Visual quantitative detection of rail surface crack based on laser ultrasonic technology

Abstract

The surface rolling contact fatigue crack is a common crack on the rail surface. When it extends to a certain length, it will lead to rail fracture and affect the safety of railway operation. Therefore, it is necessary to carry out quantitative detection of RCF cracks to ensure the safety of railway operation. The state-of-the-art shows that the visualization method has advantages for quantitative crack detection. In this study, a quantitative detection method combining non-contact laser ultrasonic testing technology and variational mode decomposition (VMD) is proposed to realize the visual detection of the oblique crack on the railhead surface. Wigner time-frequency distribution and fir1 filtering are used to preliminarily filter all scanning signals. Further, VMD is utilized to decompose the signal into multiple intrinsic mode function (IMF) component signals and improve signal-to-noise ratio (SNR). According to the correlation coefficient (C) and SNR characteristics between different IMF components and the original signal, the optimal IMF component is selected. Finally, visual crack-induced surface wave energy from the ultrasonic propagation images is realized according to the time-domain and time characteristics of signals. The visual quantitative detection of RCF cracks in different lengths is realized clearly and intuitively, and the quantitative error is less than 5%. This method lays a foundation for the visual detection of laser ultrasonic rail surface defects.