{"title":"Prediction of Maximum Outlet Velocity of Auxiliary Nozzle with Six Orifices Based on PSO-BP","authors":"Yalong He, Junqing Yin, Yongdang Chen, Xingxuan Yang, Jianxin Ma, Keyu Ni, Chen Zhang","doi":"10.4108/eai.17-6-2022.2322855","DOIUrl":null,"url":null,"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.","PeriodicalId":156653,"journal":{"name":"Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eai.17-6-2022.2322855","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.