Automated design parameter extraction and restoration from 2D propeller drawings
The shipbuilding industry increasingly needs 3D propeller models from 2D drawings for repair, retrofitting, and energy-saving device (ESD) analysis. However, clients often provide only 2D drawings due to security, making manual information extraction for propeller models time-consuming, labor-intensive, and prone to errors. This highlights the need for automated, accurate extraction techniques. This study proposes a line detection and information extraction method to obtain design parameters from 2D propeller drawings. The method converts PDF drawings to images, preprocesses them, and then uses a path-finding algorithm to detect lines and extract information. This extracted data is converted into design parameters like rake, skew, chord length, camber, and thickness through offset data acquisition. Applying this method to propeller drawings significantly reduces time and effort compared to manual work, greatly improving efficiency and restoration accuracy. The method effectively detects complex and overlapping lines, and the quantitative accuracy of the extracted design parameters has been validated, with most parameters showing less than 1 % error. • This study presents a method for propeller design parameters from 2D drawing. • The proposed methods involve line detection techniques in 2D drawing. • This study shows how to acquire design parameters such as rake, skew, and chord length. • The proposed method was verified through comparative validation with an actual model.
Authors
- Seung-Ho Ham (ORCID: https://orcid.org/0000-0001-8226-6029)
- Junsu Park (ORCID: https://orcid.org/0000-0003-1176-2126)
Institutions
- Changwon National University (KR)
Publication Details
- Journal
- International Journal of Naval Architecture and Ocean Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.ijnaoe.2025.100689
- Citations
- 1
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.24