In-pipeline inspection is an important pre-control method to ensure the safety of oil and gas pipeline transportation. This paper proposes an electromagnetic in-pipe detector based on passive resonance-enhanced differential planar coils to detect defects on the inner surface of pipes. Both qualitative and quantitative analysis of pipeline defects and damage are developed. The introduction of passive resonant coils is shown to significantly improve the detection capability of the sensor. This is coupled with the establishment of a theoretical derivation model of the proposed structure. The hardware platform of the laboratory system has been built, and an eddy current internal detector suitable for 8-inch diameter pipes is developed and integrated into the system. Numerical simulations and experimental verifications on flat defects and pipe defects have been undertaken. The obtained results have shown that the real defects have been correctly detected and that the system is effective. reliable and efficiency.

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The effectiveness of railway fault inspection has remained challenging. Conventional techniques are still functionally limited and unable to meet the increasing demand of railway diagnosis. To mitigate the variety of rail fault detection problems, this paper proposes a dynamic railway inspection system based on multi-physical coupled electromagnetic and thermography sensing. It further shows the development and construction of a new inverted L-type magnet yoke abreast with volumetric coils array. The novel structure can not only significantly enhance the sensitivity and detectability of the region of interest (ROI), but also effectively detect the subsurface defects with the compensation of coils array due to the coupled electromagnetic field. Furthermore, the theoretical analysis of the coupled physical fields has been derived and proved to be consistent with the numerical simulation results. A rail test sample with various defects is carried out to verify the feasibility of the proposed system. Additionally, a metric learning post-processing algorithm has been conducted for distilling eddy current signals and thermograms to improve the accuracy of the detection results. On-site experimental and contrast results with various levels of performance validation have demonstrated that the integrated system is well suited for dynamic rail inspection on near-surface cracks at speed of 1 km/h.

Magnetic flux leakage (MFL) detection methods are widely used to detect pipeline defects. However, it is limited by the detection orientation and magnetization. Besides, bulky excitation systems are incapable of adapting to the complex detection environments. This paper proposes a new Electromagnetic Structured Coupling sensing of merging Alternating Current Field Measurement (ACFM) and MFL within a multi-parameter system for different types of pipeline defects detection. In particular, a novel electromagnetic coupling sensor structure is proposed which enables simultaneous interaction between the excitation modes of Yoke and coil. Magnetic Yoke is integrated to magnetizing the axial pipeline to detect the circumferential surface and subsurface defects while the coil excites the circumferential uniform alternating current field and recognizes the axial defect. The novel structured sensing is highly sensitivity to the detection of both surface and subsurface defects. Simulation and experiments on defects in several samples have been conducted to validate the reliability and efficiency of the proposed system.