Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Surface Threat Event Identification for Subway Tunnels Using Multi-classifier Fusion Algorithm Based Optical Fiber DAS System

Not Accessible

Your library or personal account may give you access

Abstract

Multi-classifier fusion algorithm is proposed to identify surface intrusion events in the subway tunnel. Experimental demonstration verifies that the average recognition rate of 96.1% for four target events is achieved by the proposed scheme.

© 2023 The Author(s)

PDF Article
More Like This
Optical Fiber Subway Intrusion Monitoring using the entropy of the wavelet packet coefficients and wavelet multi-scale ridge detection

Minggan Lou, Wenzhu Huang, Fang Li, and Wentao Zhang
Th6.40 Optical Fiber Sensors (OFS) 2023

Subway tunnel intrusion detection based on fiber optic seismic sensor array

Wentao Zhang, Jiantao Huang, Wenzhu Huang, Gaoran Guo, Fang Li, and Yanliang Du
JTh2A.32 Fourier Transform Spectroscopy (FTS) 2019

An intrusion events recognition method by incremental learning assisted with fiber optic DAS system

Shixiong Zhang, Tao He, Kai xiao, Cunzheng Fan, Hao Li, Zhijun Yan, Deming Liu, and Qizhen Sun
JW3A.22 CLEO: Applications and Technology (CLEO:A&T) 2022

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.