• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2024, Vol. 60 ›› Issue (24): 244-253.doi: 10.3901/JME.2024.24.244

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Research on Wheel Polygon Recognition Method of Heavy-haul Locomotive Under Variable-speed Condition

LIU Renzhe, WANG Hongbing, CHEN Shiqian, WANG Kaiyun   

  1. State Key Laboratory of Rail Transit Vehicle System Southwest Jiao Tong University, Chengdu 610031
  • Received:2024-01-15 Revised:2024-08-19 Online:2024-12-20 Published:2025-02-01

Abstract: It is of great significance for the safe and stable operation of locomotives to identify the polygonal state of wheels by monitoring the vibration response of vehicle components. The complex running environment of heavy-haul locomotive leads to its monitoring signals showing strong noise interference and fast frequency modulation characteristics, which brings great challenges to wheel polygon recognition. Therefore, a method of wheel polygon recognition for heavy-haul locomotive based on optimization of spectrum concentration index is proposed. In this method, polynomial function is used to describe the instantaneous frequency of the low-frequency signal of axle box acceleration, and polynomial parameters are estimated by optimizing the spectral concentration index to approximate the real instantaneous frequency; Based on this, the axle box acceleration is converted in space domain to eliminate the frequency band diffusion phenomenon caused by locomotive speed change; Further, the order spectrum of wheel polygon with high resolution is obtained through order analysis to realize accurate identification of harmonic order. In order to verify the effectiveness of this method, a dynamic model of heavy-haul locomotive is established to simulate the actual speed change conditions to obtain non-stationary axle box acceleration. The proposed method is applied to analyze the signal, and the results show that the method can accurately identify the harmonic order of wheel polygon under variable-speed conditions. In addition, the proposed method shows good accuracy and noise robustness when analyzing the measured axle box acceleration signal.

Key words: heavy-haul locomotives, fault diagnosis, wheel polygon, variable-speed condition, order analysis

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