【摘要】 文中针对压电式多维力测力仪向间干扰大，制约测量精度的问题，分析了向间干扰对测力仪测量精度的影响，提出了一种基于支持向量回归机(SVR)的非线性解耦算法。利用混合模拟退火算法(HSA)对SVR进行参数寻优，对比并分析了HSA-SVR和线性最小二乘解耦法(LS)的解耦性能，证明经该方法解耦后向间干扰最大为0.526%,非线性误差最大为0.214%,HSA-SVR具有更好的非线性解耦效果。更多还原

【Abstract】 Addressing the issue of significant inter-directional interference in piezoelectric multidimensional force measuring instruments, which constrains measurement accuracy, this paper analyzed the impact of inter-directional interference on the precision of force measuring instruments and proposed a nonlinear decoupling algorithm based on support vector regression(SVR) machine learning.The optimization of SVR parameters was achieved using a hybrid simulated annealing algorithm(HSA).The 0decoupling performance of HSA-SVR was compared and analyzed with linear least squares decoupling(LS).The results demonstrate that after decoupling, the maximum inter-directional interference is only 0.526%,and the maximum nonlinear error is 0.214%.HSA-SVR exhibits superior performance in decouplingnonlinearities.更多还原