Trace generation of friction stir welding robot for space weld joint on large thin-walled parts. Issue 6 (17th October 2016)

• Record Type: Journal Article
• Authors: Qi, Ruolong; Zhou, Weijia; Zhang, Huijie; Zhang, Wei; Yang, Guangxin
• Is Part Of: Industrial robot. Volume 43:Issue 6(2016)
• Page Start: 617
• Page End: 627
• Publication Date: 2016-10-17
• Subjects: Path planning -- Friction stir welding -- Robot welding -- Weld joint measurement; Robots, Industrial -- Periodicals; Machinery in the workplace -- Periodicals; 629.892
• DOI: 10.1108/IR-04-2015-0075
• Languages: English
• ISSNs: 0143-991X

Abstract

Abstract : Purpose: The weld joint of large thin-wall metal parts which deforms in manufacturing and clamping processes is very difficult to manufacture for its shape is different from the initial model; thus, the space normals of the part surface are uncertain. Design/methodology/approach: In this paper, an effective method is presented to calculate cutter location points and to estimate the space normals by measuring some sparse discrete points of weld joint. First, a contact-type probe fixed in the end of friction stir welding (FSW) robot is used to measure a series of discrete points on the weld joint. Then, a space curve can be got by fitting the series of points with a quintic spline. Second, a least square plane (LSP) of the measured points is obtained by the least square method. Then, normal vectors of the plane curve, which is the projection of the space curve on the LSP, are used to estimate the space normals of the weld joint curve. After path planning, a post-processing method combing with FSW craft is elaborated. Findings: Simulation and real experiment demonstrate that the proposed strategy, which obtains cutter locations of welding and normals without measuring the entire surface, is feasible and effective for the FSW of large thin-walled complex surface parts. Originality/value: This paper presents a novel method which makes it possible to accurately weld the large thin-wall complex surface part by the FSW robot. The proposed method might be applied to any multi-axes FSW robot similar to the robot studied in this paper.