传感技术学报Issue(11)：1537-1542,6.DOI:10.3969/j.issn.1004-1699.2013.11.013
基于导数约束的称重传感器非线性误差补偿方法
Method for Compensation of Load Cell's Nonlinear Error Based on Derivatives Constraints
摘要
Abstract
The nonlinear error of the resistance strain gauge load cell has heavy nonlinear error,which will lead to the low accuracy of weighing results. In this paper,the mechanism of the load cell's nonlinear error is introduced and a method for compensation on the load cell's nonlinear error based on derivatives constraints neural network ( DCNN) is proposed. In this method,the monotonically increasing characteristic of load cell's input-output function is used to construct the constraint conditions of training and optimizing the error compensation model with neural network,which can decrease the model's generalization error because of the lack of its training samples. On the other hand,the model's performance affected by the punishing factor is discussed. The experimental results show that the nonlinear error of load cell with this proposed method is far less than that without compensation,and the DCNN's generalization ability is more advantageous than the DINN( i. e. training neural network by only using data samples and not any constraint condition) ,and the weighing results of load cell with DCNN are more accurate.关键词
称重传感器/非线性误差补偿/神经网络/导数约束Key words
load cell/nonlinear error compensation/neural network/derivatives constraints分类
信息技术与安全科学引用本文复制引用
林海军,王震宇,林亚平,汪鲁才..基于导数约束的称重传感器非线性误差补偿方法[J].传感技术学报,2013,(11):1537-1542,6.基金项目
国家自然科学基金项目(51205127) （51205127）
中国博士后基金项目(2012M511717) （2012M511717）
湖南省教育厅基金项目(110845) （110845）
