Designing and Investigating a Nondestructive Magnetic Flux Leakage Detection System for Quantitatively Identifying Wire Defects

In-haul cables must be examined and maintained regularly to ensure the smooth operation of cable-stayed bridges. The magnetic flux leakage (MFL) detection method is being applied increasingly commonly to inspect defects. For the quantitative identification of the broken wire, we designed an MFL inspection equipment and investigated the performance. A trapezoidal magnetic dipole model is constructed to simulate the leakage distribution, and the axial and circumferential excitation schemes are used to obtain the intensity of magnetic induction. Then, based on the simulation of model parameters, an MFL detection system is configured for detecting the damage in the broken wire. To investigate the adaptability of the developed system, a rectangular defect is inspected in the vertical and spiral climbing modes. The signal acquired under different paths is processed by the median filtering and wavelet transform methods and analyzed. A random forest algorithm is used to quantitatively identify the number of broken wires, defect dimensions, and cross-sectional area loss to verify the proposed method. The results show that the axial excitation generates a single peak signal, which offers better detection of the wire defects. In the vertical climbing mode, the maximum detection errors in the width and cross-sectional area loss are 0.64 mm and 0.46%, respectively, while the values are 0.21 mm and 0.1% in the spiral climbing mode, indicating that the latter mode offers higher identification accuracy. Furthermore, in future work, the detection capability of irregular defects should be studied, expanding its application in health monitoring.