摘要
传感器的可靠性及准确性对制冷机系统的可靠控制和系统的最优运行起着至关重要的作用。同时,传感器的读数也是进行部件故障诊断的基础。本文提出了基于主元分析法的制冷机传感器故障诊断方法,该方法的主元分析模型由离心式制冷机系统中的相关测量变量在正常条件下的观测样本构成。这一方法利用这些变量在正常条件下的相关性来对传感器的测量观测值进行故障检测与诊断及测量重构,并分别用Q-统计及Q-分布图来对传感器故障进行检测及诊断。本文利用实验室离心式制冷机的试验数据对这一基于主元分析法的传感器故障诊断方法进行了验证。
The reliability and accuracy of sensor measurements are greatly of significance to control and optimal operation of chiller system, as well as the basis of fault detection and diagnosis of chiller component faults. This paper presents a principle component analysis （PCA）-based sensor fault detection and diagnosis and estimation method for chiller system. A PCA model is composed of the observations of correlated variables in centrifugal chiller system in normal operation conditions aiming to capture the systematic variations of chiller system. These variations are used for the fault detection and diagnosis of new observations in terms of Q-statistic and Q-contribution plot. This PCA- based chiller sensor fault detection and diagnosis method was validated using the experimental test data of a centrifugal chiller.
出处
《建筑科学》
北大核心
2007年第6期45-48,67,共5页
Building Science
关键词
离心式制冷机系统
传感器故障
主元分析
故障检测诊断与重构
试验研究
centrifugal chiller system
sensor fault
principal component analysis
fault detection and diagnosis and estimation
experimental study
