摘要
为解决食品包装过程中分拣困难、漏拣和误拣率高等问题,基于并联机器人设计一种食品分拣控制系统。食品分拣设备主要包括并联机器人、夹持器、工业相机、LED光源、传送带等。以并联机器人为研究对象,设计一种模糊神经网络控制器,实现在线调节PID控制参数。通过改进粒子群优化算法,实现神经网络初始权值最优化处理,并开展相关试验研究。结果表明,系统漏抓和误抓率非常低,最大为0.1%;并联机器人的食品分拣控制系统具有好的稳定性和可靠性;抓取精度较高;能够满足食品包装要求。
In order to solve the problems of difficult sorting,high rate of omission and mislabeling in the process of food packaging,a food sorting control system based on parallel robots was designed.Food sorting equipment mainly includes parallel robot,gripper,industrial camera,LED light source,conveyor belt,etc.A fuzzy neural network controller was designed to adjust PID control parameters on-line.By improving the particle swarm optimization algorithm,the initial weight of neural network was optimized.The relevant experimental study was carried out.The experimental results show that the system picking error rate is very low,and the maximum is about 0.1%.The food sorting control system of the parallel robot has very good stability and reliability.The grasping precision is high,and be able to meet food packaging requirements.
作者
郝琳
张坤平
HAO Lin;ZHANG Kunping(Xuchang Electrical Vocational College,Xuchang 461000)
出处
《食品工业》
CAS
北大核心
2020年第4期209-212,共4页
The Food Industry
关键词
并联机器人
食品分拣
模糊神经网络控制
粒子群优化
parallel robot
food sorting
fuzzy neural network control
particle swarm optimization
