关键词: 主元分析, 产品质量控制, 故障分离, 故障识别

Abstract: Principal component analysis (PCA) has found wide application in chemical process monitoring and product quality control as a data-driven modeling method.Based on the fault reconstruction technology, the fault isolation and identification issues were explored by using T² index, since some faults involving process fault and sensor fault that do not violate the dominant process relation described by the PCA statistical model could only be detected by T² index.The theoretical conditions of isolatability and identifiability were obtained.The acquired results were then illustrated and verified by monitoring a simulated double-effect evaporator (DEE) process, where 10 different faults were studied.

Key words: 主元分析, 产品质量控制, 故障分离, 故障识别