Abstract
The paper analyzes the effect of technological parameters on manufacturing superfine quartz powder body by the method of high-energy ball, and studies the detail test methods based on the orthogonal experimental design and the uniformity experimental design. The paper applies the artificial neural network technology to establish the prediction model of the quartz powder body particle diameter, and optimizes the weight of BP neural network model by using the global search capability of Genetic Algorithm, and advances the prediction model of superfine quartz powder particle diameter. The experimental results show that the model is precise to predict the particle diameter. The technology will provide the theoretic guidance for further studying the technology parameters of manufacturing superfine quartz powder body.
| Original language | English |
|---|---|
| Pages (from-to) | 55-58+63 |
| Journal | Cailiao Kexue yu Gongyi/Material Science and Technology |
| Volume | 15 |
| Issue number | 1 |
| State | Published - Feb 2007 |
Keywords
- BP neural network
- High-energy ball mill
- Superfine quartz powder
- Technology parameters
- Test method
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