A novel differential excitation capacitive sensing for hydrogen pipeline inspection

Transportation and storage for hydrogen have garnered increasing attention in recent years because of the rapid development of low-carbon hydrogen energy. Pipeline is regarded as one of the most efficient ways for hydrogen transportation. However, many research found that the active hydrogen atoms can penetrate into the material and induce cracking on the pipe. As the initial hydrogen induced cracking is small, detecting these small defects can be challenging. To enhance the detectability of these small defects, we propose a novel capacitive sensor structure featuring two differential excitations. It is noted that the lift-off noise is always a challenging problem in electromagnetic NDE method. Fortunately, this problem can be alleviated by the proposed method. The simulation result shows the output signal will not be significantly influenced by the lift-off changing. Two metallic samples with defects are tested with a PCB-based prototype probe. Experiment result shows that the developed sensor can suppress the lift-off noise by 81.0% and increase the SNR by 592.28%, comparing to the results of a conventional sensor. A defects extraction algorithm is developed based on morphological image processing method to extract the defects from the raw data automatically. Size estimation is conducted and the average quantization error rate is 7.01% for 10 mm defects. Therefore, from the simulation and experimental results, the proposed capacitive sensing method can be a potential approach for hydrogen pipeline inspection.