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Detecting the normal-direction in automated aircraft manufacturing based on adaptive alignment

In aircraft manufacturing, the vertical accuracy of connection holes is important indicator of the quality of holes making. Aircraft products have high requirements for the vertical accuracy of holes positions. When drilling and riveting are performed by an automatic robotic system, assembly errors,...

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Detalles Bibliográficos
Autores principales: Zhang, Ying, Ding, Hongchang, Zhao, Changfu, Zhou, Yigen, Cao, Guohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450886/
https://www.ncbi.nlm.nih.gov/pubmed/33356951
http://dx.doi.org/10.1177/0036850420981212
Descripción
Sumario:In aircraft manufacturing, the vertical accuracy of connection holes is important indicator of the quality of holes making. Aircraft products have high requirements for the vertical accuracy of holes positions. When drilling and riveting are performed by an automatic robotic system, assembly errors, bumps, offsets and other adverse conditions, can affects the accuracy of manufacturing and detection, and in turn the fatigue performance of the entire structure. To solve this problem, we proposed a technology for detecting the normal-direction based on the adaptive alignment method, built a mathematical model for posture alignment, and studied the calibration method and mechanism of the detection device. Additionally, we investigated techniques for error compensation using an electronic theodolite and other devices when the adaptive method is used for detection. In verification experiments of the method, multiple sets of results demonstrated that the key technical indicators are as follows: normal accuracy <0.5°, average deviation after correction =0.0667°. This method can effectively compensate the errors affecting hole making work in automated manufacturing, and further improve the positioning accuracy and normal-direction detection accuracy of the robot.