Cargando…
Material Classification and Aging Time Prediction of Structural Metals Using Laser-Induced Breakdown Spectroscopy Combined with Probabilistic Neural Network
In this paper, laser-induced breakdown spectroscopy (LIBS) combined with a probabilistic neural network (PNN) was applied to classify engineering structural metal samples (valve stem, welding material, and base metal). Additionally, utilizing data from the plasma emission spectrum generated by laser...
Autores principales: | Wang, Qian, Li, Guowen, Hang, Yuhua, Chen, Silei, Qiu, Yan, Zhao, Wanmeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456602/ https://www.ncbi.nlm.nih.gov/pubmed/37629889 http://dx.doi.org/10.3390/ma16165599 |
Ejemplares similares
-
Benchmark classification dataset for laser-induced breakdown spectroscopy
por: Képeš, Erik, et al.
Publicado: (2020) -
Laser-Induced Breakdown Spectroscopy Combined with Nonlinear Manifold Learning for Improvement Aluminum Alloy Classification Accuracy
por: Harefa, Edward, et al.
Publicado: (2022) -
Application of Laser-Induced Breakdown Spectroscopy for Depth Profiling of Multilayer and Graded Materials
por: Królicka, Agnieszka, et al.
Publicado: (2023) -
Heavy metal detection in mulberry leaves: Laser-induced breakdown spectroscopy data
por: Yang, Liang, et al.
Publicado: (2020) -
Discrimination of Grape Seeds Using Laser-Induced Breakdown Spectroscopy in Combination with Region Selection and Supervised Classification Methods
por: He, Yong, et al.
Publicado: (2020)