Rotary kiln combustion working condition recognition based on flame image texture features and LVQ neural network

@article{Wang2012RotaryKC,
  title={Rotary kiln combustion working condition recognition based on flame image texture features and LVQ neural network},
  author={Jiesheng Wang and Xiudong Ren},
  journal={Proceedings of the 10th World Congress on Intelligent Control and Automation},
  year={2012},
  pages={305-309}
}
According to the pulverized coal combustion flame image texture features of the rotary-kiln oxide pellets sintering process, a combustion working condition recognition method based on learning vector quantization (LVQ) neural network is introduced. Firstly, the numerical flame image was analyzed to extract texture features, such as energy, entropy and inertia, based on grey-level co-occurrence matrix (GLCM) to provide qualitative information on the changes in the visual appearance of the flame… CONTINUE READING
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