基于扩展卡尔曼滤波的吊钩姿态估计技术研究

Attitude Estimation of Crane Hook Based on Extended Kalman Filter

针对吊钩运动不定且易受大风、雾气等影响其作业效率问题,提出并实现基于MEMS传感器的吊钩姿态估计系统;建立吊钩三维空间运动模型,消除吊钩扭转影响;通过四元数的扩展卡尔曼滤波算法,对MEMS陀螺仪、加速度计与磁强计进行数据融合,解算得到吊钩三维姿态、摆角与摆向;采用基于视觉检测的吊钩空间姿态为参考基准,对起重机吊钩进行姿态估计验证;实验结果表明:该系统能有效融合MEMS传感器数据,获得高精度的吊钩姿态,实现姿态的实时检测。

An attitude estimation of crane hook system based on Micro-Electro-Mechanical Systems（MEMS） sensors is proposed to address the problem of the inefficiency of crane due to the unstable movement of hook,the windy condition and foggy weather.A three-dimensional hook motion model is built to eliminate the negative effects of hook torsion;by fusing the data acquired from the MEMS gyroscope,accelerometer and magnetometer,the error quaternion extended kalman filter is implemented to solve the variables of attitude angle,oscillating angle and swing angle;Implementation using the designed attitude detection platform of crane based on visual inspection technology has been performed to verify the estimation.Experimental results illustrate the proposed system can effectively fuse the MEMS sensor data,achieve highly precise attitude and realize real-time detection.