Page 88 - 捷運技術 第60期
P. 88

Journal of Rapid Transit System and Technology No.60
            pp. 77-94, 2025                                   DOI 10.29670/JRTST.202510_(60).0005




            Received May 27, 2025, accepted July 07, 2025, date of publication October 31, 2025



              Temperature Monitoring System for EMU Hot

                     Axle Bearings and Brake Discs





            YUHJANG LEE , PEIYUAN LEE , CHANGHAN LIN       3
                           1
                                          2
            1  Department of Rapid Transit Systems, TCG, SEMPO
            2  Department of Rapid Transit Systems, TCG, SEMPO
            3  Department of Rapid Transit Systems, TCG, SEMPO
            Corresponding Authors: YUHJANG LEE , E-mail: ax8187@gov.taipei



                                              ABSTRACT


            This research explores the temperature monitoring system for axle neck bearings
            and brake discs of electric multiple units (EMUs). With the development of smart
            railway technologies, enhancing transportation safety and maintenance efficiency
            has become an important issue. This paper introduces the design framework of this
            monitoring system and utilizes high-precision temperature sensing technology,
            combined with RFID and wireless communication, to collect real-time data and
            transmit it to backend systems for preventive maintenance and optimization of
            maintenance plans. The implementation of the system allows for the early detection
            of anomalies to ensure operational safety and aims to effectively reduce
            maintenance costs while improving overall operational efficiency. By introducing
            the functions, structure, and principles of the monitoring system, this research
            provides a reference direction for the future development of smart railways.


            Keywords:  Temperature Monitoring System, Axle Bearings and Brake Discs,
                        Predictive Maintenance
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