Electrolytic aluminum whole-process monitoring and fault diagnosis system based on multivariate statistic method

Abstract

The invention discloses an electrolytic aluminum whole-process monitoring and fault diagnosis system based on a multivariate statistic method. The system comprises three layers, the bottom layer is used for monitoring key technological parameters, the middle layer is used for monitoring the device running in the electrolytic aluminum process, and the top layer is used for comprehensively monitoring the whole process. The system monitors the bottom layer, the middle layer and the top layer respectively, analyzes measured results comprehensively, and thus guarantees the monitoring pertinence and the accuracy of the monitored results. According to the invention, the separation and integrated monitoring is realized by adopting the concept of monitoring in layers, and further the monitoring pertinence and the accuracy of the monitored results are ensured; forecast before fault, alarming in fault and fault diagnosis and retrospect functions can be realized; the modular design concept is adopted for the off-line modeling and on-line monitoring, and each module performs the corresponding function; not only can the safety production and product quality be ensured, but also the consumption of raw materials and electricity energy can be reduced.

Description

technical field [0001] The invention belongs to the technical field of electrolytic aluminum process monitoring and fault diagnosis, in particular a whole-process monitoring and fault diagnosis of electrolytic aluminum based on a multivariate statistical method that can realize the functions of forecasting before a fault occurs, alarming when a fault occurs, fault diagnosis and fault tracing. diagnostic system. Background technique [0002] Modern science and technology are changing with each passing day, and the modern process industry is gradually developing in the direction of large-scale, complex, continuous and automated. People put forward higher requirements for high-quality, high-yield, low-consumption, and low-pollution process industries, and also put forward stricter requirements for safe production. In actual factory production, it is difficult for workers to know the status of the system from the large amount of collected data. They cannot know in time in the e...

AI Technical Summary

Problems solved by technology

[0005] The present invention solves the problem of monitoring possible faults in the electrolytic aluminum process and ensuring timely alarm and troubleshooting of the faults. The purpose of the present invention is to provide a set of electrolytic aluminum full-process monitoring and fault diagnosis system based on multivariate statistical methods , in order to realize the forecast before the fault occurs, the alarm when the fault occurs, fault diagnosis and fault traceability, ensure safe production and product quality, and reduce the consumption of raw materials and electric energy

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