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ISSN 2753-3239
CCC: 15
PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE
Edited by: J. Pombo
Paper 7.3

Analytic Temporal Tracker Sensor Monitoring System - Case Study

L. Lopes1, J.L.G. Spada1, L.C. Pedrosa1 and D. Trautwein2

1, Muniz & Spada Engenheiros Consultores Ltda., Brazil
2, Solver Tecnologias, Brasil

Full Bibliographic Reference for this paper
L. Lopes, J.L.G. Spada, L.C. Pedrosa, D. Trautwein, "Analytic Temporal Tracker Sensor Monitoring System - Case Study", in J. Pombo, (Editor), "Proceedings of the Seventh International Conference on Railway Technology: Research, Development and Maintenance ", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 15, Paper 7.3, 2026, doi:10.4203/ccc.15.7.3
Keywords: railway monitoring, track modulus, deflection, case study, infrastructure maintenance, vibration sensors.

Abstract
This paper introduces the Analytic Temporal Tracker (ATT) sensor system and its application in a railway section. The equipment provides high-frequency tracking of vibration, acceleration, inclination, and temperature, delivering processed data such as dynamic deflection and track modulus. The system operates in both stationary and campaign modes, allowing multiple point measurements with the same portable hardware. A case study was conducted at four critical points of interest along a railway section located in Rio de Janeiro, Brazil. Using a portable ATT sensor, it was possible to monitor all four locations within a single day. The methodology involved temporary mechanical fixation to the rail and data recording during train passage. Results indicated that deflection and track modulus were outside the ideal design parameters, potentially influenced by significant rainfall during the three days preceding the tests. The ATT sensor offers a practical alternative for remote railway monitoring through continuous or programmed readings. Its automated alerts and limit configurations facilitate prompt actions. The results of the case study confirmed the system’s effectiveness in identifying critical deviations in track performance, highlighting the immediate need for maintenance intervention.

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