基于NSGA-Ⅱ算法的电容称重传感器抗偏载能力的优化

The Optimization for Anti-Bias Load of Capacitance Weighing Sensor Based on NSGA-Ⅱ Algorithm

为了满足在保证电容称重传感器最小识别极距变化的同时达到提高其抗偏载能力的要求,对传感器进行了多目标优化的研究。分析计算了电容称重传感器力学性能与结构参数之间的关系,建立了以其导向性能和抗弯性能为优化目标的0.001 g精度电容称重传感器的多目标优化模型。应用Isight优化软件中的改进型非支配解遗传(NSGA-Ⅱ)算法得到电容称重传感器的Pareto最优解集,并通过有限元验证了优化结果的准确性。研究表明,在保证电容称重传感器最小识别极距变化的前提下,极大地屏蔽了偏载对电容精度的影响,结果具有很强的实用性。

In order to meet the requirements of improving the anti-bias load capability on the condition that the changes of minimum identified polar pitch of capacitance weighing sensor can be guaranteed, the multi-goals optimization study for the sensor has been made. And the relationship between the mechanical performance and structural parameters has been analyzed and calculated, the optimized model with multi-goals for capacitance weighing sensor with precision 0. 001 g is established based on its guide performance and bending performance as the optimizing goal;the improved non-dominant deciphering genetic algorithm（NSGA-Ⅱ ）in the optimized software of Isight for getting the Pareto optimal solution set is applied, and the accuracy of the optimized results by finite elements has been verified;The study shows that, the affect on capacitance precision by bias load has been shielded at the premise that the changes of minimum identified polar pitch of capacitance weighing sensor can be ensured, the results are of strong practical.