摘要
汽车衡称重传感器零点故障是一种典型的微小故障,不易在线检测,利用递推主元分析(RPCA)与四类故障检测指标相结合的方法,提出一种汽车衡称重传感器零点故障在线检测方法。该方法首先利用基于秩1修正的主元递推算法在线更新主元模型,然后利用Hotelling’s T^2统计量、平方预测误差(SPE)统计量、Hawkins TH^2统计量、主元相关变量残差(PVR)统计量及其控制限构建故障综合评判方法,最终完成称重传感器零点故障及微小故障在线检测。实验表明,采用这种基于递推主元分析和综合评判方法的称重传感器,零点故障检测准确率比传统方法(即仅采用T^2、TH^2、SPE、PVR任何一类统计量进行判别),提高了一个数量级,证实了该方法的有效性。
A zero-point fault of load cells in truck scale is a typical minor fault and it is difficult to be detected online.A method for detecting zero-point fault online is proposed by combining a recursive principal component analysis(RPCA)with four types of fault detection indicators.In this method,firstly,the principal component model is updated online by the principal recursive algorithm based on rank 1 modification,and then the four statistics,i.e.,the Hotelling’s T^2 statistic,the squared prediction error(SPE)statistic,the Hawkins TH^2 statistic,and the principal component related variable residual(PVR)statistic,are used to construct a comprehensive evaluation method for fault detection.This proposed method for fault detection online is applied to load cells in truck scale,and the experimental results show that the accuracy of zero-point fault detection is increased with an order of magnitude by the traditional method,which proves the effectiveness of this proposed method.
作者
李慧霞
林海军
邵耿荣
叶源
Li Huixia;Lin Haijun;Shao Gengrong;Ye Yuan(College of Engineering and Design,Hunan Normal University,Changsha 410081,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2020年第1期32-42,共11页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(51775185)
湖南省自然科学基金(2018JJ2261)资助项目。
关键词
汽车衡
称重传感器
零点故障检测
递推主元分析
综合评判
truck scale
load cell
zero-point fault detection
recursive principal component analysis
comprehensive evaluation method
