Structural Damage Detection with Automatic Feature‐Extraction through Deep Learning

Volume: 32, Issue: 12, Pages: 1025 - 1046
Published: Nov 10, 2017
Abstract
Structural damage detection is still a challenging problem owing to the difficulty of extracting damage‐sensitive and noise‐robust features from structure response. This article presents a novel damage detection approach to automatically extract features from low‐level sensor data through deep learning. A deep convolutional neural network is designed to learn features and identify damage locations, leading to an excellent localization accuracy...
Paper Details
Title
Structural Damage Detection with Automatic Feature‐Extraction through Deep Learning
Published Date
Nov 10, 2017
Volume
32
Issue
12
Pages
1025 - 1046
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