传感技术学报2017，Vol.30Issue(6)：861-866,6.DOI:10.3969/j.issn.1004-1699.2017.06.010
基于径向基神经网络的称重设备传感器故障检测方法
Fault Detection Method for Weighing Equipment Sensor Based on Radial Basis Function Neural Network
摘要
Abstract
In the process of digitalization of weighing equipment,some researchers have proposed some faultdiagnosis methods for a particular sensor,but for non-specific sensor or two fault sensors,situation these methods are not ap-plicable. So,this paper presents a method foranyone sensor or two sensors based on RBFNN. Firstly,this paperestab-lish the prediction model of any single sensor and prediction model of any two sensors,and thencalculate any one weighing sensor,s predictive value and any two sensors,predictions,judging the fault weighing sensor,s number,lo-cation,type through the difference between predicted value and actual value. Experiments show that this method can accurately detect the fault information of the sensor when the error of the sensor is above 0.3 tons.关键词
称重传感器/故障检测/故障类型识别/径向基神经网络Key words
weighing sensor/fault detection/fault type identification/radial basis function neural network分类
信息技术与安全科学引用本文复制引用
刘洋,欧文,卢赢,卢圣文..基于径向基神经网络的称重设备传感器故障检测方法[J].传感技术学报,2017,30(6):861-866,6.基金项目
江苏省科技支撑重点项目( BE2014003) （ BE2014003）
江苏省自然科学基金项目( BK20161149) （ BK20161149）
