Review of Emerging Technologies and Issues in Rail and Track Inspection for Local Lines in the United States
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 10
Abstract
Deteriorated track infrastructure can lead to significant consequences, such as derailment incidents, loss of revenue-service hours, reduced train operation speed, and even failure of the business. The Federal Railroad Administration (FRA) requires thorough and timely rail track inspections to keep trains operating safely. Approaches using advanced and emerging technologies have become more accessible and broadened their applications. Unfortunately, for Class II (regional) and III (short line) railroads (referred to as local railroads hereafter), there are many obstacles for deployment of these advanced technologies, such as budget constraints and lack of workforce skills. Local railroads are actively seeking cost-effective and efficient approaches to replace conventional methods of manual inspection. This paper, for the first time, aims at identifying the key challenges for local railroads regarding the demand for reliable and timely rail track inspection, lack of advancement of emerging technologies, and unique constraints faced by the local railroads. Through a comprehensive review of the common rail and track geometry defects and state-of-the-art track inspection techniques, this paper critically analyzes the knowledge gaps from four key perspectives from the perspective of local railroad operation: finance, technology, standards, and operation. It is found that automated nondestructive evaluation (NDE) techniques and inexpensive alternatives to the Automated Track Inspection Program (ATIP) may still be cost-feasible and effective for local railroads with future technological and operational upgrades.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
The data and associated information to support this research appear in the published article.
Acknowledgments
The authors acknowledge support from the Mountain-Plains Consortium (MPC), a university transportation center funded by the US Department of Transportation, and North Dakota State University.
References
AAR (Association of American Railroads). 2018. “Overview of America’s freight railroads.” Accessed June 12, 2020. https://www.aar.org/wp-content/uploads/2018/08/Overview-of-Americas-Freight-RRs.pdf.
AAR (Association of American Railroads). 2019. “Railroad 101.” Accessed June 12, 2020. https://www.aar.org/wp-content/uploads/2020/08/AAR-Railroad-101-Freight-Railroads-Fact-Sheet.pdf.
Alfi, S., and S. Bruni. 2008. “Estimation of long wavelength track irregularities from on board measurement.” In Proc., 2008 4th IET Int. Conf. on Railway Condition Monitoring (RCM 2008). London: Institution of Engineering and Technology. https://doi.org/10.1049/ic:20080323.
Allen, W. B., M. Sussman, and D. Miller. 2002. “Regional and short line railroads in the United States.” Transp. Q. 56 (4): 77–113.
Artagan, S. S., L. B. Ciampoli, F. D’Amico, A. Calvi, and F. Tosti. 2020. “Non-destructive assessment and health monitoring of railway infrastructures.” Surv. Geophys. 41 (3): 447–483. https://doi.org/10.1007/s10712-019-09544-w.
Auer, F. 2013. “Multi-function track recording cars.” Rail Technol. Rev. 53 (3–4): 32–36.
Bachinsky, G. S. 1995. “Electronic BAR gauge: A customized optical rail profile measurement system for rail-grinding applications.” In Vol. 2458 of Proc., Nondestructive Evaluation of Aging Railroads, 52–63. Bellingham, WA: International Society for Optics and Photonics. https://doi.org/10.1117/12.212689.
Beger, R., C. Gedrange, R. Hecht, and M. Neubert. 2011. “Data fusion of extremely high resolution aerial imagery and LiDAR data for automated railroad centre line reconstruction.” Supplement, ISPRS J. Photogramm. Remote Sens. 66 (6): S40–S51. https://doi.org/10.1016/j.isprsjprs.2011.09.012.
Bitzan, J., D. Tolliver, and D. Benson. 2002. Small railroads: Investment needs, financial options, and public benefits. Fargo, ND: North Dakota State Univ.
BTS (Bureau of Transportation Statistics). 2016. “Chapter 1: Extent and physical condition of the US transportation system.” Accessed March 25, 2021. https://www.bts.gov/archive/publications/transportation_statistics_annual_report/2015/chapter1.
California Department of Transportation. 2018. “Terrestrial laser scanning specifications.” Accessed June 12, 2021. https://dot.ca.gov/-/media/dot-media/programs/right-of-way/documents/ls-manual/15-surveys-a11y.pdf.
Cannon, D. F., K. O. Edel, S. L. Grassie, and K. Sawley. 2003. “Rail defects: An overview.” Fatigue Fract. Eng. Mater. Struct. 26 (10): 865–886. https://doi.org/10.1046/j.1460-2695.2003.00693.x.
Carter, J., K. Schmid, K. Waters, L. Betzhold, B. Hadley, R. Mataosky, and J. Halleran. 2015. “Lidar 101: An introduction to lidar technology, data, and applications.” Accessed June 12, 2021. https://coast.noaa.gov/data/digitalcoast/pdf/lidar-101.pdf.
Census. 2017. “Economic census.” Accessed March 25, 2021. https://data.census.gov/cedsci/table?q=cf17%5C&tid=CFSPRELIM2017.CF1700P1.
Chia, L., B. Bhardwaj, R. Bridgelall, P. Lu, D. Tolliver, and N. Dhingra. 2019a. “Heuristic methods of inertial signal alignment to enhance the detection and localization accuracy of railtrack anomalies.” In Proc., Transportation Research Board 98th Annual Meeting. Washington, DC: Transportation Research Board.
Chia, L., P. Lu, B. Bhardwaj, R. Bridgelall, D. Tolliver, and N. Dhingra. 2019b. “Automatic rail track surface anomaly detection with smartphone based monitoring system.” In Proc., DEStech Transactions on Engineering and Technology Research. Lancaster, PA: DEStech Publications. https://doi.org/10.12783/dtetr/icicr2019/30565.
Chugui, Y. 2011. “Optical measuring technologies for scientific and industrial applications.” In Vol. 2 of Proc., IEEE 2011 10th Int. Conf. on Electronic Measurement and Instruments, 7–12. New York: IEEE.
CN Rail. 2010. “Industry track inspection.” Accessed June 12, 2021. https://www.cn.ca/-/media/Files/Customer-Centre/Track-Specifications/industry-track-inspection-en.pdf?la=en&hash=9A2E6CA60AD68FAF52DD0D02F9FE892C585494D.
Congress. 1981. “S.1946–96th Congress (1979–1980): Staggers Rail Act of 1980.” Accessed March 25, 2021. https://www.congress.gov/bill/96th-congress/senate-bill/1946.
De Ruvo, P., A. Distante, E. Stella, and F. Marino. 2009. “A GPU-based vision system for real time detection of fastening elements in railway inspection.” In Proc., 2009 16th IEEE Int. Conf. on Image Processing, 2333–2336. New York: IEEE.
Dey, A., J. Kurz, and L. Tenczynski. 2016. “Detection and evaluation of rail defects with non-destructive testing methods.” In Proc., 19th World Conf. on Non-Destructive Testing, 1–9. Red Hook, NY: Curran Associates.
DOD (Department of Defense). 2008. “Railroad track maintenance safety standards.” Accessed June 12, 2021. https://www.wbdg.org/FFC/DOD/UFC/ufc_4_860_03_2008.pdf.
Elberink, S. O., and K. Khoshelham. 2015. “Automatic extraction of railroad centerlines from mobile laser scanning data.” Remote Sens. 7 (5): 5565–5583. https://doi.org/10.3390/rs70505565.
El-khateeb, L. 2017. “Defect-based condition assessment model of railway infrastructure.” Ph.D. dissertation, Dept. of Civil Engineering, Concordia Univ.
Falamarzi, A., S. Moridpour, and M. Nazem. 2019. “A review on existing sensors and devices for inspecting railway infrastructure.” Jurnal Kejuruteraan 31 (1): 1–10.
Farkas, A. 2020. “Measurement of railway track geometry: A state-of-the-art review.” Period. Polytech. Transp. Eng. 48 (1): 76–88. https://doi.org/10.3311/PPtr.14145.
Ferreira, L., and M. H. Murray. 1997. “Modelling rail track deterioration and maintenance: Current practices and future needs.” Transp. Rev. 17 (3): 207–221. https://doi.org/10.1080/01441649708716982.
FHA (Federal Highway Administration). 2016. “Guide for efficient geospatial data acquisition using LiDAR surveying technology.” Accessed June 12, 2021. https://rosap.ntl.bts.gov/view/dot/42716.
Fitzgerald, C. S. 1995. “Inspection for rail defects by magnetic induction.” In Vol. 2458 of Proc., Nondestructive Evaluation of Aging Railroads, 40–44. Bellingham, WA: International Society for Optics and Photonics. https://doi.org/10.1117/12.212672.
FRA (Federal Railroad Administration). 2008. “Track safety standards compliance manual.” Accessed June 12, 2021. https://railroads.dot.gov/sites/fra.dot.gov/files/2020-08/2008_Track_Safety_Standards%20%281%29.pdf.
FRA (Federal Railroad Administration). 2014. “Summary of Class II and Class III railroad capital needs and funding sources.” Accessed June 12, 2021. https://www.infrastructurereportcard.org/wp-content/uploads/2017/05/C1-140212-001_D1-FRA-Report-on-RRs-Report-9-30.pdf.
FRA (Federal Railroad Administration). 2015. “Track inspector rail defect reference manual.” Accessed March 25, 2021. https://railroads.dot.gov/elibrary/track-inspector-rail-defect-reference-manual.
FRA (Federal Railroad Administration). 2018a. “Autonomous track geometry measurement system: Technical development & short line demonstration.” Accessed March 25, 2021. https://railroads.dot.gov/elibrary/autonomous-track-geometry-measurement-system-technical-development-short-line.
FRA (Federal Railroad Administration). 2018b. “Track and rail and infrastructure integrity compliance manual: Volume I. Chapter 2: Field reporting procedures and forms.” Accessed March 25, 2021. https://railroads.dot.gov/elibrary/track-and-rail-and-infrastructure-integrity-compliance-manual-volume-i-chapter-2-field-1.
FRA (Federal Railroad Administration). 2019. “History of ATIP.” Accessed February 11, 2021. https://cms8.fra.dot.gov/track/automated-track-inspection-program-atip/history-atip.
FRA (Federal Railroad Administration). 2020a. “Freight rail overview.” Accessed March 25, 2021. https://railroads.dot.gov/rail-network-development/freight-rail-overview.
FRA (Federal Railroad Administration). 2020b. “Ten year accident/incident overview.” Accessed March 25, 2021. https://safetydata.fra.dot.gov/OfficeofSafety/publicsite/Query/TenYearAccidentIncidentOverview.aspx.
Gan, J., Q. Li, J. Wang, and H. Yu. 2017. “A hierarchical extractor-based visual rail surface inspection system.” IEEE Sens. J. 17 (23): 7935–7944. https://doi.org/10.1109/JSEN.2017.2761858.
Gargoum, S. A., and K. El Basyouny. 2019. “A literature synthesis of LiDAR applications in transportation: Feature extraction and geometric assessments of highways.” GISci. Remote Sens. 56 (6): 864–893. https://doi.org/10.1080/15481603.2019.1581475.
Gibert, X., V. M. Patel, and R. Chellappa. 2015. “Robust fastener detection for autonomous visual railway track inspection.” In Proc., 2015 IEEE Winter Conf. on Applications of Computer Vision, 694–701. New York: IEEE.
Gikas, V., and J. Stratakos. 2011. “A novel geodetic engineering method for accurate and automated road/railway centerline geometry extraction based on the bearing diagram and fractal behavior.” IEEE Trans. Intell. Transp. Syst. 13 (1): 115–126. https://doi.org/10.1109/TITS.2011.2163186.
Grassie, S. L. 1996. “Short wavelength rail corrugation: Field trials and measuring technology.” Wear 191 (1–2): 149–160. https://doi.org/10.1016/0043-1648(95)06755-8.
Grassie, S. L. 2005. “Rail corrugation: Advances in measurement, understanding and treatment.” Wear 258 (7–8): 1224–1234. https://doi.org/10.1016/j.wear.2004.03.066.
Heckel, T., H. M. Thomas, M. Kreutzbruck, and S. Rühe. 2009. “High speed non-destructive rail testing with advanced ultrasound and eddy-current testing techniques.” In Proc., NDT in Progress, 5th Int. Workshop of NDT Experts. Red Hook, NY: Curran Associates.
IEEE. 2009. “IEEE 1559–2009: IEEE standard for inertial systems terminology.” Accessed March 25, 2021. https://standards.ieee.org/standard/1559-2009.html.
IEEE. 2020. “IEEE P1780 DRAFT standard for the specification of inertial measurement units (IMUs).” Accessed March 25, 2021. https://standards.globalspec.com/std/14368300/ieee-p1780-draft.
Jasiūnienė, E., and E. Žukauskas. 2010. “The ultrasonic wave interaction with porosity defects in welded rail head.” Ultragarsas 65 (1): 12–18.
Jimenez–Redondo, N., N. Bosso, L. Zeni, A. Minardo, F. Schubert, F. Heinicke, and A. Simroth. 2012. “Automated and cost effective maintenance for railway (ACEM–rail).” Procedia-Social Behav. Sci. 48: 1058–1067. https://doi.org/10.1016/j.sbspro.2012.06.1082.
Junger, M., H. M. Thomas, R. Krull, and S. Rühe. 2004. “The potential of eddy current technology regarding railroad inspection and its implementation.” In Proc., 16th World Conf. on Non-Destructive Testing. Vienna, Austria: International Atomic Energy Agency.
Kemeny, J., and K. Turner. 2008. Ground-based lidar: Rock slope mapping and assessment. Washington, DC: Federal Highway Administration, Central Federal Lands Highway Division.
Knothe, K., and A. Groß-Thebing. 2008. “Short wavelength rail corrugation and non-steady-state contact mechanics.” Veh. Syst. Dyn. 46 (1–2): 49–66. https://doi.org/10.1080/00423110701590180.
Lato, M., J. Hutchinson, M. Diederichs, D. Ball, and R. Harrap. 2009. “Engineering monitoring of rockfall hazards along transportation corridors: Using mobile terrestrial LiDAR.” Nat. Hazards Earth Syst. Sci. 9 (3): 935–946. https://doi.org/10.5194/nhess-9-935-2009.
Lawrence Romaine, L. R. 2019. “Shortline maintenance: Focus on the fundamentals.” Accessed February 8, 2021. https://www.rtands.com/track-maintenance/on-track-maintenance/shortline-maintenance-focus-on-the-fundamentals/.
Lee, J. S., S. Choi, S. S. Kim, and C. Park. 2012. “Estimation of rail irregularity by axle-box accelerometers on a high-speed train.” In Noise and vibration mitigation for rail transportation systems, 571–578. Tokyo: Springer.
Li, Q., and S. Ren. 2012a. “A real-time visual inspection system for discrete surface defects of rail heads.” IEEE Trans. Instrum. Meas. 61 (8): 2189–2199. https://doi.org/10.1109/TIM.2012.2184959.
Li, Q., and S. Ren. 2012b. “A visual detection system for rail surface defects.” IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42 (6): 1531–1542. https://doi.org/10.1109/TSMCC.2012.2198814.
Li, Q., Z. Shi, H. Zhang, Y. Tan, S. Ren, P. Dai, and W. Li. 2018. “A cyber-enabled visual inspection system for rail corrugation.” Future Gener. Comput. Syst. 79 (Feb): 374–382. https://doi.org/10.1016/j.future.2017.04.032.
Li, Q., Y. Tan, Z. Huayan, S. Ren, P. Dai, and W. Li. 2016. “A visual inspection system for rail corrugation based on local frequency features.” In Proc., 2016 IEEE 14th Int. Conf. on Dependable, Autonomic and Secure Computing, 14th Int. Conf. on Pervasive Intelligence and Computing, 2nd Int. Conf. on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), 18–23. New York: IEEE.
Li, Q., Z. Zhong, Z. Liang, and Y. Liang. 2015. “Rail inspection meets big data: Methods and trends.” In Proc., 2015 18th Int. Conf. on Network-Based Information Systems, 302–308. New York: IEEE.
Li, Y., H. Trinh, N. Haas, C. Otto, and S. Pankanti. 2013. “Rail component detection, optimization, and assessment for automatic rail track inspection.” IEEE Trans. Intell. Transp. Syst. 15 (2): 760–770.
Li, Z., R. P. B. J. Dollevoet, M. Molodova, and X. Zhao. 2009. “The validation of some numerical predictions on squats growth.” In Proc., 8th Int. Conf. on Contact Mechanics and Wear of Rail/Wheel Systems (CM2009), edited by P. A. Bracciali, 369–377. Amsterdam, Netherlands: Elsevier.
Liu, X., C. T. Dick, and M. R. Saat. 2014. “Optimizing ultrasonic rail defect inspection to improve transportation safety and efficiency.” In Proc., T&DI Congress 2014: Planes, Trains, and Automobiles, 765–774. Reston, VA: ASCE. https://doi.org/10.1061/9780784413586.074.
Lou, Y., T. Zhang, J. Tang, W. Song, Y. Zhang, and L. Chen. 2018. “A fast algorithm for rail extraction using mobile laser scanning data.” Remote Sens. 10 (12): 1998. https://doi.org/10.3390/rs10121998.
Lu, P. 2020. “Technologies in railroad infrastructure inspection approach: A review.” In Proc., 2020 New Technologies in Transportation Infrastructure Management and Maintenance World Transport Convention. Xi’an, China: World Transport Convention.
Ma, L., Y. Li, J. Li, C. Wang, R. Wang, and M. A. Chapman. 2018. “Mobile laser scanned point-clouds for road object detection and extraction: A review.” Remote Sens. 10 (10): 1531. https://doi.org/10.3390/rs10101531.
Magel, E. E. 2011. Rolling contact fatigue: A comprehensive review. Washington, DC: USDOT.
Magnus, D. L. 1995. “Noncontact technology for track speed rail measurements: ORIAN.” In Vol. 2458 of Proc., Nondestructive Evaluation of Aging Railroads, 45–51. Bellingham, WA: International Society for Optics and Photonics. https://doi.org/10.1117/12.212677.
Mandriota, C., M. Nitti, N. Ancona, E. Stella, and A. Distante. 2004. “Filter-based feature selection for rail defect detection.” Mach. Vis. Appl. 15 (4): 179–185. https://doi.org/10.1007/s00138-004-0148-3.
Marino, F., A. Distante, P. L. Mazzeo, and E. Stella. 2007. “A real-time visual inspection system for railway maintenance: Automatic hexagonal-headed bolts detection.” IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37 (3): 418–428. https://doi.org/10.1109/TSMCC.2007.893278.
Mazzeo, P. L., M. Nitti, E. Stella, and A. Distante. 2004. “Visual recognition of fastening bolts for railroad maintenance.” Pattern Recognit. Lett. 25 (6): 669–677. https://doi.org/10.1016/j.patrec.2004.01.008.
Mockel, S., F. Scherer, and P. F. Schuster. 2003. “Multi-sensor obstacle detection on railway tracks.” In Proc., IEEE IV2003 Intelligent Vehicles Symp. (Cat. No. 03TH8683), 42–46. New York: IEEE.
Mohamad, M., K. Kusevic, P. Mrstik, and M. Greenspan. 2013. “Automatic rail extraction in terrestrial and airborne LiDAR data.” In Proc., 2013 Int. Conf. on 3D Vision-3DV 2013, 303–309. New York: IEEE.
Molodova, M., Z. Li, and R. Dollevoet. 2009. Simulation of dynamic responses of vehicle track system for detection of track short wave defects. In Proc., 8th Int. Conf. on Contact Mechanics and Wear of Rail/Wheel Systems (CM2009), 1121–1128. Amsterdam, Netherlands: Elsevier.
MTA. 2016. “Annual procurement report 2016.” http://web.mta.info/mta/compliance/pdf/2016_annual/MTAProcurementReport.pdf.
Muñoz, J., M. Ahmadian, and M. Craft. 2013. “Evaluation of LIDAR track measurement systems in car body and truck-mounted configurations.” In Vol. 56116 of Proc., Rail Transportation Division Conf., V001T01A012. New York: ASME.
Netzelmann, U., G. Walle, A. Ehlen, S. Lugin, M. Finckbohner, and S. Bessert. 2016. “NDT of railway components using induction thermography.” In Vol. 1706 of Proc., AIP Conf., 150001. Melville, NY: AIP Publishing LLC. https://doi.org/10.1063/1.4940613.
Neubert, M., C. Gedrange, R. Hecht, and M. Trommler. 2008a. “Automated object extraction from LiDAR and ortho-image data for railroad databases.” In Proc., Geospatial Crossroads@ GI_Forum’08: Proc., Geoinformatics Forum Salzburg, 221–226. Stuttgart, Germany: Wichmann.
Neubert, M., R. Hecht, C. Gedrange, M. Trommler, H. Herold, T. Krüger, and F. Brimmer. 2008b. “Extraction of railroad objects from very high resolution helicopter-borne LiDAR and ortho-image data.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 38 (Part 4/C1): 25–30.
Nordco. 1999a. “Introduction to rail flaw detection.” Accessed March 25, 2021. https://www.nordco.com/Customer-Support/Rail-Services--Inspection-Technologies/Introduction-to-Rail-Flaw-Detection.htm#:%7E:text=When%20a%20potential%20flaw%20is%20identified%2C%20the%20vehicle%20is%20stopped,the%20railroad%20for%20remedial%20action.
Nordco. 1999b. “Rail flaw identification handbook.” Accessed March 25, 2021. https://www.nordco.com/Customer-Support/Rail-Services--Inspection-Technologies/Inspection-Services/Rail-Flaw-Identification-Handbook.htm.
Olsen, M. J. 2013. Vol. 748 of Guidelines for the use of mobile LIDAR in transportation applications. Washington, DC: Transportation Research Board.
Omar, T. 2016. The Federal Railroad Administration’s LiDAR-based automated grade crossing survey system: Research results. Washington, DC: Federal Railroad Administration.
Papaelias, M. P., and M. Lugg. 2012. “Detection and evaluation of rail surface defects using alternating current field measurement techniques.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 226 (5): 530–541. https://doi.org/10.1177/0954409712444840.
Papaelias, M. P., C. Roberts, and C. L. Davis. 2008. “A review on non-destructive evaluation of rails: State-of-the-art and future development.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 222 (4): 367–384. https://doi.org/10.1243/09544097JRRT209.
Pohl, R., A. Erhard, H. J. Montag, H. M. Thomas, and H. Wüstenberg. 2004. “NDT techniques for railroad wheel and gauge corner inspection.” NDT&E Int. 37 (2): 89–94. https://doi.org/10.1016/j.ndteint.2003.06.001.
Popović, Z., V. Radović, L. Lazarević, V. Vukadinović, and G. Tepić. 2013. “Rail inspection of RCF defects.” Metalurgija 52 (4): 537–540.
RailCorp. 2006. “Rail defects handbook.” Accessed June 12, 2021. https://www.transport.nsw.gov.au/system/files/media/asa_standards/2019/tmc-226.pdf.
RailCorp. 2013. “TMC 203 track inspection.” Accessed June 12, 2021. https://www.transport.nsw.gov.au/system/files/media/asa_standards/2019/tmc-203.pdf.
Real, J., P. Salvador, L. Montalbán, and M. Bueno. 2011. “Determination of rail vertical profile through inertial methods.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 225 (1): 14–23. https://doi.org/10.1243/09544097JRRT353.
Reid, L. 2016. Overcoming rail-end bolt hole cracking by cold expansion pre-stressing. Seattle: Fatigue Technology, Inc.
RIEGL Laser Measurement Systems. 2020. “RIEGL VMX-RAIL.” Accessed June 12, 2021. http://www.riegl.com/uploads/tx_pxpriegldownloads/RIEGL_VMX-RAIL-brochure_2020-09-04.pdf.
Saadat, S., C. Stuart, G. Carr, and J. Payne. 2014. “Development and use of FRA autonomous track geometry measurement system technology.” In Proc., AREMA 2014 Annual Conf. Washington, DC: USDOT.
Sabato, A., C. H. Beale, and C. Niezrecki. 2017. “A novel optical investigation technique for railroad track inspection and assessment.” In Vol. 10169 of Proc., Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, and Civil Infrastructure 2017, 101692C. Bellingham, WA: International Society for Optics and Photonics. https://doi.org/10.1117/12.2257831.
Sabato, A., and C. Niezrecki. 2017. “Feasibility of digital image correlation for railroad tie inspection and ballast support assessment.” Measurement 103 (Jun): 93–105. https://doi.org/10.1016/j.measurement.2017.02.024.
Sánchez-Rodríguez, A., M. Soilán, M. Cabaleiro, and P. Arias. 2019. “Automated inspection of railway tunnels’ power line using LiDAR point clouds.” Remote Sens. 11 (21): 2567. https://doi.org/10.3390/rs11212567.
Sasama, H., M. Ukai, and Y. Okimura. 1991. “The development of rail-gap inspection system.” Railway Tech. Res. Inst., Q. Rep. 32 (1): 21–29.
Soleimanmeigouni, I., A. Ahmadi, and U. Kumar. 2018. “Track geometry degradation and maintenance modelling: A review.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 232 (1): 73–102. https://doi.org/10.1177/0954409716657849.
Song, Z., T. Yamada, H. Shitara, and Y. Takemura. 2011. “Detection of damage and crack in railhead by using eddy current testing.” J. Electromagn. Anal. Appl. 3 (12): 546–550. https://doi.org/10.4236/jemaa.2011.312082.
Stella, E., P. Mazzeo, M. Nitti, G. Cicirelli, A. Distante, and T. D’Orazio. 2002. “Visual recognition of missing fastening elements for railroad maintenance.” In Proc., IEEE 5th Int. Conf. on Intelligent Transportation Systems, 94–99. New York: IEEE.
Stevens, J. 2009. “Unattended vehicle/track interaction (V/TI) monitoring systems: Applied approaches for improving track safety and maintenance planning.” In Proc., AusRAIL PLUS 2009. Springfield, VA: ENSCO.
Sun, Y. Q., C. Cole, M. McClanachan, A. Wilson, S. Kaewunruen, and M. B. Kerr. 2009. “Rail short-wavelength irregularity identification based on wheel-rail impact response measurements and simulations.” In Proc., 9th Int. Heavy Haul Conf. Virginia Beach, VA: International Heavy Haul Association.
Sun, Y. Q., C. Cole, and M. Spiryagin. 2013. “Study on track dynamic forces due to rail short-wavelength dip defects using rail vehicle-track dynamics simulations.” J. Mech. Sci. Technol. 27 (3): 629–640. https://doi.org/10.1007/s12206-013-0117-8.
Szugs, T., A. Krüger, G. Jansen, B. Beltman, S. Gao, H. Mühmel, and R. Ahlbrink. 2016. “Combination of ultrasonic and eddy current testing with imaging for characterization of rolling contact fatigue.” In Proc., 19th World Conf. on Non-Destructive Testing, 19680. Red Hook, NY: Curran Associates.
Taheri Andani, M., A. Mohammed, A. Jain, and M. Ahmadian. 2018a. “Application of LIDAR technology for rail surface monitoring and quality indexing.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 232 (5): 1398–1406. https://doi.org/10.1177/0954409717727200.
Taheri Andani, M., A. Peterson, J. Munoz, and M. Ahmadian. 2018b. “Railway track irregularity and curvature estimation using doppler LIDAR fiber optics.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 232 (1): 63–72. https://doi.org/10.1177/0954409716660738.
Tang, X. N., and Y. N. Wang. 2013. “Visual inspection and classification algorithm of rail surface defect.” Comput. Eng. 39 (3): 25–30.
Thomas, H. M., T. Heckel, and G. Hanspach. 2007. “Advantage of a combined ultrasonic and eddy current examination for railway inspection trains.” Insight, Non-Destr. Test. Cond. Monit. 49 (6): 341–344. https://doi.org/10.1784/insi.2007.49.6.341.
Thomas, H. M., M. Junger, H. Hintze, R. Krull, and S. Rühe. 2000. “Pioneering inspection of railroad rails with eddy currents.” In Proc., 15th World Conf. on Non-Destructive Testing. Red Hook, NY: Curran Associates.
TSB (Transportation Safety Board of Canada). 2017. “Railway investigation report r05e0059.” Accessed February 3, 2021. https://www.tsb.gc.ca/eng/rapports-reports/rail/2005/r05e0059/r05e0059.html.
Westeon, P. F., C. S. Ling, C. Roberts, C. J. Goodman, P. Li, and R. M. Goodall. 2007. “Monitoring vertical track irregularity from in-service railway vehicles.” Proc. Inst. Mech. Eng., Part F: J. Rail Rapid Transit 221 (1): 75–88. https://doi.org/10.1243/0954409JRRT65.
WMATA (Washington Metropolitan Area Transportation Authority). 2008. “Rail geometry vehicle.” Accessed June 12, 2021. https://www.wmata.com/about/board/meetings/board-pdfs/upload/021408_3BGeometry Car.pdf.
Wu, Y., Y. Qin, Z. Wang, and L. Jia. 2018. “A UAV-based visual inspection method for rail surface defects.” Appl. Sci. 8 (7): 1028. https://doi.org/10.3390/app8071028.
Xin, T., P. Wang, and Y. Ding. 2019. “Effect of long-wavelength track irregularities on vehicle dynamic responses.” Shock Vib. 2019: 1–11. https://doi.org/10.1155/2019/4178065.
Yang, B., and L. Fang. 2014. “Automated extraction of 3-D railway tracks from mobile laser scanning point clouds.” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 7 (12): 4750–4761. https://doi.org/10.1109/JSTARS.2014.2312378.
Zarembski, A. 2015. Determination of the impact of heavy axel loads on short lines. Newark, DE: Delaware Center for Transportation, Univ. of Delaware.
Zhang, H., X. Jin, Q. J. Wu, Y. Wang, Z. He, and Y. Yang. 2018. “Automatic visual detection system of railway surface defects with curvature filter and improved Gaussian mixture model.” IEEE Trans. Instrum. Meas. 67 (7): 1593–1608. https://doi.org/10.1109/TIM.2018.2803830.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 10 • October 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Nov 3, 2020
Accepted: Apr 16, 2021
Published online: Jul 28, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 28, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Zhihao Hu, Xiaoci Huang, A real-time automatic rail extraction algorithm for low-density mobile laser scanning data, Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 10.1177/09544097241228888, (2024).
- Pan Lu, Yihao Ren, Chengbo Ai, Xianfeng (Terry) Yang, Denver Tolliver, Xinyi Yang, AI-Assisted LiDAR System’s Performance Assessment for Automatic Track Geometry Monitoring, International Conference on Transportation and Development 2024, 10.1061/9780784485521.056, (627-636), (2024).
- Yuhua Sun, Yuan Wang, Song Tian, ShuaiShuai Huo, Man Hu, Fei Wu, Qiang Yi, Boyang An, Ping Wang, Mingyuan Gao, Energy Self-Sufficient Rail Corrugation Identification by a Multistable Piezo-Electro-Magnet Coupled Energy Transducer, IEEE Transactions on Instrumentation and Measurement, 10.1109/TIM.2023.3309382, 72, (1-13), (2023).
- Don Skerman, Colin Cole, Maksym Spiryagin, The effect of the wavelength of lateral track geometry irregularities on the response measurable by an instrumented freight wagon, Vehicle System Dynamics, 10.1080/00423114.2023.2183871, 62, 3, (533-555), (2023).
- Yihao Ren, Chengbo Ai, Pan Lu, Zhenyu Dai, Hao Wang, An Automated Rail Extraction Framework for Low-Density LiDAR Data Without Sensor Configuration Information, IEEE Sensors Journal, 10.1109/JSEN.2022.3177698, 22, 13, (13234-13243), (2022).