Multi-stage distributed monitoring and diagnosis method for cigarette tobacco making process based on partitioning and stratifying thoughts

Abstract

The invention discloses a multi-stage distributed monitoring and diagnosis method for cigarette tobacco making process based on partitioning and stratifying thoughts. The method comprises: identifyingdifferent monitoring requirements of a standby operation stage and a stable production stage of a cigarette tobacco making process, using thoughts of transverse equipment partitioning and longitudinal time stratifying, to establish a multi-stage distributed monitoring model for key equipment of a Sirox warming and dampening machine and a KLD sheet cut-tobacco drier in a cigarette tobacco making process, to realize single and concurrent abnormity effective detection of the cigarette tobacco making process, and abnormal reasons are accurately identified by a contribution plot method. A monitoring blind area of a standby operation stage of the cigarette tobacco making process is eliminated, catching capability of concurrent abnormity information of the process is improved, and the method canaccurately and effectively monitor and diagnose single and concurrent abnormity of different operation stages of key equipment in the cigarette tobacco making process.

Description

technical field [0001] The invention relates to the field of product quality and equipment integrity monitoring in the process of making shredded tobacco leaves, in particular to a multi-stage distributed monitoring and diagnosis method for the shredded cigarettes making process based on the idea of ​​division and layering. Background technique [0002] With the continuous improvement of the overall strength of my country's tobacco industry, effectively improving the intelligence level and efficient operation of equipment has become the focus of cigarette factories. Condition monitoring and abnormal diagnosis are important means to improve equipment intelligence and efficient operation. At present, the univariate statistical process control method is the main method for equipment status monitoring and abnormal diagnosis in the cigarette shredding process, and the steady-state data in the production stage are analyzed by using rainbow diagram and process capability index. Suc...

AI Technical Summary

Problems solved by technology

This method is aimed at the steady-state data analysis in the production stage, without considering the equipment status monitoring in the standby operation stage before feeding, and there is a monitoring blind spot in the standby operation stage; at the same time, because Sirox and KLD are modeled and monitored as a whole, one of the equipment will appear After the abnormality causes the model to alarm, it will interfere with the status monitoring of another equipment, which limits the ability of this method to capture the concurrent abnormal information in the batch process of shredded leaves

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