The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Blade Inspection System
Abstract
The manufacturing quality of turbine blade is the key problem for an engine. Blade inspection is the important safeguard to blade quality. This paper presented some key techniques of a blade inspection system. First of all, the scan planning strategy and the results for a blade for getting as complete as possible data are described. Secondly, the data processing methodologies for the laser measurement data are put forward. Thirdly,the innovated methods of parameter extraction strategy, work flow and the key techniques are analyzed in details. Finally, the inspection results are illustrated. It shows that the presented solutions of the developed blade inspection are valid, practical and efficient.
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In the citing paper
“Furthermore, most research focuses on defect detection on turbine blades rather than compressor blades. This encompasses mainly crack detection [9,33,37,38,42], as this is the most critical type of defect and the main source of failure.”
From Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection (2021) · cites this paper as [37]
Citations
Cites
Automatic inspection of turbine blades using a 3-axis CMM together with a 2-axis dividing head
Chang, H.-C., & Lin, A. C. (2005) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-003-1877-6 · Cited by 52
Chen, T., Du, X., Jia, M., et al. (2010) · International Conference on Computer Engineering and Technology · doi:10.1109/iccet.2010.5486027 · Cited by 9
Self-citationData Processing Methodology for Laser Measurement Point Cloud
Tian, 陈. C. (2011) · Laser & Optoelectronics Progress · doi:10.3788/lop48.091202 · Cited by 5
Flagged first, then by citations
Research works printed but not linked: 1
- Yan Liu. Blade Manufacturing Technology. Beijing: Science Press, 2002. (in Chinese).
Cited by
Sorted by citations
Automated Defect Detection and Decision-Support in Gas Turbine Blade Inspection
Aust, J., Shankland, S., Pons, D., Mukundan, R., & Mitrovic, A. (2021) · Aerospace · doi:10.3390/aerospace8020030 · Cited by 66
Metadata
- Authors
- Chen, T.
- Affiliations
- Shanghai Dianji University
- Venue
- Applied Mechanics and Materials
- Publisher
- Trans Tech Publications, Ltd.
- Published
- 2013-09
- Volume
- 423-426
- Pages
- 2386-2389
- ISSN
- 1660-9336 (ISSN-L)
- 1662-7482
- OpenAlex
- W1997497947
- Cited by
- 2
- References
- 3
- Citations by year
- 2022: 1 · 2021: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Applied Mechanics and Materials (publishedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Measurement and Metrology Techniques
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
- Keywords
- turbine blade inspection, laser scanning, scan planning, parameter extraction, aircraft engine components
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