Dynamic Compensation Based on FLANN Algorithm for Velocity Sensor

Lower cut-off frequency of the magnetoelectric velocity sensor is limited by the structure and the volume due to its nature.In the engineering filed,the band of the sensor should be stretched to detect the velocity signals with lower frequencies.The dynamic characteristic model of magnetoelectric velocity sensor is derived and a dynamic compensation strategy based on FLANN(function link artificial neural networks) algorithm for velocity sensor is proposed.The dynamic compensation effect is compared between FLANN and the pole-zero placement method.The results show that the compensation error is smaller when using FLANN algorithm and the frequency bandwidth of the velocity sensor is expanded effectively,and thus the measurement of ultra-low frequency in engineering is satisfied.