基于卡尔曼滤波的区间式铝电解槽似在电阻采集算法

针对目前铝电解行业对于槽似在电阻的采集不够准确并且延时较高的问题,本文提出一种基于卡尔曼滤波的区间式槽似在电阻采集算法。该算法以卡尔曼滤波为基础,用预测值与采样值的均方差表征它们的高斯白噪声功率,使其能够在电阻平稳的状态下有着较强的跟踪性能;再结合一阶惯性滤波的强滤波特性和卡尔曼滤波的强跟踪优势,设置适用的滤波区间,确保组合算法在槽似在电阻波动较大的情况下能够滤除掉噪声的影响,并在电解槽稳定后能对槽似在电阻进行快速收敛跟踪。结果表明:与一阶惯性滤波相比,改进后的卡尔曼滤波在电阻平稳的状态下其均方根误差减少50%,在电解槽反生针振和摆动情况之后的收敛时间减少90%。

Kalman filter-based segmented aluminum electrolytic cell slot-like resistance acquisition algorithm

Aiming at the current problems of the aluminum electrolytic cell's inaccurate collection of slot-like resistance and high delay,this paper proposed an interval slot-like resistance acquisition algorithm based on Kalman filtering.This algorithm is based on Kalman filtering and uses the mean squared error of predicted and sampled values to characterize their Gaussian white noise power,enabling it to have strong tracking performance in the state of stable cell resistance.Combined with the strength of first-order inertial filtering characteristics and the strong tracking advantage of Kalman filtering,an applicable filtering interval is set to ensure that the combined algorithm can filter out the influence of noise when the slot-like resistance fluctuates greatly,and can quickly converge the slot-like resistance after the electrolytic cell is on stable track.The simulation results show that compared with the first-order inertial filter,the improved Kalman filter reduces the root mean square error by 50%when the cell resistance is stable,and reduces the convergence time by 90%after the electrolytic cell regenerates needle vibration and swing.