基于模糊神经网络的啤酒灌装精度控制技术
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刘伟(1982—),女,吉林电子信息职业技术学院讲师,硕士。E-mail:liuwei321@126.com

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吉林省科技发展计划项目(编号:20190302099GX)


Beer filling precision control technology based on fuzzy neural network
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    摘要:

    目的:解决目前啤酒灌装机工作效率低、灌装精度不高的问题。方法:分析啤酒灌装机的结构和工作原理,确定以二次补灌的重量偏差为指标的控制方式;在PLC控制器的基础上,利用模糊算法抗干扰能力强以及神经网络算法自适应性好的特点,提出一种基于模糊神经网络的PID控制策略,并进行仿真分析和灌装测试。结果:在设定目标范围内,灌装重量的最大偏差仅为1.7 g,灌装合格率为100%。与传统PID控制相比,该算法的响应速度提高了55%,灌装精度提高了50%。结论:试验方法可有效提高灌装精度和灌装效率,能够满足自动生产线运行稳定、快速、可靠的要求。

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    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.

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刘伟.基于模糊神经网络的啤酒灌装精度控制技术[J].食品与机械,2022,(4):104-108.
LIU Wei. Beer filling precision control technology based on fuzzy neural network[J]. Food & Machinery,2022,(4):104-108.

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  • 在线发布日期: 2022-07-20
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