Distributed collaborative intelligent control method for rice milling machine and rice milling process

Abstract

The invention discloses a rice mill and a distributed type collaborative intelligent control method for a rice processing rice milling procedure. The distributed type collaborative intelligent controlmethod comprises the steps of obtaining technological detection data of each rice mill; and conducting analysis, judgment, reasoning, decision-making and control action generation on the data. Independent analysis, decision-making and control are conducted on each rice mill, and decision-making and control on a cluster intelligent controller for the whole rice milling procedure; and under the condition that production efficiency is guaranteed, the whole rice milling procedure fully meets the rice milling target control rate and maintains the minimum broke rice increasing rate and the minimummilling reduction rate.

Description

technical field [0001] The invention relates to a rice milling machine, in particular to a rice milling machine and a distributed cooperative control method for the rice processing and rice milling process. Background technique [0002] Rice milling is the core process of rice processing. Only by realizing the intelligent control of the rice milling process can a rice processing smart factory be realized. At present, the status of rice processing in the rice milling process is: [0003] 1. Multi-machine light milling, usually three rice mills (one mill, two mills, three mills), and a few four rice mills. [0004] 2. The evaluation of the process effect of each rice machine is only based on visual inspection, and whether the last rice machine process reaches the processing target is only based on visual inspection. [0005] 3. The control of the rice machine is manual modulation. [0006] 4. The adjustment method of the weight cannot be fine, but only rough adjustment. ...

AI Technical Summary

Problems solved by technology

[0004] 2. The evaluation of the process effect of each rice machine is only based on visual inspection, and whether the last rice machine process reaches the processing target is only based on visual inspection

[0005] 3. The control of the rice machine is manual modulation

[0006] 4. The adjustment method of the weight cannot be fine, only rough modulation

[0007] 5. The coordination point between the optimal state point of each rice machine and the multi-channel rice machine is a complete blind spot

[0008] 6. As the incoming material changes, the rice milling method cannot match accordingly

[0009] 7. All rice machines are traditional mechanical and electrical equipment, and there is no intelligent interface physically, let alone software interface

[0011] 1. The control of each rice mill is isolated, and there is no organic coordination of the multi-path rice milling of "multi-machine light milling"

[0012] 2. Each rice machine itself is also isolated, and there is no communication network between each rice machine

[0013] 3. The rice milling process is isolated and not connected to the industrial Internet of the factory

[0014] 4. Feedback control is usually carried out according to the online energy consumption per unit time or according to the amount of material in the hopper, which ignores the essence of "seeing rice and beating rice" according to the continuous change of incoming materials for rice milling, and does not take the online process detection data as the basis. Intelligent control based on

[0015] 5. Did not consider the complexity and variability of rice milling, did not endow the intelligent system with self-learning function

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