Rapid Detection of Stabilizer Content in Double‐Base Propellant Based on Artificial Neural Network Combined With Near‐Infrared Spectroscopy

ABSTRACT During long‐term storage, double‐base propellants are prone to chemical decomposition of internal nitrate esters, leading to decreased burn rate, reduced strength, and degraded ballistic performance. Adding an appropriate amount of Centralite‐II is crucial for ensuring storage safety. This...

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Veröffentlicht in:	Journal of chemometrics 2024-12, Vol.38 (12), p.n/a
Hauptverfasser:	Ouyang, Dihua, Cui, Tianyu, Zhang, Qiantao, Dai, Haoxiang, Qin, Xiaowen, Hu, Yaoli
Format:	Artikel
Sprache:	eng
Schlagworte:	Antiballistic materials Artificial intelligence Artificial neural networks Back propagation networks component model content of Centralite‐II double‐base propellant Energetic materials Esters Infrared spectroscopy machine learning Near infrared radiation near‐infrared spectroscopy (NIRS) Neural networks Nitrate esters Principal components analysis Propellant storage Propellants Spectrum analysis
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