Abstract
Severe wheel polygon will cause the strong repeated wheel-rail excitation, accelerating the failure of vehicle key components. Nevertheless, the traditional spectral estimation methods are not ideal for dealing with these wheel fault signals, making the characteristic frequencies caused by wheel polygon hardly detected. This paper proposes a dynamic detection method for wheel polygon based on parametric power spectral estimation for the first time. Firstly, according to the dynamic characteristics of the wheel polygon, the harmonic frequency recovery model is established. Secondly, the order of the harmonic frequency recovery model is determined based on singular value decomposition and normalised error analysis. Then, the total least square method is used to calculate the parameters of the harmonic recovery model. Finally, the power spectrum of the fault signal is evaluated according to the Cadzow estimation theory. The simulation signal and the measured axle-box vertical vibration acceleration signal of a metro vehicle are taken as case studies to verify the feasibility and effectiveness of the proposed method thoroughly. The results show the proposed method can avoid the inherent defects of traditional detection and analysis methods, weaken the influence of background noise, and is highly advantageous in detecting the initial stage of wheel polygonal wear.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
