Neural Network Control System for Rotary Kiln Based on Features of Combustion Flame
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摘要: 提出了一种基于燃烧火焰图象特征的回转窑神经网络控制系统.系统主要由两部分组 成,一部分是回转窑煅烧带火焰燃烧状态识别系统,包括火焰图象获取、预处理、分割、特征提 取与识别;另一部分是基于高斯基函数神经网络的控制系统.实际运行结果表明该系统的有效 性和实用性.Abstract: In this paper, a neural network control system for rotary kiln based on features of combustion flame is proposed. The system consists of two main parts. One is status recognition system of calcine band flame, which is composed of image capturing, preprocessing, segmentation, feature extraction and pattern recognition. The other is neural network control system using Gaussian potential function network (GPFN). The practical operating results illustrate effectiveness and practicability of the proposed system.
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Key words:
- Visual detection /
- image processing /
- neural network /
- fuzzy logic /
- rotary kiln
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