Adaptive Inspection Approach for Internal Local Flaw Detection Based on Magnetic Flux Leakage Imaging

Compared with the external local flaw (ELF), the internal local flaw (ILF) of the steel wire rope (SWR) is quite challenging in the field of intelligent operation and maintenance since it cannot be diagnosed online by manual visual methods. In this article, an inspection equipment based on the magnetic flux leakage (MFL) effect suitable for detecting ILFs is developed, and a circular noise suppression (CNS) method and adaptive detection method based on the morphological features are proposed. The proposed noise suppression method makes full use of the spatial information in the MFL image and can realize the removal of image edge noise. The proposed detection method can adaptively adjust the threshold value according to different complex working conditions to realize accurate ILF detection. Compared with the state-of-the-art (SOTA) methods, the proposed method is robust and advanced in terms of high signal-to-noise ratio (SNR) and $F1$ -Score under complex working conditions and noise effects.