摘要
在散状物料运输过程中,经常出现带式输送机跑偏现象。基于多智能体协同控制思想,采用STOA-PNN方法,设计了带式输送机自适应纠偏系统。通过STOA算法优化概率神经网络(PNN)的平滑参数,将传感器采集到的不同情况下的偏移数据作为输入,PNN控制器根据输送带偏移情况,自适应地输出控制参数,结合调整电机完成输送机运行过程的动态纠偏。现场应用表明,基于STOA-PNN方法的纠偏系统应用到带式输送机上,有效避免了偏移故障的发生,保证了输送机稳定运行,实现无偏移运输。
In the process of bulk material transportation,belt conveyor runout phenomenon often occurs.Based on the idea of multi-intelligent body cooperative control,the STOA-PNN method is used to design the belt conveyor adaptive deflection correction system.The smoothing parameters of the probabilistic neural network(PNN)are optimized by the STOA algorithm,and the offset data collected by the sensors under different conditions are used as input.The PNN controller adaptively outputs the control parameters according to the belt offset,and completes the dynamic deflection correction of the conveyor operation process in combination with the adjustment motor.The field application shows that the deflection correction system based on STOA-PNN method applied to the belt conveyor effectively avoids the occurrence of deflection failure,ensures the stable operation of the conveyor and realizes deflection-free transportation.
出处
《工业控制计算机》
2023年第1期34-36,共3页
Industrial Control Computer
基金
淮北市重大科技专项(Z2020004)
国家自然科学基金项目(51874010)。
