取未知受损金属杆件之
振动讯号时,即可藉类神经网路做杆件之裂缝位置及受损程度之判别,以
此建立受损结构之整体诊断架构。
The structures are damaged, due to its enviromental chang and
overloading, after their completion. If they are maintained
properly with routingly examination and repairation, eir
service life will be extened. This research ultilized the modal
testing of cracked steel beam to explore the vibrational
characteristics of the crackedeam. The time domain signal was
transformed into frequencymain by FFT. These data were used to
setup a diagnose theition and depth of the cracked structure
from its vibrational signal.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT820015013
http://hdl.handle.net/11536/57528
显示于类别:Thesis