高灵敏度感应式磁传感器测量误差校正算法

Measurement Error Correction Algorithm of High Sensitivity Induction Magnetic Sensor

针对复杂磁环境下感应式磁传感器测量误差偏高的问题,基于改进遗传算法设计了一种测量误差校正算法。在分析传感器工作原理及影响灵敏度关键因素基础上,将硬铁误差、软铁误差、装配弧度误差、标度系数误差及噪声作为感应式磁传感器误差来源,把不同姿态下所有测量值收敛在一个椭球面,构建磁传感器误差模型。然后利用遗传算法中的选择、交叉和变异等算子优化误差模型参数,再应用一种仅与进化代数相关和个体适应度无关的计算方法,获得自适应交叉算子与变异算子,从而完成高精度测量误差校正任务。仿真结果表明,所提算法拥有很高的参数估计精度,可有效对上述因素引发的误差实施校正,对高灵敏度感应式磁传感器在多种测量环境下的有效应用具有重要参考意义。

Traditionally,genetic algorithm has high measurement error of induction magnetic sensor.Therefore,this paper designed a measurement error correction algorithm based on improved genetic algorithm.The working principle of the sensor and the key factors affecting the sensitivity were analyzed,respectively.Hard iron error,soft iron error,assembly radian error,scale coefficient error and noise were regarded as error sources of induction magnetic sensor.The measured values of different attitude were converged to an ellipsoid to construct the error model of magnetic sensor.The opators of selection,crossover and mutation of genetic algorithm were applicatedto optimiz the parameters of error model.A calculation method related to evolutionary algebra and independent of individual fitness was adopted to obtain adaptive crossover operator and mutation operator,thus completing the error correction of high-precision measurement.The simulation results show that the algorithm has high accuracy of parameter estimation and can effectively correct the errors caused by the above factors.It is of great significance for the effective application of high sensitivity induction magnetic sensor in various measurement environments.