Research and Design of An Automatic Monitoring Technology for Composite Riveting Process
- DOI
- 10.2991/978-94-6463-514-0_72How to use a DOI?
- Keywords
- composite; riveting process; intelligent inspection
- Abstract
To solve the problems such as difficulty in inspection and inefficiency of quality inspection in the composite riveting process, this paper studies a method of data monitoring during riveting. According to this method, a pressure sensor and a flowmeter are mounted on the riveting tool using integrated development techniques. During riveting, sensor signals are collected during the riveting to obtain the deformation length and riveting force of the rivets during the rivet forming indirectly, so as to draw the curves of riveting force and displacement during the rivet forming. The riveting curves are analyzed by an empirical threshold method to determine the riveting quality. The results show that this method is suitable for monitoring the composite riveting process and can provide effective quality assurance for its riveting.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yu Liu AU - Lin Yang AU - Wei Li AU - Yun-Long Jia AU - Long Guo AU - Xue-Hui Liao PY - 2024 DA - 2024/09/28 TI - Research and Design of An Automatic Monitoring Technology for Composite Riveting Process BT - Proceedings of the 2024 7th International Symposium on Traffic Transportation and Civil Architecture (ISTTCA 2024) PB - Atlantis Press SP - 741 EP - 750 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-514-0_72 DO - 10.2991/978-94-6463-514-0_72 ID - Liu2024 ER -