Prediction of Yarn Unevenness Based on BP Neural Network

Hui Jun Li; Xin Hou Wang

doi:10.4028/www.scientific.net/AMR.627.329

Paper Titles

Influence of Mole Ratio and Pressure on Properties of UHMWPA6/GdCl₃ Fiber by Dry-Spinning Method
p.312

Influence of Yarn-Reduction Technique on Bending Properties of Tapered 3D Braided Composites
p.317

Manufacturing Techniques and Mechanical Properties of Recycle High-Strength PET Compound Nonwoven
p.321

Overview and Correlation Study on Electrostatic Property of Different Testing Standards
p.325

Prediction of Yarn Unevenness Based on BP Neural Network
p.329

Process Technique and Property Evaluation of Bamboo Charcoal/Polyamide/Stainless Steel Elastic Warp-Knitted Fabrics
p.333

Research on the Method of Wool Knitted Fabric Style Evaluation
p.338

Researches on Microwave Dyeing Cotton Fabrics
p.343

Study of Irradiation Hydrophilic Modification of Polypropylene Meltblown Nonwovens
p.348

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 627Prediction of Yarn Unevenness Based on BP Neural...

Prediction of Yarn Unevenness Based on BP Neural Network

Abstract:

The objective of this research is to predict yarn unevenness. The model of predicting yarn unevenness is built based on BP neural network. The BP neural networks are trained with HVI test results of cotton and USTER TENSOJET 5-S400 test results of yarn. The results show prediction models based on BP neural network are very precise and efficient.