Method for monitoring and diagnosing super-high-speed small box packaging machine having multiple condition characteristic

Abstract

The invention discloses a method for monitoring and diagnosing super-high-speed small box packaging machine having multiple condition characteristics. Aiming for the problem that the multiple working condition characteristics and the working condition are generally unknown in the working process, the method comprises steps of calculating stability factors based on a sliding window to identify different working conditions, adopting a self-adaptive clustering method to divide the stable working condition into a plurality of stable working condition data clusters, utilizing a PCA method to establish a monitoring model for each stable working condition data cluster by using a PCA method, determining the type of the working condition according to the data stable factor inside the current sliding window in the process of multiple working condition monitoring, if the working condition is a transition working condition, assigning 0 as the monitoring statistics, if the working condition is a stable working condition, calculating the distances between current effective data and the various cluster centers to obtain a matched PCA monitoring model to perform real time monitoring, and adopting a contribution plot to determine the main process variable causing the fault when any statistics exceeds the time frame.

Description

technical field [0001] The invention relates to the statistical monitoring modeling, state monitoring and diagnosis technology of the ultra-high-speed small box packaging machine H1000 of Italian G.D company. Background technique [0002] With the globalization of the tobacco industry, new laws and regulations, and major changes in the external environment in recent years, China Tobacco is facing increasingly severe competitive pressure and social pressure. Under the premise of ensuring product quality, effectively improving the intelligence level and efficient operation of equipment has become the focus of cigarette factories. Intelligent, that is, production equipment has the functions of perception, analysis, reasoning and decision-making; efficient operation, that is, consume less resources to produce more and better products within a specified time. The intelligence level and efficient operation capability of cigarette factory equipment are inseparable from the degree ...

AI Technical Summary

Problems solved by technology

The operating efficiency of ultra-high-speed packaging equipment in Hangzhou Cigarette Factory in 2014 was only 70.08%. The current equipment status monitoring method can no longer meet the actual needs of cigarette production. There is an urgent need for a practical and effective ultra-high-speed small box packaging machine H1000 diagnosis method

[0004] In order to solve the problem that G.D Company’s ultra-high-speed packaging equipment bottom layer PLC parameter data is difficult to obtain, Hangzhou Cigarette Factory (Zhu Liming, Qian Jie, Wang Qi, Li Yuliang, Li Yong. A data acquisition system for ultra-high-speed packaging machines: China, CN204056360U[P] .2014-12-31.) Proposed a data collection method for ultra-high-speed packaging equipment based on Beckoff soft PLC. Through the analysis of the underlying PLC source code and library files of the equipment, some parameters of the ultra-high-speed small box packaging machine H1000 can be collected data, thus providing a wealth of operating data for the implementation of the ultra-high-speed small box packaging machine H1000 status monitoring and diagnosis with multi-working condition characteristics based on the multivariate statistical analysis method

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