Deep Learning-Based Damage, Load and Support Identification for a Composite Pipeline by Extracting Modal Macro Strains from Dynamic Excitations

Deep Learning-Based Damage, Load and Support Identification for a Composite Pipeline by Extracting Modal Macro Strains from Dynamic Excitations

Modal macro strain-based damage identification is a promising approach since it has the advantages of high sensitivity and effectiveness over other related methods. In this paper, a basalt fiber-reinforced polymer (BFRP) pipeline system is used for analysis by using long-gauge distributed fiber Brag...

Full description

Bibliographic Details
Main Authors: Ying Zhao, Mohammad Noori, Wael A. Altabey, Ramin Ghiasi, Zhishen Wu
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Applied Sciences
Subjects:
modal macro strain
fiber-reinforced polymer (FRP) composite pipeline
damage
load
support identification
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/2076-3417/8/12/2564

Internet

https://www.mdpi.com/2076-3417/8/12/2564

Similar Items