دورية أكاديمية
Research on Micro/Nano Surface Flatness Evaluation Method Based on Improved Particle Swarm Optimization Algorithm
| العنوان: | Research on Micro/Nano Surface Flatness Evaluation Method Based on Improved Particle Swarm Optimization Algorithm |
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| المؤلفون: | Han Shu, Chunlong Zou, Jianyu Chen, Shenghuai Wang |
| المصدر: | Frontiers in Bioengineering and Biotechnology, Vol 9 (2021) |
| بيانات النشر: | Frontiers Media S.A., 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Biotechnology |
| مصطلحات موضوعية: | flatness error, micro/nano surface, improved particle swarm optimization algorithm, minimum zone method, uncertainty, AFM, Biotechnology, TP248.13-248.65 |
| الوصف: | Flatness error is an important factor for effective evaluation of surface quality. The existing flatness error evaluation methods mainly evaluate the flatness error of a small number of data points on the micro scale surface measured by CMM, which cannot complete the flatness error evaluation of three-dimensional point cloud data on the micro/nano surface. To meet the needs of nano scale micro/nano surface flatness error evaluation, a minimum zone method on the basis of improved particle swarm optimization (PSO) algorithm is proposed. This method combines the principle of minimum zone method and hierarchical clustering method, improves the standard PSO algorithm, and can evaluate the flatness error of nano scale micro/nano surface image data point cloud scanned by atomic force microscope. The influence of the area size of micro/nano surface topography data on the flatness error evaluation results is analyzed. The flatness evaluation results and measurement uncertainty of minimum region method, standard least squares method, and standard PSO algorithm on the basis of the improved PSO algorithm are compared. Experiments show that the algorithm can stably evaluate the flatness error of micro/nano surface topography point cloud data, and the evaluation result of flatness error is more reliable and accurate than standard least squares method and standard PSO algorithm. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2296-4185 08671494 |
| Relation: | https://www.frontiersin.org/articles/10.3389/fbioe.2021.775455/full; https://doaj.org/toc/2296-4185 |
| DOI: | 10.3389/fbioe.2021.775455 |
| URL الوصول: | https://doaj.org/article/5fbfc9d08671494d9161618d49701064 |
| رقم الأكسشن: | edsdoj.5fbfc9d08671494d9161618d49701064 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 22964185 08671494 |
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| DOI: | 10.3389/fbioe.2021.775455 |