Combination Balance Correction of Grinding Disk Based on Improved Quantum Genetic Algorithm

Abstract

To solve the problems of low measurement efficiency and measurement accuracy error in the balance correction of the mill before delivery. The measurement method of measuring a single chip instead of the whole chip group is adopted. And based on that, an improved adaptive quantum genetic algorithm (QGA) based on Bloch spherical coordinates is proposed. Three layers of quantum coding are used for the grinding group, the first layer adopts three-strand gene coding, the second and third layers adopt double-strand gene coding, and the adaptive step coefficient is introduced on this basis. The improved algorithm not only has the global search ability of a genetic algorithm (GA) but also has the coding ability of quantum bit, which can avoid the premature algorithm and improve the convergence performance of the algorithm. The results show that the proposed method enhances the correction accuracy compared with the traditional correction method. The residual unbalance is less than 0.005 kg; work efficiency increased by 92%. It can improve the calibration efficiency and accuracy of grinding disk installation balance measurement.