基于神经元网络的燃油锅炉烟气氧含量的软

The Soft Sensor of Oxygen Content in Oil Fired Boiler Based on Neural Nefwook

针对目前各种氧含量检测仪表在运行过程中的可靠性差、使用寿命短及价格昂贵等诸多不足，通过探寻锅炉运行中的其他参数与烟气氧含量的映射关系，建立ＢＰ神经元网络，提出了燃油锅炉烟气氧含量的软测量方法。结果表明，其精度完全达到了设计要求。

Recently, low credibility,short lifetime and high cost are the weakness of oxygen detector.After having searched for the relation between oxygen content in boiler flue gas and otherparameters, a BP artificial neural network soft sensor system, which used to measure oxygen content of oil fired boiler real time, has been built. It is evidence by practice that the precise of the soft sensor system reaches what we wanted.