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Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying.
Yao, Yijun; Liu, Shaowu; Planche, Marie Pierre; Deng, Sihao; Liao, Hanlin.
Afiliação
  • Yao Y; ICB PMDM LERMPS UMR 6303, CNRS, Université de Bourgogne Franche-Comté, UTBM, Belfort, France.
  • Liu S; ICB PMDM LERMPS UMR 6303, CNRS, Université de Bourgogne Franche-Comté, UTBM, Belfort, France.
  • Planche MP; ICB PMDM LERMPS UMR 6303, CNRS, Université de Bourgogne Franche-Comté, UTBM, Belfort, France.
  • Deng S; ICB PMDM LERMPS UMR 6303, CNRS, Université de Bourgogne Franche-Comté, UTBM, Belfort, France.
  • Liao H; ICB PMDM LERMPS UMR 6303, CNRS, Université de Bourgogne Franche-Comté, UTBM, Belfort, France.
J Therm Spray Technol ; 31(1-2): 46-58, 2022.
Article em En | MEDLINE | ID: mdl-37520911
ABSTRACT
In thermal spray process, the characteristics of in-flight particles (velocity and temperature) play an important role regarding the microstructure of the deposit and thus the coating performances. The implementation of diagnostic devices is necessary to measure such characteristics. Many imaging systems and algorithms have been developed for identifying and tracking in-flight particles. However, these current image systems have significant limitations in terms of accuracy for example. One key to solving the tracking problem is to get an algorithm that can effectively distinguish different particles in the same image frame at the same time. This study aims to develop an algorithm capable of identifying a large number of in-flight particles sprayed by thermal process. The results show that the noise and vignettes could be successfully treated, particles are clearly recognized in the background, leading to properly measuring the sizes and positions of the particle versus time. The proposed algorithm has a higher recognition rate and recognition range than other algorithms, which will provide a reasonable basis for subsequent calculation and processing.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Therm Spray Technol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Therm Spray Technol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: França