基于小波神经网络的电容称重传感器非线性补偿研究  

Research on the Non-linearity compensation Based on Wavelet Neural Network for Capacitance weighing Sensor

作　　者：俞阿龙[1] 

机构地区：[1]淮阴师范学院电子与电气工程系,江苏淮安223300

出　　处：《微计算机信息》2010年第7期49-50,33,共3页Control & Automation

基　　金：基金申请人:俞阿龙;项目名称:"智能神经算法在传感器信号处理中应用研究";基金颁发部门:江苏省高等学校自然科学基础研究基金(07KJD510027)

摘　　要：为了解决电容称重传感器的非线性问题,提出了补偿其非线性的小波神经网络方法。该方法以电容称重传感器实验数据为基础,通过小波神经网络训练来确定传感器非线性补偿网络。介绍电容称重传感器非线性补偿原理,分析网络的拓扑结构,给出网络参数训练方法。结果表明,采用小波神经网络进行电容称重传感器非线性补偿具有好的鲁棒性,网络训练速度快、精度高,并能在线补偿,在测试领域有实用价值。A method used to the capacitance weighing sensor non-linearity compensation is applied based on wavelet neural network（WNN） to settle its non-linear problem.In this method,a non-linear compensation network can be set up according to measurement data of capacitance weighing sensor.The compensating principle is introduced and the geometrical structure of the network is analyzed and the algorithms of network parameters training is given.The results show that the proposed WNN has strong robustness,and on-line correction ability,and fast network training speed and high precision when used in the capacitance weighing sensor non-linearity compensation and practical value in measurement field.

关 键 词：电容称重传感器 非线性 补偿 小波神经网络 

分 类 号：TP212.6[自动化与计算机技术—检测技术与自动化装置]