基于最小二乘与粒子群算法的压力传感器动态补偿方法  

Dynamic Compensation Method Based on Least Squares Algorithm and Particle Swarm Optimization for Pressure Sensor

作　　者：轩春青[1,2] 轩志伟[3,4] 陈保立[3] 

机构地区：[1]郑州成功财经学院信息工程系,河南巩义451200 [2]郑州大学信息工程系,郑州450001 [3]中北大学电子测试技术国防重点实验室,太原030051 [4]武汉高德红外股份有限公司,武汉430070

出　　处：《传感技术学报》2014年第10期1363-1367,共5页Chinese Journal of Sensors and Actuators

摘　　要：为了降低运用简化传感器模型对动态测试结果进行修正时带来的误差,提出一种基于最小二乘(LSM)与粒子群优化算法(PSO)的动态补偿器设计方法。采用最小二乘法识别传感器的最佳阶次,作为补偿器的阶次,克服简化模型对补偿器设计的影响,结合粒子群算法对传感器进行逆建模得到补偿器,并分析补偿前后传感器的时域与频域特性。实验表明,该方法能有效的降低传感器的动态测量误差。In order to correct the error caused by dynamic characteristics of sensor by using simplified model,a de￣sign method of dynamic compensator based on least square method( LSM)&particle swarm optimization( PSO) algo￣rithm is presented. Using the least square method to identify the optimal order of the sensor,which used as the order of the compensator,an analysis about the dynamic characteristics of the sensor is made in the time domain and fre￣quency domain. Experimental results show that this method can effectively reduce the dynamic measurement error of the sensor.

关 键 词：动态误差补偿 阶次识别 最小二乘与粒子群优化算法 频带拓展 

分 类 号：TP212.6[自动化与计算机技术—检测技术与自动化装置]