{"title":"基于视觉的龙门起重机系统控制","authors":"A. Okubanjo, O. Oyetola, O. Adekomaya","doi":"10.18038/AUBTDA.420980","DOIUrl":null,"url":null,"abstract":"Heavy materials handling requires a sophisticated tool for efficient and optimum operations. In recent times, gantry cranes are considered as a dependable choice in terms of handling capacity, effectiveness, timeliness and safety. However, positioning of a trolley to the desired set point as fast as possible within minimum time without overshoot and payload induced oscillation have remained obstacles in crane dynamic control. Several control algorithms have been proposed, tested and implemented based on classical control. Recently, vision control has been introduced in the field of mechatronics as a bridging gap with little or no impact. In this paper, a vision based software control model is proposed such that webcam serves as a capturing sensor and the National Instrument LabVIEW is used as a programming tool for both image processing and crane control. Subsequently, the results of the proposed algorithm are experimentally validated by step increase in the trolley position. According to the results analysis, it is evident that the webcam performance is at an optimum level when compared with the installed sensor in positioning the trolley and minimizing the payload oscillation.","PeriodicalId":7757,"journal":{"name":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"VISION BASED CONTROL OF GANTRY CRANE SYSTEM\",\"authors\":\"A. Okubanjo, O. Oyetola, O. Adekomaya\",\"doi\":\"10.18038/AUBTDA.420980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heavy materials handling requires a sophisticated tool for efficient and optimum operations. In recent times, gantry cranes are considered as a dependable choice in terms of handling capacity, effectiveness, timeliness and safety. However, positioning of a trolley to the desired set point as fast as possible within minimum time without overshoot and payload induced oscillation have remained obstacles in crane dynamic control. Several control algorithms have been proposed, tested and implemented based on classical control. Recently, vision control has been introduced in the field of mechatronics as a bridging gap with little or no impact. In this paper, a vision based software control model is proposed such that webcam serves as a capturing sensor and the National Instrument LabVIEW is used as a programming tool for both image processing and crane control. Subsequently, the results of the proposed algorithm are experimentally validated by step increase in the trolley position. According to the results analysis, it is evident that the webcam performance is at an optimum level when compared with the installed sensor in positioning the trolley and minimizing the payload oscillation.\",\"PeriodicalId\":7757,\"journal\":{\"name\":\"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18038/AUBTDA.420980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anadolu University Journal of Science and Technology-A Applied Sciences and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18038/AUBTDA.420980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heavy materials handling requires a sophisticated tool for efficient and optimum operations. In recent times, gantry cranes are considered as a dependable choice in terms of handling capacity, effectiveness, timeliness and safety. However, positioning of a trolley to the desired set point as fast as possible within minimum time without overshoot and payload induced oscillation have remained obstacles in crane dynamic control. Several control algorithms have been proposed, tested and implemented based on classical control. Recently, vision control has been introduced in the field of mechatronics as a bridging gap with little or no impact. In this paper, a vision based software control model is proposed such that webcam serves as a capturing sensor and the National Instrument LabVIEW is used as a programming tool for both image processing and crane control. Subsequently, the results of the proposed algorithm are experimentally validated by step increase in the trolley position. According to the results analysis, it is evident that the webcam performance is at an optimum level when compared with the installed sensor in positioning the trolley and minimizing the payload oscillation.