Abstract
Objective:Solve the problems of low working efficiency and low filling accuracy of beer filling machine.Methods:The structure and working principle of beer filling machine were analyzed, and the control mode based on the weight deviation of secondary supplementary filling was determined; On the basis of PLC controller, using the characteristics of strong anti-interference ability of fuzzy algorithm and good self-adaptability of neural network algorithm, a PID control strategy based on fuzzy neural network was proposed, and simulation analysis and filling test were carried out.Results:Within the set target range, the maximum deviation of filling weight was only 1.7 g, and the filling qualification rate was 100%. Compared with the traditional PID control, the response speed of the algorithm was improved by 55% and the filling accuracy was improved by 50%.Conclusion:The test method can effectively improve the filling accuracy and filling efficiency, and can meet the requirements of stable, fast and reliable operation of automatic production line.
Publication Date
7-20-2022
First Page
104
Last Page
108
DOI
10.13652/j.spjx.1003.5788.2022.90126
Recommended Citation
Wei, LIU
(2022)
"Beer filling precision control technology based on fuzzy neural network,"
Food and Machinery: Vol. 38:
Iss.
4, Article 18.
DOI: 10.13652/j.spjx.1003.5788.2022.90126
Available at:
https://www.ifoodmm.cn/journal/vol38/iss4/18
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