Abstract: In order to eliminate the blind spots of monitoring at idle running stage in batch process of cut strip processing section and prevent the mutual interference between several pieces of equipment working at abnormal status to communicate with the overall monitoring model at one time, a multi-stage distributed monitoring and trouble diagnosis method was proposed based on the strategy of dividing into blocks horizontally and into layers vertically. According to the different monitoring requirements at idle running stage and steady production stage, the monitoring models for Sirox heating and humidifying machine and KLD thin plate dryer at different stages were separately developed by principal component analysis to monitor equipment abnormality at different stages effectively. Contribution plot method was used to accurately identify the reasons causing abnormality. Validation was conducted on the basis of actual running data of cut strip processing section in Hangzhou Cigarette Factory, the results showed that the proposed method raised the ability of the monitoring models to capture batch process information, monitored and diagnosed equipment abnormalities at different stages accurately and effectively. This method provides a theoretical support for the state monitoring and trouble diagnosis of batch process of primary processing in smart cigarette factories.