Author: Tong, Andi
Title: Analysis of dynamic interaction and coupling in a high-speed train based on on-board monitoring data
Degree: M.Sc.
Year: 2017
Subject: Hong Kong Polytechnic University -- Dissertations
High speed trains -- Dynamics
Railroad tracks -- Dynamics
High speed trains -- Vibration
Railroad tracks -- Vibration
Department: Faculty of Construction and Environment
Pages: 81 pages : color illustrations
Language: English
Abstract: When the operation velocity of the high-speed train rises, not only the sensitivity of the wheel/rail contact improves, but also the vibration frequency domain of the vehicle system dynamics increases. Therefore, it is important to investigate the vibration characteristics and the dynamics frequency transference from the wheel/rail interface to the carbody of the high-speed train. Several triaxial accelerometers are assembled on the wheelset boxes, bogie frames and carbodies to test the vibration of the vehicle system. Based on the on-board monitoring data, the vibrating accelerations of axle boxes, bogie frames and carbodies of the high-speed train on three directions are obtained. Fast Fourier Transform (FFT) method is introduced to investigate the vibration energy in different critical components. The wheels lathed during the testing period. The results show that the main frequency domain of the axle box, bogie frame and carbody around 600 - 650 Hz, 80 - 85 Hz, 0-2 Hz, respectively. The vibrations energy of running gear mainly concentrated around 85 Hz and 620 Hz, the concrete frequency depends on the velocity. In other frequency ranges, (200- 400 Hz) the cause of these vibrations is inferred to be the high-order polygonization of the wheel. The frequencies of the vibration over 500 Hz almost concentrated around the integer multiplies of the rotation frequency. Due to the roles of the primary and secondary suspension system, the mean value of spectrum power density reduced dramatically in lateral and vertical direction. The eliminated vibrations are mainly in high-frequency range. In low-frequency range, the vibration energy concentrated around 7 Hz before wheel lathing. After wheel lathing, the vibration of that vibration was eliminated. According to this phenomenon, a Naïve Bayes Classifier (NBC) was established. This paper presents the use of Naïve Bayes algorithm for state diagnosis through FFT features extracted from vibration signals of good and bad conditions of the wheel tread.
Access: restricted access

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/9530