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Intelligent logistics system of steel bar warehouse based on ubiquitous information 被引量:4
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作者 Hai-nan He Xiao-chen Wang +6 位作者 Gong-zhuang Peng Dong Xu Yang Liu Min Jiang Ze-dong Wu Da Zhang He Yan 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2021年第8期1367-1377,共11页
Internet of Things and artificial intelligence technology are the key elements of the intelligent construction of iron and steel production warehouse. This paper puts forward a whole set of intelligent scheme for bar ... Internet of Things and artificial intelligence technology are the key elements of the intelligent construction of iron and steel production warehouse. This paper puts forward a whole set of intelligent scheme for bar warehouse crane for the guidance of metallurgical process engineering, including cluster rapid self-awareness technology of the smart crane, precise self-executing technique of crane with rigid-flexible hybrid structure, multi-body system kinematics model of the smart crane sling and the swing characteristics model at different azimuth, antiswing control technology based on the optimization objective function, the vehicle model recognition system based on lidar, and the clustering crane dynamic scheduling method based on multi-agent reinforcement learning. The complete intelligent logistics system of the bar warehouse has changed the original operation mode of the warehouse area and realized the unmanned operation and intelligent scheduling of the crane,which is of great significance for improving the production efficiency, reducing the production cost, and improving the product quality. 展开更多
关键词 intelligent warehouse CRANE vehicle identification anti-pendulum control multi-agent reinforcement learning
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Warehouse Environment Parameter Monitoring System and Sensor Error Correction Model Based on PSO-BP 被引量:5
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作者 Lin Sen Wang Guanglong +3 位作者 Chen Yingjie Wang Le Qiao Zhongtao Gao Fengqi 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2017年第3期333-340,共8页
The warehouse environment parameter monitoring system is designed to avoid the networking and high cost of traditional monitoring system.A sensor error correction model which combines particle swarm optimization(PSO)w... The warehouse environment parameter monitoring system is designed to avoid the networking and high cost of traditional monitoring system.A sensor error correction model which combines particle swarm optimization(PSO)with back propagation(BP)neural network algorithm is established to reduce nonlinear characteristics and improve test accuracy of the system.Simulation and experiments indicate that the PSO-BP neural network algorithm has advantages of fast convergence rate and high diagnostic accuracy.The monitoring system can provide higher measurement precision,lower power consume,stable network data communication and fault diagnoses function.The system has been applied to monitoring environment parameter of warehouse,special vehicles and ships,etc. 展开更多
关键词 Warehouse warehouse correction networking swarm terminals hidden acceleration normalized intelligent
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