精馏塔开车过程混合故障诊断策略

化工过程有很多过渡过程,例如开停车、不同稳态间转换和间歇过程。这些过程的非线性很强，变化范围大，需要有经验的操作员连续监控。近年来对过渡过程的故障诊断比较通用的方法是多变量统计方法，其优点是能快速检测异常的发生，但是用贡献图分析方法的诊断效果往往不够理想。本文结合主元分析和动态时间规整的方法，提出了一个开车过程的混合故障诊断策略，提高了故障诊断效率。一个实验室规模的精馏塔开车过程的在线故障诊断应用实例表明:该策略具有比较好的早期故障诊断效果。

A Hybrid Fault Diagnosis Strategy for Distillation Column Startup Process

Chemical processes usually have many transitions, e.g., startup and shutdown, transfer ring between different modes. These processes are highly nonlinear with large variations and require continuous monitoring by experienced operators. Multivariate statistical methods (MSM) is a popular monitoring method for transition processes. The main advantage of MSM is the quick detection of abnormal events, but the contribution plot analysis cannot obtain better accuracy and reliability for fault diagnosis. A hybrid fault diagnosis strategy is proposed in this paper by combining principal component analysis (PCA) and on-line dynamic time warping. By means of a simulation experiment of the startup process of a laboratory scale distillation column case, the performance of the hybrid fault diagnosis strategy is demonstrated.