Solid Propellant Aging Detection Method Based on Impedance Spectroscopy

Abstract:

Aiming at the shortcomings of large volume, high cost and long detection cycle of traditional solid propellant aging detection methods, a solid propellant aging detection method based on impedance spectroscopy is proposed. Firstly, the internal impedance of the solid propellant changes after aging, and a portable solid propellant impedance spectrum acquisition system based on impedance spectroscopy is designed based on the principle of electrochemical impedance spectroscopy, and the real and imaginary parts of the impedance spectrum are obtained. Secondly, in order to reduce the data dimension of the classification algorithm, the KPCA (Nuclear Principal Component Analysis) feature extraction algorithm is used to extract the impedance spectrum features of the solid propellant. Then, according to the impedance spectrum characteristics, the BP neural network is used for classification training, and the correspondence between the impedance spectrum and the aging time is obtained. Finally, the feasibility and effectiveness of the proposed method are verified on the physical platform, and the results show that the proposed method has the advantages of high precision and accurate classification, and can effectively predict the aging degree of solid propellant.

• Periodical: Advanced Materials Research (Volume 1179)
• Pages: 133-144
• DOI: https://doi.org/10.4028/p-hnKN3r
• Online since: January 2024
• Authors: Bin Bin Zhang, Guan Hua Wu, Сhao Bo Chen*, Song Gao
• Keywords: BP Neural Network, Classification Training, Impedance Spectroscopy, KPCA Feature Extraction, Solid Propellant

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