In this study, the relationship between the visual information gathered from the flame images and the excess air factor 2 in coal burners is investigated. In conventional coal burners the excess air factor 2. can be o...In this study, the relationship between the visual information gathered from the flame images and the excess air factor 2 in coal burners is investigated. In conventional coal burners the excess air factor 2. can be obtained using very expensive air measurement instruments. The proposed method to predict ） for a specific time in the coal burners consists of three distinct and consecutive stages; a） online flame images acquisition using a CCD camera, b） extrac- tion meaningful information （flame intensity and bright- ness）from flame images, and c） learning these information （image features） with ANNs and estimate 2. Six different feature extraction methods have been used： CDF of Blue Channel, Co-Occurrence Matrix, L-Frobenius Norms, Radiant Energy Signal （RES）, PCA and Wavelet. When compared prediction results, it has seen that the use of co- occurrence matrix with ANNs has the best performance （RMSE = 0.07） in terms of accuracy. The results show that the proposed predicting system using flame images can be preferred instead of using expensive devices to measure excess air factor in during combustion.展开更多
宽域废气氧(Universal Exhaust Gas Oxygen,UEGO)传感器可以在很宽的空燃比范围内提供有效的氧含量信号,它的结构特殊,必须配以控制器才能使用。利用鲁棒PID算法控制UEGO控制器中泵电压的大小和方向,并将泵电压反馈作用在UEGO传感器上...宽域废气氧(Universal Exhaust Gas Oxygen,UEGO)传感器可以在很宽的空燃比范围内提供有效的氧含量信号,它的结构特殊,必须配以控制器才能使用。利用鲁棒PID算法控制UEGO控制器中泵电压的大小和方向,并将泵电压反馈作用在UEGO传感器上。检测UEGO传感器上的泵电流,并设计非线性校正环节对其进行校正,校正输出值即为过量空气系数(λ)。利用dSPACE实时仿真系统实现UEGO控制器,并在汽车化油器发动机台架上进行相关实验。实验数据表明,在λ值静态和动态变化时,UEGO控制器都具有良好的鲁棒性和运行性能,响应快速且精度良好。展开更多
基金supported by The Scientific and Technological Research Council of Turkey(TUBITAK,Project number:114M116)and MIMSAN AS
文摘In this study, the relationship between the visual information gathered from the flame images and the excess air factor 2 in coal burners is investigated. In conventional coal burners the excess air factor 2. can be obtained using very expensive air measurement instruments. The proposed method to predict ） for a specific time in the coal burners consists of three distinct and consecutive stages; a） online flame images acquisition using a CCD camera, b） extrac- tion meaningful information （flame intensity and bright- ness）from flame images, and c） learning these information （image features） with ANNs and estimate 2. Six different feature extraction methods have been used： CDF of Blue Channel, Co-Occurrence Matrix, L-Frobenius Norms, Radiant Energy Signal （RES）, PCA and Wavelet. When compared prediction results, it has seen that the use of co- occurrence matrix with ANNs has the best performance （RMSE = 0.07） in terms of accuracy. The results show that the proposed predicting system using flame images can be preferred instead of using expensive devices to measure excess air factor in during combustion.
文摘宽域废气氧(Universal Exhaust Gas Oxygen,UEGO)传感器可以在很宽的空燃比范围内提供有效的氧含量信号,它的结构特殊,必须配以控制器才能使用。利用鲁棒PID算法控制UEGO控制器中泵电压的大小和方向,并将泵电压反馈作用在UEGO传感器上。检测UEGO传感器上的泵电流,并设计非线性校正环节对其进行校正,校正输出值即为过量空气系数(λ)。利用dSPACE实时仿真系统实现UEGO控制器,并在汽车化油器发动机台架上进行相关实验。实验数据表明,在λ值静态和动态变化时,UEGO控制器都具有良好的鲁棒性和运行性能,响应快速且精度良好。
