Quantitative detection of rail head internal hole defects based on laser ultrasonic bulk wave and optimized variational mode decomposition algorithm

This paper proposes a quantitative rail head internal defect detection method combining mode conversion and time-of-flight based on the theory of laser ultrasonic bulk wave scattering and diffraction. The interaction between laser ultrasonic bulk wave and rail internal hole defects is modeled using finite element simulation, and the modal conversion of bulk wave encountered defects is investigated. The feasibility of localization and the quantitative method are both confirmed. Simultaneously, an Optimized Variational Modal Decomposition (OPVMD) method is proposed to solve the problem of low SNR of bulk wave signals and to facilitate multi-mode wave discrimination. This method can extract the defect diffraction Shear Wave (S) signal from complex ultrasonic signals. Finally, experiments are performed on the defects of artificial internal holes in rail heads with varying burial depths and sizes. The experimental results show that the method can not only detect but also quantify the defects of internal holes in rail heads. The location relative errors are within 3%, and the quantitative relative errors are within 7%.