摘要
为监测锅炉烟气排放,采用软件传感器代替实际传感器分析NOx和SO2。根据理论分析和现场试验,选取循环流化床锅炉的有关控制输入和中间变量为输入变量,采用多变量ARX模型(autoregressiveexogenousvariablemodels),设计了全局最优的烟气NOx和SO2排放预测模型,以此作为软件传感器代替实际的烟气分析仪表,具有反应快、维护简单等优点,提高了系统的自动化水平,且降低了成本。现场数据分析表明,软件传感器可用于指导机组优化运行和烟气后处理设备的反馈控制。
This paper discusses the theoretical basis and the methodology for software sensors for detecting boiler emissions. Soft sensors for NOx and SO2 to replace hardware analyzers of boiler emissions would be cheaper, require less maintenance and have faster response. Some boiler control inputs and state variables were selected as inputs to a multiinput autoregressive exogenous (ARX) variable models based on boiler operating conditions and experimental data. Optimal NOx and SO2 emission monitoring models were established using global optimization. As low cost alternatives to hardware sensors, software sensors enhance process automation and lower cost. Plant data analysis demonstrates that these software sensors can be used to optimize boiler operation and to control exhaust gas cleaning facilities.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第12期1636-1638,共3页
Journal of Tsinghua University(Science and Technology)
