- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | GAO Tianci, JIANG Lepeng, CONG Jianli, WANG Yuan, LIU Xiaozhou, ZHU Jiasong, LUO Qin, WANG Ping. Rapid Detection Method for Rail Corrugation in Metro Lines Based on Data Fusion of Train-Borne Vibration and Noise[J]. Journal of Southwest Jiaotong University, 2025, 60(6): 1603-1610. doi: 10.3969/j.issn.0258-2724.20240121
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The rapid identification and accurate localization of rail corrugation in metro lines are of significant importance for the maintenance departments of metros to formulate reasonable maintenance plans, thereby saving considerable efforts in metro operational works. In this study, low-cost, portable, and vehicle-mounted sensing terminals were utilized to detect the vibration and noise of metro trains across the entire line. Given the difficulty in obtaining stable GPS signals in underground environments, a multi-source data fusion method based on the secondary integration of longitudinal acceleration, the yaw rate of the vehicle body, and the matching with the line’s planar curvature was adopted to achieve precise mileage localization of the detected vibration and noise data. Building upon this foundation and in conjunction with on-site corrugation detection results, a vibrational-noise feature of the wave depth index for identifying rail corrugation was proposed. Furthermore, by utilizing quantile regression, a correlation between the wave depth index and corrugation depth was established. The findings indicate that the corrugation identification and localization results based on the wave depth index are consistent with on-site observations, with the primary wavelength of corrugation concentrated around 40 mm. Additionally, as the wave depth index increases, the corrugation depth exhibits a “fan-shaped” growth pattern, consistent with the characteristics of quantile regression, enabling the estimation of corrugation noise management thresholds at different quantile levels.
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