摘要
电站锅炉烟气含氧量的准确测量对锅炉燃烧效率的提高具有重要的意义。针对锅炉燃烧过程中存在的氧量信号测量滞后大和可靠性差,提出采用基于改进BP神经网络的烟气含氧量的软测量方法。实践验证:神经网络的预测值和实测值相吻合,烟气含氧量预测最大绝对误差为0.37,较好地实现了烟气含氧量的预测。
The accurate measurement of oxygen content in flue gas for boilers is significant to the enhancement of boiler combustion efficiency. Aiming at the long lag of oxygen content signal measurement and low reliability during combustion, this paper proposes the soft - sensing of oxygen content in flue gas based on the improved BP nerve network. Verification shows that the predictive value coincides with the measured value and the biggest absolute error of the oxygen content prediction in flue gas is 0.37, which better realizes the prediction.
出处
《黑龙江电力》
CAS
2011年第6期418-420,共3页
Heilongjiang Electric Power
关键词
改进BP神经网络
烟气含氧量
燃烧效率
软测量
improved BP nerve network
oxygen content in flue gas
combustion efficiency
soft-sensing
