{"title":"基于灰色自举法的高速加工中心热误差动态预测","authors":"Taomei Lv, Fannian Meng, Jiangping Tao","doi":"10.1109/CCDC.2017.7978272","DOIUrl":null,"url":null,"abstract":"Thermal error is always the key factor which affects processing precision of high-speed machine center. How to predict the thermal error of the high-speed machine center, is the prerequisite and foundation of thermal error compensation. To solve this problem, a grey bootstrap model is proposed, which is first used thermal error prediction of high-speed machine center. Experimental study shows that the prediction accuracy is very high using grey bootstrap model, and the maximum, the minimum and the mean of the relative errors of the predicted results are respectively 7.72%, 1.19% and 4.48%, and the reliability of the predicted interval is proved to be 100%. The point prediction and interval prediction are actualized, which solve the problem of dynamic evaluation of thermal error of high-speed machine center.","PeriodicalId":6588,"journal":{"name":"2017 29th Chinese Control And Decision Conference (CCDC)","volume":"140 1","pages":"6130-6133"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic prediction for thermal error of high-speed machine center using grey bootstrap\",\"authors\":\"Taomei Lv, Fannian Meng, Jiangping Tao\",\"doi\":\"10.1109/CCDC.2017.7978272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thermal error is always the key factor which affects processing precision of high-speed machine center. How to predict the thermal error of the high-speed machine center, is the prerequisite and foundation of thermal error compensation. To solve this problem, a grey bootstrap model is proposed, which is first used thermal error prediction of high-speed machine center. Experimental study shows that the prediction accuracy is very high using grey bootstrap model, and the maximum, the minimum and the mean of the relative errors of the predicted results are respectively 7.72%, 1.19% and 4.48%, and the reliability of the predicted interval is proved to be 100%. The point prediction and interval prediction are actualized, which solve the problem of dynamic evaluation of thermal error of high-speed machine center.\",\"PeriodicalId\":6588,\"journal\":{\"name\":\"2017 29th Chinese Control And Decision Conference (CCDC)\",\"volume\":\"140 1\",\"pages\":\"6130-6133\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 29th Chinese Control And Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2017.7978272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 29th Chinese Control And Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2017.7978272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic prediction for thermal error of high-speed machine center using grey bootstrap
Thermal error is always the key factor which affects processing precision of high-speed machine center. How to predict the thermal error of the high-speed machine center, is the prerequisite and foundation of thermal error compensation. To solve this problem, a grey bootstrap model is proposed, which is first used thermal error prediction of high-speed machine center. Experimental study shows that the prediction accuracy is very high using grey bootstrap model, and the maximum, the minimum and the mean of the relative errors of the predicted results are respectively 7.72%, 1.19% and 4.48%, and the reliability of the predicted interval is proved to be 100%. The point prediction and interval prediction are actualized, which solve the problem of dynamic evaluation of thermal error of high-speed machine center.