WSN-Based Vibration Characteristic Research for Various Railway Track Structures for Pattern Classification

Author:

Yue Guo-dong1,Xu Zheng1,Wang Liding1,Liu Chong1,Ren Tongqun1

Affiliation:

1. Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian 116085, P. R. China

Abstract

To effectively study vibration characteristics of tracks under different track structures, wavelet transforms of the vibration data are used for pattern classification of vibration feature. First, acceleration data of the track are collected with running speed of 150[Formula: see text]km/h at 26 positions respectively on a slab tangent track, ballast tangent track and ballast curve track by a wireless sensor network (WSN). Then they are analyzed using the power spectral densities (PSDs) and wavelet-based energy spectrum analysis. The paper elaborates on the reasons for the differences of vibration energy and excitation frequencies due to the mechanism of different frequency bands and the corresponding track structures. Based on these, the instantaneous frequencies, vibration energies and durations in the low, medium, and high frequency bands are selected as the features for three track structures. A function curve representing the features is proposed to detect the abnormal track structure by a correlation analysis. Finally, the proposed method of pattern classification has been validated by experimental testings.

Funder

Key Projects in the National Science and Technology Pillar Program of China

Science Fund for Creative Research Groups of NSFC

the National Natural Science Foundation of China

the Fundamental Research Funds for the Central Universities

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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