摘要
利用三端压电陶瓷片设计的结冰传感器测量值受温度的影响较大,为了提高传感器测量的准确度,提出了一种自适应模拟退火粒子群优化算法进行温度补偿。该算法将模拟退火算法和粒子群优化算法进行融合,采用非线性双曲正切函数来控制惯性权重系数的变化,利用线性变化策略来控制社会学习因子和自我学习因子的值,使寻优重点在不同阶段有所变化,自适应地改变惯性权重系数、社会学习因子和自我学习因子,并解决了算法容易陷入局部优解的问题。实验结果表明,经该算法温度补偿后,结冰状态下测量的误差减少3%左右,测量精度提高0.1 mm,说明该补偿算法能有效地减小-5℃~-55℃的低温环境对传感器测量结果的影响,提高了测量精度。
The measurement value of the icing sensor designed with three-terminal piezoelectric ceramics is greatly affected by temperature.In order to improve the measurement accuracy of the sensor,an adaptive simulated annealing particle swarm optimization algorithm is proposed to compensate for temperature.This algorithm integrates the simulated annealing algorithm and the particle swarm algorithm,uses the nonlinear hyperbolic tangent function to control the change of the inertia weight coefficient,and uses the linear change strategy to control the values of the social learning factor and the self-learning factor,so that the optimization focus varies at different stages.The inertia weight coefficient,the social learning factorand the self-learning factor are adaptively changed,which solves the problem that the algorithm is easy to fall into the local optimal solution.The experimental results show that after the temperature compensation of this algorithm,the measurement error is reduced to about 3%in the freezing state,and the measurement accuracy is improved to 0.1 mm,indicating that the compensation algorithm can effectively reduce the influence of-5℃~-55℃on the measurement results of the sensor and improve the measurement accuracy.
作者
于天河
吴迪
YU Tianhe;WU Di(College of Measurement and Control Technology and Telecommunications engineering,Harbin University of Science and Technology,Harbin 150080,China)
出处
《北京邮电大学学报》
EI
CSCD
北大核心
2023年第6期115-120,共6页
Journal of Beijing University of Posts and Telecommunications
关键词
压电陶瓷
结冰传感器
温度补偿
模拟退火算法
粒子群优化算法
piezoelectric ceramic
ice sensor
temperature compensation
simulated annealing algorithm
particle group optimization algorithm
