Bridge Weigh-in-Motion system for the identification of train loads using fiber-optic technology

Abstract This paper presents a cost-effective Bridge Weigh-in-Motion (B-WIM) system for the identification of train loads using fiber-optic technology. The system is capable of estimating the train’s speed, geometry and static axle loads, using the algorithm proposed by Moses. This algorithm involves the resolution of an inverse identification problem where the measured structural response is known and the loading scheme is unknown. The method relies on the concept of Influence Line (IL), which is estimated from the passage of a calibration vehicle with known characteristics. A numerical validation example, based on a simply supported bridge with a train passing at different speeds, demonstrated the functionality and potential accuracy of the implemented B-WIM system. For speeds up to 120 km/h, the maximum estimated errors of the wheelbase and axle loads were 10 cm and 2.5%, respectively. A B-WIM system was installed in an existing filler-beam bridge, located on the Portuguese Railways, consisting of a minimalist layout of fiber Bragg grating sensors, which guarantee higher-quality measurements, quick installation and long-term stability. The system allowed a precise characterization of several Alfa Pendular, Urban and Regional trains. This study constitutes a step forward in the development of online B-WIM systems capable of automatically estimating traffic characteristics. The accurate estimation of the traffic loads is a valuable information for the evaluation of the structural integrity and safety of railway bridges.

[1]  Miroslav Vokáč,et al.  ANALYSIS OF THE ACCURACY OF FIBRE-OPTIC STRAIN GAUGES , 2013 .

[2]  Rui Calçada,et al.  Weighing-in-motion wireless system for sustainable railway transport , 2017 .

[3]  Guido De Roeck,et al.  One-year monitoring of the Z24-Bridge : environmental effects versus damage events , 2001 .

[4]  Raid Karoumi,et al.  Implementing bridge weigh-in-motion for railway traffic , 2007 .

[5]  H. Kanehara,et al.  Measuring rail/wheel contact points of running railway vehicles , 2002 .

[6]  A. Matsumoto,et al.  A new measuring method of wheel–rail contact forces and related considerations , 2008 .

[7]  Rui Calçada,et al.  An approach for wheel flat detection of railway train wheels using envelope spectrum analysis , 2020, Structure and Infrastructure Engineering.

[8]  R.M. da Costa Marques Pimentel,et al.  Hybrid Fiber-Optic/Electrical Measurement System for Characterization of Railway Traffic and Its Effects on a Short Span Bridge , 2008, IEEE Sensors Journal.

[9]  Rui Calçada,et al.  Evaluation of the Performance of Different Damage Indicators in Railway Bridges , 2015 .

[10]  Eugene J. O'Brien,et al.  Calculating an influence line from direct measurements , 2006 .

[11]  Raid Karoumi,et al.  Traffic monitoring using a structural health monitoring system , 2015 .

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

[13]  Rui Calçada,et al.  A new strategy to estimate static loads for the dynamic weighing in motion of railway vehicles , 2020, Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit.

[14]  Raimundo Delgado,et al.  Global and Local Dynamic Effects on a Railway Viaduct with Precast Deck , 2014 .

[15]  Mayorkinos Papaelias,et al.  Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals , 2016 .

[16]  Congcong Fang,et al.  A new wayside method for measuring and evaluating wheel-rail contact forces and positions , 2020 .

[17]  Ole Øiseth,et al.  Influence line extraction by deconvolution in the frequency domain , 2017 .

[18]  Fred Moses,et al.  Weigh-In-Motion System Using Instrumented Bridges , 1979 .

[19]  Raid Karoumi,et al.  Monitoring traffic loads and dynamic effects using an instrumented railway bridge , 2005 .

[20]  Humberto Varum,et al.  Probabilistic Seismic Performance Analysis of RC Bridges , 2018, Journal of Earthquake Engineering.

[21]  Benedetto Allotta,et al.  A New Strategy for Dynamic Weighing in Motion of Railway Vehicles , 2015, IEEE Transactions on Intelligent Transportation Systems.

[22]  Eugene J. O'Brien,et al.  Development and Testing of a Railway Bridge Weigh-in-Motion System , 2020, Applied Sciences.

[23]  Maja Kreslin,et al.  Railway Bridge Weigh-in-Motion System , 2016 .

[24]  Rui Calçada,et al.  Impact of track irregularities and damping on the fatigue damage of a railway bridge deck slab , 2018 .

[25]  Raid Karoumi,et al.  BWIM aided damage detection in bridges using machine learning , 2015, Journal of Civil Structural Health Monitoring.

[26]  U. Saravanan,et al.  Algorithms to determine wheel loads and speed of trains using strains measured on bridge girders , 2018, Structural Control and Health Monitoring.

[27]  Lennart Elfgren,et al.  Sustainable Bridges - Results from a European Integrated Research Project , 2010 .

[28]  Túlio Nogueira Bittencourt,et al.  Dynamic Response of a Railway Bridge to Heavy Axle-Load Trains Considering Vehicle–Bridge Interaction , 2018 .

[29]  Nicola Bosso,et al.  Wheel flat detection algorithm for onboard diagnostic , 2018, Measurement.

[30]  Myra Lydon,et al.  Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors , 2017 .

[31]  Pedro A. S. Jorge,et al.  Calibration of the Numerical Model of a Short-span Masonry Railway Bridge Based on Experimental Modal Parameters , 2015 .

[32]  Leandro Fleck Fadel Miguel,et al.  Weight estimation on static B-WIM algorithms: A comparative study , 2019, Engineering Structures.

[33]  Dan M. Frangopol,et al.  Maintenance and management of civil infrastructure based on condition, safety, optimization, and life-cycle cost* , 2007 .

[34]  C. Esveld Modern railway track , 1989 .

[35]  Jinkyo F. Choo,et al.  New Bridge Weigh-in-Motion System Using Piezo-Bearing , 2018, Shock and Vibration.

[36]  Raimundo Delgado,et al.  Finite-element model calibration of a railway vehicle based on experimental modal parameters , 2013 .

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

[38]  Joaquim Gabriel,et al.  On-line monitoring system for tracks , 2015, 2015 3rd Experiment International Conference (exp.at'15).

[39]  Przemysław Kołakowski,et al.  Piezo‐based weigh‐in‐motion system for the railway transport , 2012 .

[40]  Álvaro Cunha,et al.  Weigh-in-motion implementation in an old metallic railway bridge , 2016 .

[41]  Tadeusz Uhl,et al.  The inverse identification problem and its technical application , 2007 .

[42]  Eugene J. O'Brien,et al.  Bridge weigh-in-motion using a moving force identification algorithm , 2017 .

[43]  Mark F. Green,et al.  A regularised solution to the bridge weigh-in-motion equations , 2009 .

[44]  Hitoshi Tsunashima,et al.  Condition Monitoring of Railway Tracks from Car-Body Vibration Using a Machine Learning Technique , 2019, Applied Sciences.

[45]  C. S. Cai,et al.  State-of-the-art review on bridge weigh-in-motion technology , 2016 .