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Modeling and Optimizing the Composite Prepreg Tape Winding Process Based on Grey Relational Analysis Coupled with BP

Bo Deng1, Yaoyao Shi2

  • 1The Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, Ministry of Education, Northwestern Polytechnical University, Xi'an, 710072, China. dengbo1025@outlook.com.

Nanoscale Research Letters
|August 30, 2019
PubMed
Summary
This summary is machine-generated.

Optimizing composite prepreg tape winding for aerospace motors involves fine-tuning heating temperature, tape tension, roller pressure, and winding velocity. This study achieved lower void content and higher tensile strength using advanced analysis methods.

Keywords:
Backpropagation neural networkBat algorithmComposite tape winding processTensile strengthVoid content

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Area of Science:

  • Materials Science
  • Manufacturing Engineering
  • Aerospace Engineering

Background:

  • Composite prepreg tape winding is crucial for manufacturing aerospace motor components.
  • Processing parameters significantly impact the void content and tensile strength of winding products.

Purpose of the Study:

  • To investigate the influence of processing parameters on composite tape winding performance.
  • To identify optimal parameters for reduced void content and enhanced tensile strength.

Main Methods:

  • Grey relational analysis was used to understand parameter influences.
  • A backpropagation neural network modeled the winding process.
  • The bat algorithm optimized the process parameters.

Main Results:

  • Optimal parameters identified: 73.8°C heating temperature, 291.2 N tape tension, 1804.1 N roller pressure, and 9.1 rpm winding velocity.
  • Tensile strength increased from 1215.31 to 1329.62 MPa.
  • Void content decreased from 0.15% to 0.137%.

Conclusions:

  • The integrated approach effectively optimizes composite tape winding parameters.
  • Achieved improvements in tensile strength and reduction in void content validate the method.