Electrogalvanizing zinc coating thickness BP neural network control method and application in PLC thereof

Abstract

The invention relates to an electrogalvanizing zinc coating thickness BP neural network control method and an application in PLC thereof. The method includes the following steps of: (1) collecting electrogalvanizing sample data; (2) establishing BP neural network; (3) BP neural network learning and training; and (4) recording the trained BP neural network in a PLC controller. The adoption of an electrogalvanizing zinc coating thickness BP neural network controller designed by the invention can control galvanizing thickness with high accuracy, effectively inhibit industrial interference, and has intelligent self-adaptability, and good accuracy and fault-tolerance.

Description

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AI Technical Summary

Benefits of technology

This technology helps create precise coatings on steel materials that are less likely to be affected during manufacturing processes or use than usual. It also allows for efficient adaptation based upon changes made over time without losing its effectiveness due to factors like temperature fluctuations.

Problems solved by technology

This patented describes how in order to improve the quality of galvanization by adjusting the amount or concentration of metal added during plating process. However, current methods have limitations that can lead to issues with accuracy when trying to achieve this objective.

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