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Simulation of Motor Core Gluing Process with Fine Mesh Nets
Yong-Jie Zeng1, Chia-Wei Liang1, Sheng-Jye Hwang1
1Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.
Polymers
|November 11, 2022
Summary
Using fine mesh nets improves resin distribution in motor core gluing, reducing defects and processing time. This method enhances product quality and lowers experimental costs through accurate computer simulations.
Area of Science:
- Materials Science
- Manufacturing Engineering
- Computational Fluid Dynamics
Background:
- Traditional motor core welding presents challenges like iron loss and processing time.
- Resin gluing offers potential improvements but faces difficulties in uniform resin distribution.
- Optimizing resin distribution is critical for successful gluing processes.
Purpose of the Study:
- To investigate the use of fine mesh nets for enhancing resin distribution in motor core gluing.
- To employ computer-aided engineering (CAE) for simulating the resin flow behavior.
- To validate simulation accuracy against experimental results and identify process improvements.
Main Methods:
- Experimental application of fine mesh nets during resin application.
- Computer simulation using CAE to model the resin distribution and filling process.
- Comparative analysis of resin distribution with and without fine mesh nets.
Main Results:
- Computer simulations accurately predicted the resin filling process observed in experiments.
- Fine mesh nets significantly improved the uniformity of resin distribution compared to traditional methods.
- Simulations effectively predicted defects and guided improvements, reducing experimental costs.
- Fine mesh nets mitigated overflow issues, preventing bump formation.
Conclusions:
- Fine mesh nets are effective in optimizing resin distribution for motor core gluing.
- CAE simulations provide a reliable tool for predicting and improving gluing processes.
- The integration of fine mesh nets and simulation analysis leads to enhanced product quality and efficiency.
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