基于模糊神经网络的啤酒灌装精度控制技术

Beer filling precision control technology based on fuzzy neural network

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。

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.