基于声学黑洞的谷物流量传感器支架减振优化

为减少联合收获机振动对谷物流量传感器监测结果的干扰，设计了一种基于声学黑洞（ABH，acoustic black hole）原理的谷物流量传感器龙门支架减振结构，通过有限元方法分析减振结构的振动特性，分析了二维声学黑洞比例系数ε、幂函数指数m和半径R对其减振性能的影响规律。结果表明，声学黑洞能够显著降低龙门支架的振动，ε、m和R对声学黑洞减振性能的影响均未表现出明显线性关系，当ε=0.001 2、m=2.5、R=15 mm时声学黑洞的减振效果最好。以振动速度平方和作为优化目标，建立了多项式回归代理模型，通过遗传算法对声学黑洞比例系数ε、幂函数指数m和半径R的取值进行了优化。相比于未添加声学黑洞的原始龙门支架和初始声学黑洞方案，优化后龙门支架的振动速度平方和分别降低68.92%和2%，表明优化方案具有更佳的减振性能。提出的基于声学黑洞的减振结构和优化设计方法为农业机械被动宽频减振研究提供了理论参考。

Damping and optimization of grain flow sensor gantry based on acoustic black hole

A damping structure of a grain flow sensor gantry based on the principle of acoustic black hole (ABH) was designed in this study to reduce the interference of vibration of the combine harvester on the monitoring results of the grain flow sensor. The vibration characteristics of the damping structure were analyzed by the finite element method, and the influence of the scale coefficient ε, power function index m and radius R of the two-dimensional ABH on the damping performance of the structure were examined. The results indicated that ABH could significantly reduce the vibration of the gantry. The influences of ε, m, and R on the vibration reduction performance of the ABH did not exhibit a significant linear correlation. When ε=0.001 2, m=2.5, and R=15 mm, the ABH demonstrated the best vibration reduction effect. Taking the sum of squares of vibration velocity as the optimization goal, a polynomial regression surrogate model was established. Then the values of the parameters ε, m and R were optimized by genetic algorithm. Compared with the original gantry without ABH and the initial ABH design scheme, the sum of squares of the optimized gantry vibration velocity was reduced by 68.92% and 2%, respectively, indicating the superior damping performance of the optimization scheme. The proposed damping structure based on ABH and optimization design method provides a theoretical reference for agricultural machinery passive and broadband damping technology.