双炉膛电站直流炉辐射图像处理及燃烧诊断与优化控制
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摘要
未来很长时间内我国仍将以燃煤发电为主。在电站燃煤锅炉中,燃烧工况组织不合理造成的燃烧不均匀、火焰中心偏斜、火焰刷墙等是导致炉膛结焦、炉管爆裂、炉膛灭火、炉膛爆炸等运行事故的重要原因。将炉内燃烧火焰图像处理技术应用到炉膛火焰监视装置中,对炉内燃烧进行温度分布可视化监视和燃烧诊断与优化控制,对于改善现有锅炉炉膛燃烧安全性和经济性具有重要意义。本文的研究对象为一台300MW双炉膛煤粉燃烧直流锅炉,针对该锅炉进行了炉内燃烧火焰辐射图像处理和燃烧诊断与优化控制的研究。具体工作如下:
大型电站锅炉内的燃烧火焰具有大尺寸、强脉动的特点,一般的方法难以实现炉内三维温度场的可视化,而双炉膛锅炉不仅重建的温度分布数量是单炉膛锅炉的2倍,而且由于其结构的特殊性(为中间连通型),使得重建炉内三维温度场更为复杂。基于本课题组已有的研究成果能够很好地解决这一问题:首先利用DRESOR法为炉内三维温度场的重建提供充分的辐射成像信息,其次采用辐射温度成像模型建立火焰温度图像(由成像装置检测得到)与炉内温度场之间的线性关系,最后基于一种改进的Tikhonov正则化方法重建炉内三维温度分布。针对该双炉膛直流炉的模拟研究结果表明:即使测量误差的均方差达到0.11,仍然能够达到很好的重建效果。
在获得炉内三维温度场重建结果的基础上本文开发了一套炉膛燃烧监控系统,基于BCB和OpenGL混合编程在计算机中实现了炉内三维温度场的可视化,基于现场总线技术首次在电厂DCS控制系统中实现了大型电站锅炉炉内三维温度场可视化。DCS中温度场可视化画面实时刷新时间不超过5s,现场运行操作人员可通过DCS画面直观地了解炉膛燃烧工况(如火焰中心位置、温度高低及火焰中心偏斜等),有助于减轻运行人员工作强度,提高锅炉安全运行水平。
在不同燃烧工况下开展了该直流炉炉内分层黑度和温度场特征参数检测的实验研究,研究结果表明:在煤质不变的情况下炉内各层黑度与各层平均温度均与负荷成正比;当进行层间燃料量调整时,煤粉浓度增加的区域分层黑度与层间温度均增加;当锅炉氧量降低时,炉膛下两层黑度增加,上两层黑度有所减少,此时炉膛火焰中心区域的辐射换热水平增加,全炉膛平均温度增加。在进行炉内温度场特征参数检测得到典型工况样本的基础上,以各层各角燃烧器燃料量及一次风、二次风量、燃尽风量等作为输入变量,以炉内各层平均温度及相应的温度中心坐标作为输出变量建立RBF网络动态模型,该模型具有良好的自适应能力,能够有效克服现有模型的不足。
通过安装在炉本体上的多个CCD探头,经图像处理技术能够得到反映炉内不同区域燃烧强度大小的多层辐射能信号。本文提出利用炉内多层辐射能信号进行炉膛燃烧精细化诊断的设想,并对该炉一次灭火事故进行了详细分析。研究结果表明:多层辐射能信号相比现有的锅炉运行参数能够更迅速更全面地反映炉内燃烧工况的变化,可为帮助查明灭火事故原因提供一个有力的诊断工具。
为便于将多层辐射能信号引入机组控制系统,本文提出一种将多层辐射能信号进行融合处理得到总辐射能信号的自适应算法,该算法能够克服因某些CCD火焰探头出现周期性积灰、结焦情况导致某些分层辐射能失真带来的不利影响,融合后的总辐射能能够很好地反映负荷的变化趋势,并超前负荷变化30s以上,适合引入机组在线控制系统。本文提出了基于RBF网络自适应整定引入总辐射能反馈信号的燃烧串级控制系统PID参数的控制策略,仿真研究表明该控制算法能快速响应主汽压的阶跃扰动,迅速克服燃料量内扰,其控制效果明显优于常规PID串级控制。
最后本文介绍了基于总辐射能信号反馈进行风煤比优化控制的原理,针对该直流炉进行了氧量-总辐射能关联特性检测实验,将检测结果应用于该直流炉风煤比优化控制方案设计,在260MW稳定负荷和295MW至280MW变负荷两种工况下进行了风煤比优化控制实验研究。研究结果表明机组DCS控制系统能够自动调整氧量寻求炉内最大辐射能,两种工况下锅炉效率分别提高了0.11和0.35个百分点,经济效益显著,具有良好的产业化应用前景。
The coal acts an important role in our country’s energy structure. In the utility boilers using coal as the input fuel, the uneven combustion, the bias of the flame center, the rushing of the flame to the walls etc., which result from the unreasonable organization of combustion condition, are the important reason leading to the boiler combustion operation failure such as fouling on the furnace wall, the leakage of the water-wall tubes, the flame extinction and the explosion of the furnaces. The image processing techniques had a successful application in the combustion diagnosis of utility boilers, so it is much meaningful to apply the technique into the boiler furnace’s monitoring systems to show the flame’s temperature distribution and optimize the combustion control in furnace in order to improve the boiler’s economical efficiency and security. In this paper, the combustion diagnosis and control based on the radiative image processing techniques in a 300 MW twin-furnace once-through boiler had been done.
Because of large scale and intensive pulsation of combustion flame in furnace, it is difficult to realize the 3-D temperature visualization in a utility boiler. Because The number of 3-D temperature values of a twin-furnace boiler is twice as those of a single-furnace boiler and the two furnaces is linked each other, it is more difficult to reconstruct the 3-D temperature distribution in the twin-furnace boiler. Based on the research findings of the research group led by Prof. Zhou Huai-chun, Huazhong University of Science & Technology, this difficult problem can be solved effectively: at first, the radiative imaging information could be obtained using the DRESOR method; second, the linear relationship of the 3-D temperature distribution and the flame radiative temperature image could be constructed using the radiative temperature imaging model; in the end, an improved Tikhonov regularization method was used to reconstruct the 3-D temperature distribution in the twin-furnace boiler. The simulation study showed that the reconstruction result was good even with the reconstruction error up to 0.11.
The hardware and software design of a monitoring system in the twin-furnace boiler are introduced in detail. Through the system, the 3-D temperature distribution in the furnaces could be visualized in industrial computer based on the BCB and OpenGL hybrid programming and could be visualized in the utility unit's DCS control system based on the fieldbus for the first time. The refreshment ratio of the visualization is less than 5 seconds. It helps power plant operators to see the combustion condition such as the position of the flame center, the value of the average temperature and the bias of the flame center, et al more directly and to enforce the combustion adjustment more effectively.
The multiple layer flame emissivity and characteristic parameters of the 3-D temperature distribution (include the average temperature, the temperature center coordinates of each cross section in furnace) had been measured under different combustion condition. The measurment results showed: the each layer flame emissivity and each layer average temperature is proportional to the unit load; under varied layer fuel quantity, the layer flame emissivity and layer average temperature increase at the areas where the coal density increase; when the oxygen contents decrease, the flame emissivity of the lower two layers increase and the flame emissivity of the higher two layers decrease a little, the radiative heat exchange of the flame center areas increase and the average temperature in full furnace increase at the same time. Based on the typical measurement samples, the dynamic RBF neural network model which using the coal consumption, primary air quantity and second air quantity of each burners as the input variables and the the characteristic parameters of temperature distribution as the output can be constructed. The dynamic model has a good adaptability and overcome the disadvantages of current such models.
The Multiple Radiant Energy Signals (MRES) which reflect the combustion intensity of different areas in furnace are obtained by the computer image processing techniques through several Charge Coupled Devices (CCD) cameras installed in the boiler furnaces. In this paper, the idea of using the MRES as the combustion detailed diagnosis tool was put forward. By the analysis of a flame-extinction incident it could be shown that MRES reflects the incident more quickly and comprehensively than other parameters of the boiler, so MRES can play an important role in the combustion diagnosis of large scale coal-fired boilers. The similar incident has not happened after taking the corresponding protective action.
A new algorithm of fuse MRES into Integral Radiant Energy Signal (IRES) had been put forward. IRES can maintain the maximum correlation with the unit load. The correlation coefficient between them is more than 0.92 and the IRES varies 30s earlier than the unit load. So IRES processed by this algorithm is suitable to been introduced into the unit’s control system. A new control method of tuning the combustion cascade control system’s PID parameters using the RBF neural network is put forward. The result of the simulation research shows that the cascade control system based on the new method can respond the step input of the main steam and overcome the fuel disturbance more quickly and more effectively than the traditional combustion cascade control system. It is featured by strong robustness and self-adaptability.
The principle of air-coal ratio optimization control were introduced in this paper. The experiment reflecting the associative relationship of oxygen content and IRES in the boiler was done and the results were applied into the scheme design of air-coal ratio optimization control circuit. The optimization experiments under the 260MW stable load and from 295MW to 280MW varied load conditions showed that the maximum IRES can be obtained automatically and the boiler efficiency increased 0.11 and 0.35 percentage respectively.
大型电站锅炉内的燃烧火焰具有大尺寸、强脉动的特点,一般的方法难以实现炉内三维温度场的可视化,而双炉膛锅炉不仅重建的温度分布数量是单炉膛锅炉的2倍,而且由于其结构的特殊性(为中间连通型),使得重建炉内三维温度场更为复杂。基于本课题组已有的研究成果能够很好地解决这一问题:首先利用DRESOR法为炉内三维温度场的重建提供充分的辐射成像信息,其次采用辐射温度成像模型建立火焰温度图像(由成像装置检测得到)与炉内温度场之间的线性关系,最后基于一种改进的Tikhonov正则化方法重建炉内三维温度分布。针对该双炉膛直流炉的模拟研究结果表明:即使测量误差的均方差达到0.11,仍然能够达到很好的重建效果。
在获得炉内三维温度场重建结果的基础上本文开发了一套炉膛燃烧监控系统,基于BCB和OpenGL混合编程在计算机中实现了炉内三维温度场的可视化,基于现场总线技术首次在电厂DCS控制系统中实现了大型电站锅炉炉内三维温度场可视化。DCS中温度场可视化画面实时刷新时间不超过5s,现场运行操作人员可通过DCS画面直观地了解炉膛燃烧工况(如火焰中心位置、温度高低及火焰中心偏斜等),有助于减轻运行人员工作强度,提高锅炉安全运行水平。
在不同燃烧工况下开展了该直流炉炉内分层黑度和温度场特征参数检测的实验研究,研究结果表明:在煤质不变的情况下炉内各层黑度与各层平均温度均与负荷成正比;当进行层间燃料量调整时,煤粉浓度增加的区域分层黑度与层间温度均增加;当锅炉氧量降低时,炉膛下两层黑度增加,上两层黑度有所减少,此时炉膛火焰中心区域的辐射换热水平增加,全炉膛平均温度增加。在进行炉内温度场特征参数检测得到典型工况样本的基础上,以各层各角燃烧器燃料量及一次风、二次风量、燃尽风量等作为输入变量,以炉内各层平均温度及相应的温度中心坐标作为输出变量建立RBF网络动态模型,该模型具有良好的自适应能力,能够有效克服现有模型的不足。
通过安装在炉本体上的多个CCD探头,经图像处理技术能够得到反映炉内不同区域燃烧强度大小的多层辐射能信号。本文提出利用炉内多层辐射能信号进行炉膛燃烧精细化诊断的设想,并对该炉一次灭火事故进行了详细分析。研究结果表明:多层辐射能信号相比现有的锅炉运行参数能够更迅速更全面地反映炉内燃烧工况的变化,可为帮助查明灭火事故原因提供一个有力的诊断工具。
为便于将多层辐射能信号引入机组控制系统,本文提出一种将多层辐射能信号进行融合处理得到总辐射能信号的自适应算法,该算法能够克服因某些CCD火焰探头出现周期性积灰、结焦情况导致某些分层辐射能失真带来的不利影响,融合后的总辐射能能够很好地反映负荷的变化趋势,并超前负荷变化30s以上,适合引入机组在线控制系统。本文提出了基于RBF网络自适应整定引入总辐射能反馈信号的燃烧串级控制系统PID参数的控制策略,仿真研究表明该控制算法能快速响应主汽压的阶跃扰动,迅速克服燃料量内扰,其控制效果明显优于常规PID串级控制。
最后本文介绍了基于总辐射能信号反馈进行风煤比优化控制的原理,针对该直流炉进行了氧量-总辐射能关联特性检测实验,将检测结果应用于该直流炉风煤比优化控制方案设计,在260MW稳定负荷和295MW至280MW变负荷两种工况下进行了风煤比优化控制实验研究。研究结果表明机组DCS控制系统能够自动调整氧量寻求炉内最大辐射能,两种工况下锅炉效率分别提高了0.11和0.35个百分点,经济效益显著,具有良好的产业化应用前景。
The coal acts an important role in our country’s energy structure. In the utility boilers using coal as the input fuel, the uneven combustion, the bias of the flame center, the rushing of the flame to the walls etc., which result from the unreasonable organization of combustion condition, are the important reason leading to the boiler combustion operation failure such as fouling on the furnace wall, the leakage of the water-wall tubes, the flame extinction and the explosion of the furnaces. The image processing techniques had a successful application in the combustion diagnosis of utility boilers, so it is much meaningful to apply the technique into the boiler furnace’s monitoring systems to show the flame’s temperature distribution and optimize the combustion control in furnace in order to improve the boiler’s economical efficiency and security. In this paper, the combustion diagnosis and control based on the radiative image processing techniques in a 300 MW twin-furnace once-through boiler had been done.
Because of large scale and intensive pulsation of combustion flame in furnace, it is difficult to realize the 3-D temperature visualization in a utility boiler. Because The number of 3-D temperature values of a twin-furnace boiler is twice as those of a single-furnace boiler and the two furnaces is linked each other, it is more difficult to reconstruct the 3-D temperature distribution in the twin-furnace boiler. Based on the research findings of the research group led by Prof. Zhou Huai-chun, Huazhong University of Science & Technology, this difficult problem can be solved effectively: at first, the radiative imaging information could be obtained using the DRESOR method; second, the linear relationship of the 3-D temperature distribution and the flame radiative temperature image could be constructed using the radiative temperature imaging model; in the end, an improved Tikhonov regularization method was used to reconstruct the 3-D temperature distribution in the twin-furnace boiler. The simulation study showed that the reconstruction result was good even with the reconstruction error up to 0.11.
The hardware and software design of a monitoring system in the twin-furnace boiler are introduced in detail. Through the system, the 3-D temperature distribution in the furnaces could be visualized in industrial computer based on the BCB and OpenGL hybrid programming and could be visualized in the utility unit's DCS control system based on the fieldbus for the first time. The refreshment ratio of the visualization is less than 5 seconds. It helps power plant operators to see the combustion condition such as the position of the flame center, the value of the average temperature and the bias of the flame center, et al more directly and to enforce the combustion adjustment more effectively.
The multiple layer flame emissivity and characteristic parameters of the 3-D temperature distribution (include the average temperature, the temperature center coordinates of each cross section in furnace) had been measured under different combustion condition. The measurment results showed: the each layer flame emissivity and each layer average temperature is proportional to the unit load; under varied layer fuel quantity, the layer flame emissivity and layer average temperature increase at the areas where the coal density increase; when the oxygen contents decrease, the flame emissivity of the lower two layers increase and the flame emissivity of the higher two layers decrease a little, the radiative heat exchange of the flame center areas increase and the average temperature in full furnace increase at the same time. Based on the typical measurement samples, the dynamic RBF neural network model which using the coal consumption, primary air quantity and second air quantity of each burners as the input variables and the the characteristic parameters of temperature distribution as the output can be constructed. The dynamic model has a good adaptability and overcome the disadvantages of current such models.
The Multiple Radiant Energy Signals (MRES) which reflect the combustion intensity of different areas in furnace are obtained by the computer image processing techniques through several Charge Coupled Devices (CCD) cameras installed in the boiler furnaces. In this paper, the idea of using the MRES as the combustion detailed diagnosis tool was put forward. By the analysis of a flame-extinction incident it could be shown that MRES reflects the incident more quickly and comprehensively than other parameters of the boiler, so MRES can play an important role in the combustion diagnosis of large scale coal-fired boilers. The similar incident has not happened after taking the corresponding protective action.
A new algorithm of fuse MRES into Integral Radiant Energy Signal (IRES) had been put forward. IRES can maintain the maximum correlation with the unit load. The correlation coefficient between them is more than 0.92 and the IRES varies 30s earlier than the unit load. So IRES processed by this algorithm is suitable to been introduced into the unit’s control system. A new control method of tuning the combustion cascade control system’s PID parameters using the RBF neural network is put forward. The result of the simulation research shows that the cascade control system based on the new method can respond the step input of the main steam and overcome the fuel disturbance more quickly and more effectively than the traditional combustion cascade control system. It is featured by strong robustness and self-adaptability.
The principle of air-coal ratio optimization control were introduced in this paper. The experiment reflecting the associative relationship of oxygen content and IRES in the boiler was done and the results were applied into the scheme design of air-coal ratio optimization control circuit. The optimization experiments under the 260MW stable load and from 295MW to 280MW varied load conditions showed that the maximum IRES can be obtained automatically and the boiler efficiency increased 0.11 and 0.35 percentage respectively.
引文
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