基于模糊神经网络的啤酒灌装精度控制技术

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。

Beer filling precision control technology based on fuzzy neural network

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.