Intelligent control system for feed production

By designing an intelligent control system in feed production, using particle swarm optimization algorithm and real-time feedback mechanism, the problems of unstable crushing effect and waste of energy in traditional production are solved, and the production efficiency and resource utilization are improved.

CN119717729AInactive Publication Date: 2025-03-28DONGTAI PARIS HARDWARE CO LTD
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Patent Information

Application Number
CN202411880265.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-19
Publication Date
2025-03-28
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

In traditional feed production, it is difficult to dynamically respond to changes in the production environment, resulting in unstable crushing effect, serious energy consumption and low production efficiency.

Method used

Design an intelligent feed production control system, including data collection, data processing, production scheduling optimization, intelligent control, performance evaluation and feedback adjustment modules, and dynamically adjust production parameters and optimize equipment status and resource utilization through particle swarm optimization algorithm and real-time feedback mechanism.

Benefits of technology

The stability and efficiency of the crushing process are improved, energy consumption is reduced, resource utilization is improved, and product quality stability and production cost are reduced.

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Abstract

The invention discloses an intelligent control system for feed production, and relates to the technical field of intelligent control for feed production, a data acquisition module acquires and integrates multi-dimensional data such as raw material flow, crusher rotating speed, production line idle time and energy consumption in real time through a raw material flow monitoring unit and an energy consumption and equipment state monitoring unit. A data set W composed of the parameters can provide comprehensive real-time data support for subsequent optimization scheduling and production control, and it is ensured that key information in the production process is not lost. A denoising processing unit in the data processing module adopts a filtering algorithm, random noise generated in the acquisition process is effectively filtered out, and a missing value is filled by using a mean value filling method, so that a more accurate data denoising set WC is generated. By dynamically regulating and controlling the raw material flow and the equipment running speed, accurate management of energy consumption and continuous optimization of the crushing effect are realized, and the stability of feed quality is ensured.
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