Title: Quality prediction method for plasticising process of single-base gun propellant based on modified multiway JY-PLS transfer model

Authors: Mingyi Yang; Junyi Wang; Di Huang; Zhigang Xu; Tingjiang Yu; Shubo Chen

Addresses: Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, 110169, China; University of Chinese Academy of Sciences, Beijing, 100049, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China ' Jinhang Digital Technology Co., Ltd., Beijing, 100028, China ' Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China ' Luzhou North Chemical Industries Co., Ltd., Luzhou, 646003, China ' Luzhou North Chemical Industries Co., Ltd., Luzhou, 646003, China

Abstract: To solve the problem that the data of new plasticising process of single-base gun propellant is not enough to build an accurate model for predicting the product quality, a modified multiway joint-Y partial least squares (MMJY-PLS) transfer model for final quality prediction in the plasticising process is proposed. Firstly, the modelling efficiency of the new plasticising process is improved by transfer learning using the plasticising process data of similar source domain. Secondly, the internal structure of the JY-PLS transfer model is improved so that the regression coefficients of the source and the target domain are no longer the same, and the prediction performance of the model is further improved. Finally, the MMJY-PLS process transfer model was applied to predict the final quality index in the plasticising process of two single-base gun propellant products, and the experimental results show its effectiveness.

Keywords: gun propellant; plasticising process; JY-PLS; quality prediction; model transfer; online update.

DOI: 10.1504/IJMIC.2022.125547

International Journal of Modelling, Identification and Control, 2022 Vol.40 No.4, pp.294 - 304

Received: 23 Sep 2021
Accepted: 27 Oct 2021
Published online: 14 Sep 2022 *

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