Rail fracture monitoring based on ultrasonic-guided wave technology with multivariate coded excitation

Yuan Yang; Ping Wang; Yinliang Jia; Lixuan Jing; Yu Shi; Hongwei Sheng; Yi Jiang; Renbao Liu; Yihang Xu; Xin Li

doi:10.1016/j.ultras.2023.107164

Rail fracture monitoring based on ultrasonic-guided wave technology with multivariate coded excitation

Ultrasonics. 2024 Jan:136:107164. doi: 10.1016/j.ultras.2023.107164. Epub 2023 Sep 17.

Authors

Yuan Yang¹, Ping Wang², Yinliang Jia³, Lixuan Jing⁴, Yu Shi⁵, Hongwei Sheng⁶, Yi Jiang⁷, Renbao Liu⁸, Yihang Xu⁹, Xin Li¹⁰

Affiliations

¹ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: y.yang20@nuaa.edu.cn.
² College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: zeitping@nuaa.edu.cn.
³ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: jyl@nuaa.edu.cn.
⁴ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: jinglixuan@nuaa.edu.cn.
⁵ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: shiyunuaa@nuaa.edu.cn.
⁶ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: zjwx521@sina.com.
⁷ College of Electrical Engineering, Nanjing Vocational University of Technology, Nanjing 210023, China. Electronic address: 2021101294@niit.edu.cn.
⁸ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: SX2203012@nuaa.edu.cn.
⁹ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: xuyihang@nuaa.edu.cn.
¹⁰ College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. Electronic address: lixin1924@nuaa.edu.cn.

PMID: 37748363
DOI: 10.1016/j.ultras.2023.107164

Abstract

Steel lay the basis of railroad train traffic. Rail fracture is the most serious injury to the rail, which should be monitored in time. The conventional mono-pulse exciting ultrasonic guide wave (UGW) has low energy, the conventional Barker code has limited coding sequence length and the orthogonal complementary Golay code has the problem of low monitoring efficiency. This study proposes multivariate coded excitation (MCE) to excite UGW to monitor rail fracture, and the feasibility of coding and decoding the method is theoretically derived and verified. Ideally, the MCE generated based on the 3-bit Barker code (B₃: 1,1, -1) and 4-bit orthogonal complementary Golay code (GA₄: 1,1,1, -1; GB₄: 1,1, -1,1) is calculated to have a main-lobe power level (MPL) gain of 8.1020 dB, which is significantly higher than the MPL of Barker and Golay codes. For the proposed method, finite element modeling simulation and experimental study are carried out respectively. Analyze and process the data, and calculate the gain of the difference in amplitude (DIA) between the amplitude of echo caused by rail fracture and the amplitude in the healthy rail. The gain of the DIA of the echoes in the MCE is above 50 dB (experimental data, the value of simulation data is 5 dB) under different degrees of rail fracture, while the gain of the DIA of the echoes caused by the other three excitation methods is below 40 dB (experimental data, the value of simulation data is 1 dB). Simulation and experimental results show that the MCE makes up for the shortcomings of the conventional Barker code and Golay code, improves the excitation energy of the monitoring system, and the high gain of the DIA of the echoes is more conducive to the identification of rail fracture damage.

Keywords: Coded excitation; Multivariate coding; Pulse compression; Rail fracture; Structural health monitoring; Ultrasonic-guided wave.