摘要
为设计一种兼具抗高过载性能与高灵敏度的低量程电容式加速度传感器,结合响应面分析和遗传算法,对传感器的7组尺寸参数进行了优化。利用实验设计(DOE)中的多组采样点与二次拟合确定了尺寸参数与传感器输出变量之间的函数关系,基于该函数引入惩罚因子,进行多次遗传算法迭代处理。最终统计响应面优化和遗传算法的结果,获得了1组最优尺寸参数。优化结果表明:在相同的加速度作用下,传感器的等效应力降低约18%,等效位移增大约12%,设计灵敏度增大约20%,在30000 gn过载下的最大应力减少224.94 MPa,具有更高的抗过载能力。
In order to design a low-range capacitive accelerometer with high overload resistance and high sensitivity,seven sets of size parameters of the sensor are optimized by combining response surface analysis and genetic algorithm.The functional relationship between the size parameter and the sensor output is determined by using multiple sets of sampling points in design of experiment(DOE)and quadratic fitting.A penalty factor is then introduced to this function to perform multiple genetic algorithm iterations.Finally,through the results of the response surface optimization and genetic algorithm,a set of optimal size parameters are obtained.The optimization results show that compared to before,the equivalent stress of the sensor is reduced by about 18%,the equivalent displacement is increased by about 12%and the design sensitivity is increased by about 20%.And the maximum stress under 30000 gn overload is reduced by 224.94 MPa,which proves the anti-overload ability of the sensor has a significant improvement.
作者
闫晓燕
刘小柔
赵建淳
李楠
YAN Xiaoyan;LIU Xiaorou;ZHAO Jianchun;LI Nan(School of Instrument and Electronics,North University of China,Taiyuan 030051,China;Chifeng Industry Vocational Technology College,Chifeng 024005,China)
出处
《传感器与微系统》
CSCD
北大核心
2024年第8期118-121,共4页
Transducer and Microsystem Technologies
基金
山西省回国留学人员科研资助项目(2021-116)。
关键词
响应面优化
遗传算法
抗过载
低量程
response surface optimization
genetic algorithms(GA)
anti-overload
low range
