scholarly journals A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives

2018 ◽  
Vol 8 (12) ◽  
pp. 2475 ◽  
Author(s):  
Fernando Garramiola ◽  
Javier Poza ◽  
Patxi Madina ◽  
Jon del Olmo ◽  
Gaizka Almandoz
Keyword(s):  
Fault Diagnosis ◽  
Health Assessment ◽  
Condition Based Maintenance ◽  
System Availability ◽  
Railway Systems ◽  
Railway Industry ◽  
Railway Traction ◽  
Railway System ◽  
Traction Drives ◽  
Early Fault Detection

During the last decade, due to the increasing importance of reliability and availability, railway industry is making greater use of fault diagnosis approaches for early fault detection, as well as Condition-based maintenance frameworks. Due to the influence of traction drive in the railway system availability, several research works have been focused on Fault Diagnosis for Railway traction drives. Fault diagnosis approaches have been applied to electric machines, sensors and power electronics. Furthermore, Condition-based maintenance framework seems to reduce corrective and Time-based maintenance works in Railway Systems. However, there is not any publication that summarizes all the research works carried out in Fault diagnosis and Condition-based Maintenance frameworks for Railway Traction Drives. Thus, this review presents the development of Health Assessment and Fault Diagnosis in Railway Traction Drives during the last decade.

scholarly journals Corporate sustainability and customer loyalty: the case of the railway industry

2016 ◽  
Vol 13 (3) ◽  
pp. 445-455 ◽  
Author(s):  
Elizabeth Chinomona ◽  
Chengedzai Mafini ◽  
Chriss Narick Mangoukou Ngouapegne
Keyword(s):  
South Africa ◽  
South African ◽  
Corporate Sustainability ◽  
Rapid Transit ◽  
The South ◽  
Gauteng Province ◽  
Railway Systems ◽  
Railway Industry ◽  
Railway System ◽  
Mass Rapid Transit

Introduction of the mass rapid transit railway system through the Gautrain has not only addressed the transport issue in South Africa but has also motivated and promoted the country’s economic growth by creating employment. Despite the increase in research focusing on the importance of the Gautrain to the South African economy, the influence of perceived convenience, image and safety on commuter satisfaction and loyalty in the South African mass rapid transit railway system context is still limited. This paper used a data collected from 206 Gautrain commuters in the Gauteng province of South Africa to examine the interplay between perceived convenience, image, safety, commuter satisfaction and loyalty. Smart PLS software technique was used to statistically analyse the measurement and structural models. The results revealed that perceived convenience, image and safety positively influenced commuter satisfaction, which, in turn, influenced commuter loyalty. These results may be used by marketers in mass public railway systems to initiate strategies intended to increase both commuter satisfaction and loyalty

scholarly journals THE IMPACT OF INNOVATIVE TECHNOLOGIES ON THE EFFICIENCY OF RAILWAY SYSTEM MANAGEMENT

2021 ◽  
pp. 68-75
Author(s):  
Irina Sabirova ◽  
◽  
Keyword(s):  
Transport Systems ◽  
System Management ◽  
Systems Management ◽  
Management Tools ◽  
Innovative Technologies ◽  
Intelligent Transport ◽  
Railway Systems ◽  
Railway Industry ◽  
Railway System ◽  
The Impact

The article discusses the issues of introducing innovative technologies into the railway management system. The object of the study is the efficiency of management of railway systems. The subject of the research is innovative technologies and their impact on the effectiveness of railway systems management. The purpose of the work is to conduct a theoretical analysis of the impact of innovations on the efficiency of railway systems management and, using the example of large foreign railway systems, to determine the main factors of innovation efficiency. The scientific novelty of the presented work lies in the analysis of foreign experience in the development of effective management tools for railway systems in the context of innovation. The paper concludes that the future of the railway industry directly depends on the degree of its digitalization and technologization, the introduction of intelligent transport systems and active integration into the global space of innovative development.

scholarly journals A Hybrid Sensor Fault Diagnosis for Maintenance in Railway Traction Drives

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 962 ◽  
Author(s):  
Fernando Garramiola ◽  
Javier Poza ◽  
Patxi Madina ◽  
Jon del Olmo ◽  
Gaizka Ugalde
Keyword(s):  
Fault Diagnosis ◽  
Time Window ◽  
Sliding Mode ◽  
Fault Detection And Isolation ◽  
Fault Classification ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Fault Reconstruction ◽  
Railway Traction ◽  
Traction Drives

Due to the importance of sensors in railway traction drives availability, sensor fault diagnosis has become a key point in order to move from preventive maintenance to condition-based maintenance. Most research works are limited to sensor fault detection and isolation, but only a few of them analyze the types of sensor faults, such as offset or gain, with the aim of reconfiguring the sensor in order to implement a fault tolerant system. This article is based on a fusion of model-based and data-driven techniques. First, an observer-based approach, using a Sliding Mode observer, is utilized for sensor fault reconstruction in real time. Then, once the fault is detected, a time window of sensor measurements and sensor fault reconstruction is sent to the remote maintenance center for fault evaluation. Finally, an offline processing is carried out to discriminate between gain and offset sensor faults, in order to get a maintenance decision-making to reconfigure the sensor during the next train stop. Fault classification is done by means of histograms and statistics. The technique here proposed is applied to the DC-link voltage sensor in a railway traction drive and is validated in a hardware-in-the-loop platform.

An Improved Torque and Current Pulsation Suppression Method for Railway Traction Drives Under Fluctuating DC-Link Voltage

2018 ◽  
Vol 33 (10) ◽  
pp. 8565-8577 ◽  
Author(s):  
Yanxiao Lei ◽  
Ke Wang ◽  
Lu Zhao ◽  
Qiongxuan Ge ◽  
Zixin Li ◽  
...  
Keyword(s):  
Railway Traction ◽  
Suppression Method ◽  
Traction Drives ◽  
Current Pulsation

scholarly journals Intelligent Fault Diagnosis of Synchromesh Gearbox Using Fusion of Vibration and Acoustic Emission Signals for Performance Enhancement

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
T Praveenkumar ◽  
M Saimurugan ◽  
K I Ramachandran
Keyword(s):  
Support Vector Machine ◽  
Acoustic Emission ◽  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Support Vector ◽  
Feature Level Fusion ◽  
Sensor Signals ◽  
Early Fault Detection ◽  
Ae Signals ◽  
Level Fusion

Condition monitoring system monitors the system degradation and it identifies common failure modes. Several sensor signals are available for monitoring the changes in system components. Vibration signal is one of the most extensively used technique for monitoring rotating components as it identifies faults before the system fails. Early fault detection is the significant factor for condition monitoring, where Acoustic Emission ( AE ) sensor signals have been applied for early fault detection due to their high sensitivity and high frequency. In this paper, vibration and acoustic emission signals are acquired under various simulated gear and bearing fault conditions from the synchromesh gearbox. Then the statistical features are extracted from vibration and AE signals and then the prominent features are selected using J48 decision tree algorithm respectively. The best features from the vibration and AE signals are then fused using feature-level fusion strategy and it is classified using Support Vector Machine ( SVM ) and Proximal Support Vector Machine ( PSVM ) classifiers and it is compared with individual signals for fault diagnosis of the synchromesh gearbox. From the experiments, it is observed that the performance of the fault diagnosis system has been improved for the proposed feature level fusion technique compared to the performance of unfused vibration and AE feature sets.

scholarly journals Vestas V90-3MW Wind Turbine Gearbox Health Assessment Using a Vibration-Based Condition Monitoring System

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
A. Romero ◽  
Y. Lage ◽  
S. Soua ◽  
B. Wang ◽  
T.-H. Gan
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Condition Monitoring ◽  
Learning Algorithm ◽  
Health Assessment ◽  
Field Trials ◽  
Health Condition ◽  
Normal Operation ◽  
Wind Turbine Gearbox ◽  
Operation Conditions

Reliable monitoring for the early fault diagnosis of gearbox faults is of great concern for the wind industry. This paper presents a novel approach for health condition monitoring (CM) and fault diagnosis in wind turbine gearboxes using vibration analysis. This methodology is based on a machine learning algorithm that generates a baseline for the identification of deviations from the normal operation conditions of the turbine and the intrinsic characteristic-scale decomposition (ICD) method for fault type recognition. Outliers picked up during the baseline stage are decomposed by the ICD method to obtain the product components which reveal the fault information. The new methodology proposed for gear and bearing defect identification was validated by laboratory and field trials, comparing well with the methods reviewed in the literature.

Software-Based Self-Test for Reliable Applications in Railway Systems

2012 ◽  
pp. 198-220 ◽  
Author(s):  
Alfredo Benso ◽  
Stefano Di Carlo ◽  
Alessandro Savino
Keyword(s):  
Test Solution ◽  
Test Coverage ◽  
High Quality ◽  
Basic Principles ◽  
Safety Standards ◽  
Railway Systems ◽  
Railway System ◽  
On Line ◽  
Self Test

The very strict safety standards, which must be guaranteed in a railway system, make the testing of all electronic components a unique and challenging case study. Software-based self-test represents a very attractive test solution to cope with the problem of on-line and off-line testing of microprocessor-based systems. It makes it possible to deeply test hardware components without introducing extra hardware and stressing the system in its operational condition. This chapter overviews the basic principles of software-based self-test techniques, focusing on a set of best practices to be applied in writing, verifying and computing the final test coverage of high-quality test programs for railway systems.

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