Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Prediction of Maximum Outlet Velocity of Auxiliary Nozzle with Six Orifices Based on PSO-BP

Download188 downloads
  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322855,
        author={Yalong  He and Junqing  Yin and Yongdang  Chen and Xingxuan  Yang and Jianxin  Ma and Keyu  Ni and Chen  Zhang},
        title={Prediction of Maximum Outlet Velocity of Auxiliary Nozzle with Six Orifices  Based on PSO-BP},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={auxiliary nozzle structural parameters maximum outlet velocity pso-bp model prediction introduction},
        doi={10.4108/eai.17-6-2022.2322855}
    }
    
  • Yalong He
    Junqing Yin
    Yongdang Chen
    Xingxuan Yang
    Jianxin Ma
    Keyu Ni
    Chen Zhang
    Year: 2022
    Prediction of Maximum Outlet Velocity of Auxiliary Nozzle with Six Orifices Based on PSO-BP
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322855
Yalong He1, Junqing Yin1,*, Yongdang Chen1, Xingxuan Yang1, Jianxin Ma1, Keyu Ni1, Chen Zhang1
  • 1: Xi’an Polytechnic University
*Contact email: jqyin@xpu.edu.cn

Abstract

In view of the complexity of the auxiliary nozzle structure of air-jet looms, a prediction model between the auxiliary nozzle structure parameters and the maximum exit velocity was established based on PSO-BP. Firstly, the finite element model of the auxiliary nozzle was established by using Ansys software. Secondly, 500 sets of structural parameters were sampled using Latin hypercube sampling, and the corresponding maximum outlet velocity was obtained using the finite element model. Finally, 450 groups of samples are used as the training set, and the remaining 50 groups are used as the test set to establish the PSO-BP prediction model. The results show that the PSO-BP model is effective and accurate to predict the maximum exit velocity of the auxiliary nozzle.