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Zhong, J. (author), Liu, Zhigang (author), Wang, H. (author), Liu, W. (author), Yang, Cheng (author), Nunez, Alfredo (author)
Brace Sleeve (BS) plays an essential role in connecting and fixing cantilevers of railway catenary systems. It needs to be monitored to ensure the safety of railway operations. In the literature, image processing techniques that can localize BSs from inspection images are proposed. However, the boxes produced by existing methods can contain...
conference paper 2020
document
Liu, Wenqiang (author), Liu, Zhigang (author), Nunez, Alfredo (author)
The development of algorithms for detecting failures in railway catenary support components has, among others, one major challenge: data about healthy components are much more abundant than data about defective components. In this paper, virtual reality technology is employed to control the learning environment of convolutional neural...
conference paper 2019
document
Liu, W. (author), Liu, Zhigang (author), Nunez, Alfredo (author), Wang, Liyou (author), Liu, Kai (author), Lyu, Yang (author), Wang, H. (author)
The goal of this paper is to evaluate from a multi-objective perspective the performance on the detection of catenary support components when using state-of-the-art deep convolutional neural networks (DCNNs). The detection of components is the first step towards a complete automatized monitoring system that will provide actual information about...
conference paper 2018
document
Wang, H. (author), Liu, Zhigang (author), Nunez, Alfredo (author), Dollevoet, R.P.B.J. (author)
For the condition monitoring of railway catenaries, the potential utilization of pantograph head (pan-head) vertical acceleration instead of pantograph-catenary contact force is discussed in this paper. In order to establish a baseline of the pan-head acceleration before it can be used for health condition monitoring, one of the essential...
conference paper 2017
document
Wang, H. (author), Nunez, Alfredo (author), Dollevoet, R.P.B.J. (author), Liu, Zhigang (author), Chen, Junwen (author)
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head vertical acceleration and pantograph-catenary contact...
conference paper 2017
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