Detection of hidden defects of aircraft long truss structures (aluminum alloy) is a challenging problem. The shape of the aircraft truss structure is complex, and the crack defects are buried in a large depth. Without the restriction of skin effect, remote field eddy current (RFEC) has great advantages in detecting buried depth defects. In this paper, in order to detect the hidden defects of the aluminum alloy aircraft long truss structure, the remote field eddy current probe is improved from two aspects of magnetic field enhancement and near-field signal suppression using the finite element method. The results show that indirect coupling energy is greatly enhanced when the connected magnetic circuit is added to the excitation coil. By adding a composite shielding structure outside the excitation coil and the detection coil, respectively, the direct coupling energy is effectively restrained. As a result, the size of the probe is reduced. By optimizing the coil spacing and probe placement position, the detection sensitivity of the probe is improved. The simulation is verified by experiments, and the experimental results are consistent with the simulation conclusions.

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The ability to characterise corrosion and gouging associated with metal loss and the identification of gouge type from metal loss defect types are two of the primary obstacles affecting magnetic flux leakage (MFL) internal inspection technology. Gouges in pipelines are not extraordinarily severe; however, the depth of corrosion increasing due to a certain corrosion rate can be quite serious. In this paper, a novel theoretical model combined with a new approach for the analysis of the signals that distinguish gouging and corrosion using a low magnetisation level is presented for MFL detection, since the traditional MFL internal detection tools are insensitive to stress characteristics in the case of saturation magnetisation. A two-stage finite element (FE) model for the prediction of magnetic flux leakage resulting from two types of defect is built. In the first stage, the stress distribution associated with gouging is obtained from a solid mechanics model and, in the second stage, the stress distribution is incorporated into a magnetic finite element model by mapping the stress levels to permeability. The possibility of detection and identification of corrosion and gouging using the MFL technique at low-level magnetisation was confirmed by experimentally comparing the characteristics of the MFL signals for each defect type.

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