An Innovative Combined Train Speed Measurement Method for Medium-Low Speed Maglev Trains

This paper delves into the medium-low speed maglev transit system, presenting a novel urban railway mode that forgoes conventional axle-based sensors such as speed odometers due to its maglev propulsion characteristics. The research introduces eddy current sensors as a viable alternative for speed measurement, leveraging their non-contact nature and immunity to mechanical wear and environmental constraints. A sophisticated sensor information fusion algorithm, integrating Kalman filtering with adaptive weighted fusion, is proposed to augment the accuracy and dependability of speed measurements. Through a meticulous comparative analysis of four speed measurement fusion algorithms based on their variance, the study identifies the most suitable algorithm for practical engineering applications in real projects. This work not only enhances the methodology of train speed measurement but also provides a foundation for future applications in similar non-contact measurement scenarios.