A fuzzy adaptive reasoning method for trains slide/slip detection

Slide/slip of train is an important factor which affects the accuracy of odometer for train positioning. Accurate and prompt detection of slide/slip can effectively avoid the danger by compensatory measurements. In this paper, an adaptive fuzzy algorithm for slide/slip detection is proposed by apply...

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Bibliographic Details
Published in2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) pp. 1 - 4
Main Authors Van Tu, Pham, Bao, Qilian, Zhang, Liang, Xu, Haigui, Du, Yuding
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2017
Subjects
Acceleration
Acceleration difference
Accelerometers
Cognition
Doppler radar
Fuzzy adaptive reasoning
Input variables
Noise measurement
Odometer
Slide/Slip detection
Speed difference
Wheels
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Summary:Slide/slip of train is an important factor which affects the accuracy of odometer for train positioning. Accurate and prompt detection of slide/slip can effectively avoid the danger by compensatory measurements. In this paper, an adaptive fuzzy algorithm for slide/slip detection is proposed by applying the measurement information of odometer, Doppler radar sensor, and accelerometer. The adaptive fuzzy reasoning rules for slide/slip detection are established based on actual data and professional experience. The experimental results showed that the performance of fuzzy adaptive reasoning method is better than fixed threshold detecting method. Furthermore, it is capable to detect weakly slide/slip which is usually ignored by fixed threshold detection.
DOI:10.1109/ICCWAMTIP.2017.8301416