A Review on Existing Sensors and Devices for Inspecting Railway Infrastructure

This paper presents a review of sensors and inspection devices employed to inspect railway defects and track geometry irregularities. Inspection of rail defects is an important task in railway infrastructure management systems, and data derived from inspections can feed railway degradation prediction models. These models are utilised for predicting potential defects and implementing preventive maintenance activities. In this paper, different sensors for detecting rail defects and track irregularities are presented, and various inspection devices which utilise these sensors are investigated. In addition, the classification of the sensors and inspection devices based on their capabilities and specifications is carried out, which has not been fully addressed in previous studies. Non-Destructive Testing (NDT) sensors, cameras and accelerometers are among sensors investigated here. Correspondingly, trolleys, Condition Monitoring Systems (CMS), hi-rail vehicles and Track Recording Vehicles (TRV) are among major inspection devices that their capabilities are studied. Furthermore, the application of new devices, including smartphones and drones, in railway inspection and their potential capabilities are discussed. The review of previous and recent approaches shows that CMSs are more cost-effective and accessible than other railway inspection methods, as they can be carried out on in-service vehicles an unlimited number of times without disruption to normal train traffic. In addition, recently smartphones as a compact inspection device with a variety of sensors are employed to measure acceleration data, which can be considered as an indicator of rail track condition.

[1]  Georges Kouroussis,et al.  Railway structure monitoring solutions using fibre Bragg grating sensors , 2016 .

[2]  M Ph Papaelias,et al.  A review on non-destructive evaluation of rails: State-of-the-art and future development , 2008 .

[3]  Danijela Jurić Kaćunić,et al.  Application of Unmanned Aerial System (UAS) in railway infrastructure , 2016 .

[4]  Gui Yun Tian,et al.  3D magnetic field sensing for magnetic flux leakage defect characterisation , 2006 .

[5]  Ferruccio Resta,et al.  Condition Monitoring of the Railway Line and Overhead Equipment Through Onboard Train Measurement - An Italian Experience , 2006 .

[6]  Amir Golroo,et al.  Turnout Degradation Modelling Using New Inspection Technologies: A Literature Review , 2016 .

[7]  R. C. Leedham,et al.  Hot bearing detection with the 'SMART-BOLT' , 1990, ASME/IEEE Joint Conference on Railroads.

[9]  Mark Evans,et al.  The inspection of level crossing rails using guided waves , 2018, Construction and Building Materials.

[10]  R. Dekker,et al.  Predicting rail geometry deterioration by regression models , 2012 .

[11]  Robin Clark,et al.  Rail flaw detection: overview and needs for future developments , 2004 .

[12]  Luis Amador-Jimenez,et al.  A comfort index for public transportation: Case study of Montreal , 2016, 2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE).

[13]  Francesco Corman,et al.  Condition monitoring approaches for the detection of railway wheel defects , 2017 .

[14]  Shahid Kabir Assessment and Monitoring for Railway Tracks Reliability and Safety using NondestructiveTesting Measurement Systems , 2015 .

[15]  Gerald B. Anderson Acoustic Detection of Distressed Freight Car Roller Bearings , 2007 .

[16]  Jianyue Zhu,et al.  Recent developments in the prediction and control of aerodynamic noise from high-speed trains , 2015 .

[17]  Vassilios Kappatos,et al.  The application of long range ultrasonic testing (LRUT) for examination of hard to access areas on railway tracks , 2011 .

[18]  N. Tandon,et al.  A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings , 1999 .

[19]  Wing Kong Chiu,et al.  Structural Health Monitoring in the Railway Industry: A Review , 2005 .

[20]  Sakdirat Kaewunruen,et al.  RideComfort: A Development of Crowdsourcing Smartphones in Measuring Train Ride Quality , 2017, Front. Built Environ..

[21]  Liu Feng,et al.  Urban rail track condition monitoring based on in-service vehicle acceleration measurements , 2016 .

[22]  Qing He,et al.  Predicting failure times of railcar wheels and trucks by using wayside detector signals , 2014, 2014 IEEE International Conference on Mechatronics and Automation.

[23]  Kenneth Gavin,et al.  A New Methodology for Assessment of Railway Infrastructure Condition , 2016 .

[24]  Archana Singh,et al.  Vision based rail track extraction and monitoring through drone imagery , 2017, ICT Express.

[26]  Sato Yasuhiro,et al.  Development of Compact Size Onboard Device for Condition Monitoring of Railway Tracks , 2013 .

[27]  Mahdi Safa,et al.  Rail corrosion forensics using 3D imaging and finite element analysis , 2015 .

[28]  Zili Li,et al.  Axle box acceleration: Measurement and simulation for detection of short track defects , 2011 .

[29]  M. Bevilacqua,et al.  Precise Vehicle Location as a Fundamental Parameter for Intelligent Self-aware Rail-track Maintenance Systems☆ , 2014 .

[30]  Andrew Ball,et al.  Modern techniques for condition monitoring of railway vehicle dynamics , 2012 .

[31]  Péter Gáspár,et al.  Smartphone Application for Assessing Various Aspects of Urban Public Transport , 2014 .

[32]  Peng Dai,et al.  A cyber-enabled visual inspection system for rail corrugation , 2018, Future Gener. Comput. Syst..

[33]  Levente Tamas,et al.  Railway track following with the AR.Drone using vanishing point detection , 2014, 2014 IEEE International Conference on Automation, Quality and Testing, Robotics.

[34]  Tomas Lidén Railway Infrastructure Maintenance - A Survey of Planning Problems and Conducted Research , 2015 .

[35]  Yi Liu,et al.  A Railway Track Geometry Measuring Trolley System Based on Aided INS , 2018, Sensors.

[36]  Andreas Engstrand,et al.  Railway surveying - A case study of the GRP 5000 , 2011 .

[37]  Michael N. Grussing,et al.  Beyond mandated track safety inspections using a mission-focused, knowledge-based approach , 2013 .

[38]  Gui Yun Tian,et al.  Multiple cracks detection and visualization using magnetic flux leakage and eddy current pulsed thermography , 2015 .

[39]  Andrea Collina,et al.  A measurement system for quick rail inspection and effective track maintenance strategy , 2007 .

[40]  Rama Chellappa,et al.  Deep Multitask Learning for Railway Track Inspection , 2015, IEEE Transactions on Intelligent Transportation Systems.