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Updated: Jun 3, 2025

Applicability Analysis of Assessment Methods for Morphological Parameters of Corroded Steel Bars
Published on: November 1, 2018
Identification Method for Railway Rail Corrugation Utilizing CEEMDAN-PE-SPWVD.
Jianhua Liu1, Kexin Zhang1, Zhongmei Wang1
1College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China.
This study introduces a new method to detect rail corrugation using CEEMDAN, PE, and SPWVD. The technique accurately identifies corrugation
Area of Science:
- Mechanical Engineering
- Signal Processing
- Railway Engineering
Background:
- Rail corrugation causes vibrations and damage to vehicle-track systems.
- Accurate identification of corrugation is crucial for maintenance and safety.
- Existing methods may lack precision in determining corrugation characteristics.
Purpose of the Study:
- To propose a novel method for identifying rail corrugation.
- To accurately determine the location, wavelength, and depth of rail corrugation.
- To validate the proposed method using simulated and real-world data.
Main Methods:
- Utilized Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for signal decomposition.
- Employed Permutation Entropy (PE) to filter intrinsic mode functions (IMFs).
- Applied Smoothed Pseudo Wigner-Ville Distribution (SPWVD) for time-frequency analysis and corrugation depth estimation.
Main Results:
- The CEEMDAN-PE-SPWVD method successfully identified rail corrugation wavelength and depth.
- Time-frequency analysis revealed variations in corrugation severity across different locations.
- Validation with simulated and measured data confirmed the algorithm's reliability.
Conclusions:
- The proposed method offers a reliable approach for detecting and characterizing rail corrugation.
- This technique can aid in proactive maintenance and improve railway infrastructure safety.
- Further research can explore real-time implementation and integration with monitoring systems.
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