A visual measurement method of the three-dimensional coordinates of the center of forgings with asymmetric flash for the intelligent hammer die forging. (31st March 2023)

• Record Type: Journal Article
• Authors: Wang, Aiming; Zhang, Zihang; Qiao, Runtian
• Is Part Of: Measurement. Volume 210(2023)
• Publication Date: 2023-03-31
• Subjects: Automated hammer die forging -- Malposition phenomenon -- Binocular vision localization; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2023.112581
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A visual measurement of the center of forgings with asymmetric flash is studied. Two novel methods are proposed for the quick judgement of malpositioned forgings. Experiments are conducted for the validation of the proposed method. Influence of distance between the camera and forging on the measurement is studied. Abstract: Hammer die forging is a widely used mechanical manufacturing technology. Although it is easy to realize the automation of cutting and heating raw material, trimming the forging flash, and shaping the forgings in the processing of hammer die forging, it is difficult to achieve the automation of the forging process of hammer die forging, which is critical to the automated hammer die forging. It is because of the malposition phenomenon in which the forgings are often extracted out of the lower die cavity. Manual judgement of the phenomenon and manual clamping of the malpositioned forging are required to reset the forging. To achieve the automated forging process, it is necessary to identify the three-dimensional coordinates of the forging centre. However, the asymmetric flash of the forging reduces the localization accuracy. Therefore, a bidirectional correction and binocular vision localization (BCBVL) algorithm is proposed in this paper. However, identifying whether the malposition phenomenon occurs by the BCBLV method is time-consuming and can affect the execution of the subsequent processes such as the trimming and shaping processes. Hence, two methods based on the forging angle and the forging nonoverlapping area are proposed to obtain the fast judgement of the malpositioned forging. Experiments are conducted using a test bench composed of a binocular camera, an industrial manipulator, a 3D-printed die cavity, and a scraper forging of the coal mine scraper conveyor. The results indicate that the average localization error of BCBVL method is 7.31 mm in the left camera coordinate system and is 8.89 mm in the manipulator coordinate system. The two proposed fast judgement methods of the malpositioned forging take 0.32 s and 0.88 s, respectively. The study provides coordinates for the manipulator to grasp malpositioned forgings to achieve the automated forging process of hammer die forging.