Analysis of data patterns of interwoven meltblown nonwoven materials based on polynomial fitting

Qiancheng Tan; Jiaoxia Huang; Sixuan Wu; Yonghui Qin

doi:10.1117/12.2685984

28 July 2023 Analysis of data patterns of interwoven meltblown nonwoven materials based on polynomial fitting

Qiancheng Tan, Jiaoxia Huang, Sixuan Wu, Yonghui Qin

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127563S (2023) https://doi.org/10.1117/12.2685984
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

The meltblown nonwoven material (MNM) is an important raw material for mask production. With good filtration performance, its production process is simple, low cost, and light quality. The research on the process parameters and structural variables of the MNM is widely concerned by domestic and foreign enterprises, and the relationship between structural variables and product performance is also. To the end, we study the process parameters and product performance of the MNM by using some mathematical methods for the high quality and high efficiency of the industry. We use a multiple nonlinear regression model to build a statistical model based on the data provided by the enterprise to reveal the variation pattern between process parameters and structural variables. The coefficient of decidability was calculated , and the correlation coefficient was above 0.9, which proved the accuracy of the model. Finally, in order to explore the relationship between structural variables and product performance, we used MATLAB to make a correlation four-dimensional diagram, used fitting polynomials to finally fit a quadratic correlation function, and used Monte Carlo multi-objective planning programming to obtain the maximum filtration efficiency of 96.8272% when the acceptance distance was 39.5cm and the hot air speed was 1188r/min.

Citation Download Citation

Qiancheng Tan, Jiaoxia Huang, Sixuan Wu, and Yonghui Qin "Analysis of data patterns of interwoven meltblown nonwoven materials based on polynomial fitting", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127563S (28 July 2023); https://doi.org/10.1117/12.2685984

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KEYWORDS

Resistance

Statistical analysis

Porosity

Data modeling

MATLAB

Data analysis

Monte Carlo methods

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