CAJ | 학술논문

针对传统的基于贡献图的多元统计方法中变量贡献值不能真实反映故障原因的不足，提出一种基于符号有向图（SDG）模型和数据重构的故障诊断方法，该方法使用平方预测误差（SPE）和累积和（ CUSUM ）统计量进行故障检测，通过在故障发生时对SDG的所有相容路径方向的样本数据进行重构，重构后残差变化最大的方向被认为是故障的传播方向，该方向上的起始节点为导致故障的原因变量。通过在TEP模型上仿真表明：该方法能有效地诊断出引起故障的根本原因。
침대전통적기우공헌도적다원통계방법중변량공헌치불능진실반영고장원인적불족，제출일충기우부호유향도（SDG）모형화수거중구적고장진단방법，해방법사용평방예측오차（SPE）화루적화（ CUSUM ）통계량진행고장검측，통과재고장발생시대SDG적소유상용로경방향적양본수거진행중구，중구후잔차변화최대적방향피인위시고장적전파방향，해방향상적기시절점위도치고장적원인변량。통과재TEP모형상방진표명：해방법능유효지진단출인기고장적근본원인。
Considering the fact that in traditional contribution plots-based multivariate statistics , variable con-tribution value has insufficiency in reflecting the failure cause , a new fault diagnosis method based on signed directed graph ( SDG) and data reconstruction was proposed to have square prediction error ( SPE) and cumula-tive sum(CUSUM) used to detect a fault;when a fault happens, all sample data on SDG’s consistent bran-ches can be reconstructed;and the branches where maximal residual change exists after to be reconstructed is the fault propagation branch , the initial node is thought to be the causal variable which resulting in the fault . Simulation in TEP process shows that this method can find the fault cause accurately .