Improved electromagnetic compatibility testing for rail vehicles using a quantum-based 3D reconstruction algorithm

This research presents a comprehensive investigation into the electromagnetic compatibility (EMC) analysis of rail vehicle speed sensors. It begins by establishing rigorous EMC testing standards for radio field speed sensors used in railway vehicles, encompassing parameters such as antenna orientation, interference strength, frequency range, and signal stability. Additionally, the study explores the theoretical underpinnings of radio frequency (RF) emissions, emphasizing the importance of loop size in PCBs with transmission lines and the complexities involved in estimating field strength. Notably, the research introduces the integration of quantum-based 3D reconstruction algorithms into EMC analysis, enabling a more accurate representation of the electromagnetic environment surrounding rail vehicles. Furthermore, an optimization algorithm based on chaos theory and neural networks is proposed, offering a promising approach to fine-tune sensor design for enhanced EMC compliance. Through experiments and tests, the study demonstrates the significant impact of optimization and quantum-enhanced 3D reconstruction on the EMC of rail vehicle speed sensors, resulting in reduced RF radiation and improved electromagnetic compatibility. This research contributes to the advancement of EMC analysis in the railway industry, ensuring the safety and performance of critical components.