基于扰动观测器和神经网络的自动门系统安全性优化研究

Safety Improvement of Automatic Gate System Based on DisturbanceObserver and Neural Network

在传统的自动门系统中,只有安装在外部的安全传感器才能检测到自动门中的干扰或碰撞,导致了很多安全事故,因此有必要对自动门的安全性进行改进。基于此,提出了补充外部安全传感器的方法,通过自动建模设计一个扰动观测器,搭建神经网络,并提出一种算法,比较观察到的扰动和神经网络输出的误差。通过实验验证了该技术的有效性和可行性,证明此种方法可以预测安全事故,有效提高自动门的安全性。

For traditional automatic doors,only the external safety sensor can detect the interference or collision in the automatic doors,which has brought a lot of safety accidents,therefore,it is necessary to improve the safety of the automatic doors.The safety improvement of automatic doors was discussed by adding supplementing external safetysensor.Adisturbance observer was designed by automatic modeling,and aneural network was set up with a new algorithm.The error was observed by comparison the observed disturbance with the out put of the neural network.The effectiveness and feasibility of this technology were verified by experiments,which proved that this method can effectively improve the security of automatic doors.