An Enhanced Local Flaw Quantification Method for SWRs Based on a Circumferential-Award Spatial Model

Magnetic flux leakage (MFL) detection is an effective non-destructive testing (NDT) method for steel wire ropes (SWRs), where the quantitative analysis of local flaws (LFs) plays a crucial role in assessing the health condition of the SWR. In this article, an optimized magnetic dipole model in a cylindrical coordinate system is proposed, capable of analyzing the spatial characteristics of the leakage magnetic field from the axial, radial, and circumferential directions. Through the proposed magnetic dipole model and 3D simulation model, the leakage magnetic fields generated by different sizes of LFs are analyzed, and a new circumferential-aware spatial model is proposed. Additionally, utilizing the MFL signals collected by a uniform circular array (UCA), the proposed model considers both the axial maximum peak value and circumferential distribution, enabling the effective LF quantification with different broken wires, achieving recognition of metal cross-sectional area loss differences as small as 0.28%. Furthermore, the validity of the proposed method is verified through experiments on different SWRs and LFs. Even in different sampling and usage scenarios, the proposed method demonstrates superior quantitative identification performance. It also facilitates subsequent processing with intelligent algorithms, such as neural networks, enhancing the health status identification of SWRs.