Hao Fu, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Shijie Liu, Shaojun Wang
{"title":"A Novel Welding Method for Repairing Surface Defects of Large-Type Rotary Machinery Based on Line Structured Light Detection","authors":"Hao Fu, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Shijie Liu, Shaojun Wang","doi":"10.1115/msec2022-85527","DOIUrl":null,"url":null,"abstract":"\n Large-type rotary machinery is the core components of national major projects which is widely used aviation, electric power, metallurgy, energy and construction machinery industries. Surface defects of Large-type rotary machinery such as cracks and pits are usually processed into groove with a certain shape first, and then the processed groove is repaired by manual welding. This manual welding repair method has a low level of automation, and the repair quality of the groove is difficult to guarantee. Therefore, this paper proposes a novel welding method for repairing surface defects of Large-type rotary machinery which uses the Kollmorgen Joint Modular Robot to complete the welding repair of the processed groove. Firstly, the groove point cloud data collected by Line structured light sensor is processed by the designed algorithm to obtain the contour characteristics of the groove. Then, the arrangement of welding pass is completed based on contour characteristics of the groove. Finally, the trajectory of the welding robot is determined by the position of welding pass. The planned trajectory verification is completed on the simulation experiment platform and the result shows the accuracy and reliability of the planned trajectory which has certain theoretical and practical significance for realizing the automation of on-site maintenance of Large-type rotary machinery.","PeriodicalId":45459,"journal":{"name":"Journal of Micro and Nano-Manufacturing","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Micro and Nano-Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/msec2022-85527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
Large-type rotary machinery is the core components of national major projects which is widely used aviation, electric power, metallurgy, energy and construction machinery industries. Surface defects of Large-type rotary machinery such as cracks and pits are usually processed into groove with a certain shape first, and then the processed groove is repaired by manual welding. This manual welding repair method has a low level of automation, and the repair quality of the groove is difficult to guarantee. Therefore, this paper proposes a novel welding method for repairing surface defects of Large-type rotary machinery which uses the Kollmorgen Joint Modular Robot to complete the welding repair of the processed groove. Firstly, the groove point cloud data collected by Line structured light sensor is processed by the designed algorithm to obtain the contour characteristics of the groove. Then, the arrangement of welding pass is completed based on contour characteristics of the groove. Finally, the trajectory of the welding robot is determined by the position of welding pass. The planned trajectory verification is completed on the simulation experiment platform and the result shows the accuracy and reliability of the planned trajectory which has certain theoretical and practical significance for realizing the automation of on-site maintenance of Large-type rotary machinery.
期刊介绍:
The Journal of Micro and Nano-Manufacturing provides a forum for the rapid dissemination of original theoretical and applied research in the areas of micro- and nano-manufacturing that are related to process innovation, accuracy, and precision, throughput enhancement, material utilization, compact equipment development, environmental and life-cycle analysis, and predictive modeling of manufacturing processes with feature sizes less than one hundred micrometers. Papers addressing special needs in emerging areas, such as biomedical devices, drug manufacturing, water and energy, are also encouraged. Areas of interest including, but not limited to: Unit micro- and nano-manufacturing processes; Hybrid manufacturing processes combining bottom-up and top-down processes; Hybrid manufacturing processes utilizing various energy sources (optical, mechanical, electrical, solar, etc.) to achieve multi-scale features and resolution; High-throughput micro- and nano-manufacturing processes; Equipment development; Predictive modeling and simulation of materials and/or systems enabling point-of-need or scaled-up micro- and nano-manufacturing; Metrology at the micro- and nano-scales over large areas; Sensors and sensor integration; Design algorithms for multi-scale manufacturing; Life cycle analysis; Logistics and material handling related to micro- and nano-manufacturing.