Vibration-Based Detection of Wheel Flat on a High-Speed Train

Wang, Ruichen; Crosbee, David; Beven, Adam; Wang, Zhiwei; Zhen, Dong

doi:10.1007/978-3-030-57745-2_14

Cited by 2 publications

(1 citation statement)

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“…Several researchers have studied wheel defect detection and evaluated wheel conditions during operation [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ], including the previous works of the authors [ 31 , 32 , 33 ]. Polygonal wheel mechanics have been studied in the last few decades [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ].…”

Section: Introductionmentioning

confidence: 99%

Wheel Out-of-Roundness Detection Using an Envelope Spectrum Analysis

Gonçalves

Mosleh

Vale

et al. 2023

Sensors

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This paper aims to detect railway vehicle wheel flats and polygonized wheels using an envelope spectrum analysis. First, a brief explanation of railway vehicle wheel problems is presented, focusing particularly on wheel flats and polygonal wheels. Then, three types of wheel flat profiles and three periodic out-of-roundness (OOR) harmonic order ranges for the polygonal wheels are evaluated in the simulations, along with analyses implemented using only healthy wheels for comparison. Moreover, the simulation implements track irregularity profiles modelled based on the US Federal Railroad Administration (FRA). From the numerical calculations, the dynamic responses of several strain gauges (SGs) and accelerometer sensors located on the rail between sleepers are evaluated. Regarding defective wheels, only the right wheel of the first wheelset is considered as a defective wheel, but the detection methodology works for various damaged wheels located in any position. The results from the application of the methodology show that the envelope spectrum analysis successfully distinguishes a healthy wheel from a defective one.

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