Intelligent condition monitoring of railway catenary systems: A Bayesian Network approach

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...

Multi-Objective Performance Evaluation of the Detection of Catenary Support Components Using DCNNs

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...

Identification of the catenary structure wavelength using pantograph head acceleration measurements

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...

Action-driven Reinforcement Learning for Improving Localization of Brace Sleeve in Railway Catenary

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...

Virtual Reality and Convolutional Neural Networks for Railway Catenary Support Components Monitoring

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...

Entropy-Based Local Irregularity Detection for High-Speed Railway Catenaries With Frequent Inspections

The condition-based maintenance of high-speed railway catenary is an important task to ensure the continuous availability of train power supply. To improve the condition monitoring of catenary, this paper presents a novel scheme to detect catenary local irregularities using pantograph head acceleration measurements. First, a series of...

A Looseness Detection Method for Railway Catenary Fasteners based on Reinforcement Learning Refined Localization

Brace sleeve (BS) fasteners, i.e., nut and bolt, are small components but play essential roles in fixing BS and cantilever in railway catenary system. They are commonly inspected by onboard cameras using computer vision to ensure the safety of railway operation. However, most BS fasteners cannot be directly localized because they are too...

High-Precision Detection Method for Structure Parameters of Catenary Cantilever Devices using 3D Point Cloud Data

This article proposes an automatic high-precision detection method for structure parameters of catenary cantilever devices (SPCCDs) using 3-D point cloud data. The steps of the proposed detection method are: 1) segmenting and recognizing the components of the catenary cantilever devices, 2) extracting the detection plane and backbone...

Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary support device is of great significance for...

Ensemble EMD-based automatic extraction of the catenary structure wavelength from the pantograph-catenary contact corce

This paper explores the use of pantograph-catenary contact force (PCCF) for monitoring of the current collection quality and detection of anomalies in the interaction between pantograph and catenary. The concept of catenary structure wavelength (CSW) is proposed as the dominant component of PCCF. It describes the signal components caused by the...

Multi-criteria evaluation of wheel/rail degradation at railway crossings

This study evaluates the degradation of wheels and rails at railway crossings. The evaluation method is composed of 1) finite element simulation of dynamic wheel/crossing interaction and 2) multi-criteria analysis of wheel/rail degradation in terms of yield behavior, rolling contact fatigue (RCF) and wear. With the aid of this method, we...

Unified deep learning architecture for the detection of all catenary support components

With the rapid development of deep learning technologies, researchers have begun to utilize convolutional neural network (CNN)-based object detection methods to detect multiple catenary support components (CSCs). The literature has focused on the detection of specified large-scale CSCs. Additionally, CNN architectures have faced difficulties in...

A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries

The growing variety of data from condition monitoring of high-speed railways offer unprecedented opportunities to improve railway infrastructure maintenance. For condition monitoring of railway catenaries, this paper proposes a data-driven approach that uses a Bayesian network (BN) to integrate the inspection data from catenaries into a key...

Analysis of the evolvement of contact wire wear irregularity in railway catenary based on historical data

This paper studies the evolvement of the wear irregularity of contact wire using wire thickness data measured yearly from a section of railway catenary. The power spectral density and time–frequency representation based on the wavelet transform are employed for data analysis, with an emphasis on local wear irregularities that are crucial for...