Multi-Vibration Sensor Fusion of Flexible DC Converter Transformer Based on Adaptive Extended Kalman Filter

Mechanical stability is a crucial aspect influencing the rheological properties of flexible direct converters. Monitoring mechanical stress can efficiently enhance the operational capacity of these converters. To increase sensing accuracy and stability for roadside sensors, an adaptive extended Kalman filter (AEKF)-based-sensor fusion method is proposed, which accounts for measurement noise. Employing the sensing results from MEMS vibration sensors, this approach achieves data fusion at the target level for heterogeneous sensors. A method is available online to assess sensor stability and generate adaptive correction coefficients for measurement noise.Practical tests have shown that the multi-sensor fusion method compares to a single sensor and improves lateral distance estimation accuracy by 9.7%.