计量学报2017，Vol.38Issue(4)：429-434,6.DOI:10.3969/j.issn.1000-1158.2017.04.10
基于BP神经网络的压电陶瓷蠕变预测
Prediction of the Creep of Piezoelectric Ceramic Based on BP Neural Network Optimized by Genetic Algorithm
摘要
Abstract
The creep errors of the piezoelectric ceramics have nonlinear change with the time, which is difficult to revise in real time. A creep prediction approach based on back propagation neural network is proposed for the piezoelectric ceramics. The data is collected by the piezoelectric ceramic driving system and normalized for prediction. The parameters of BP neural network including the number of hidden layers, the number of nodes in each hidden layer, the node transfer functions and the training function are designed by experiments.The prediction model of BP neural network is established, and the connection between the creep of the piezoelectric ceramic and the time is built. The creep of piezoelectric ceramics is predicted by the model of BP neural network, compared with the measured data, the results show that, using this prediction model the maximal absolute error is below 0.1 μm, the maximal creep error is below 0.6% and the maximal mean square error is 0.0021. So the BP neural network prediction model has a high prediction accuracy and can be applied to the creep prediction of the piezoelectric ceramics.关键词
计量学/压电陶瓷/蠕变/BP神经网络/预测模型Key words
metrology/piezoelectric ceramics/creep/BP neural network/prediction model分类
通用工业技术引用本文复制引用
范伟,林瑜阳,李钟慎..基于BP神经网络的压电陶瓷蠕变预测[J].计量学报,2017,38(4):429-434,6.基金项目
国家自然科学基金(51475176) （51475176）
福建省自然科学基金(2017J01086) （2017J01086）
中央高校基本科研业务费专项(JB-2R1159, JB-ZR1107) （JB-2R1159, JB-ZR1107）
华侨大学研究生科研创新能力培育计划资助项目 （）
