Research on rapid detection of characteristic parameters of aeroengine blade surface based on laser scanning
Research Square
2023
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
How to quickly and effectively detect and evaluate the profile quality of aeroengine blades and provide technical support for blade manufacturing has become one of the key technical problems in the field of aviation manufacturing. This paper studies the evaluation criteria of medium surface quality in the processing and manufacturing process of aeroengine blades, optimizes and innovates the fast extraction algorithms of various geometric parameters such as aeroengine blade section line, middle arc, front and rear edge center, front and rear edge radius, blade chord length and chord angle, and establishes the evaluation criteria of aeroengine blade surface. According to the geometric relationship of blade chord length and front / rear edge radius in blade section profile, the parameters are solved one by one through optimization algorithm, combined with non-contact laser scanning measurement, and the blade detection efficiency is improved by more than 40%.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know