-
TDLAS测量技术分直接吸收法和波长调制法[20-21]。相比于波长调制法而言,直接吸收法主要应用于具有足够吸光度的条件。电站锅炉一般尺寸为7m~20m,H2O体积分数约为0.10,适合应用直接吸收法进行温度测量。
当频率为的激光通过的被测气体,气体对激光的吸收满足Beer-Lambert定律[20],即:
$ \begin{array}{*{20}{c}} {{I_\nu } = {I_{{\rm{in}}, \nu }}\exp \left[ { - {\alpha _\nu }} \right] = }\\ {{I_{{\rm{in}}, \nu }}\exp [ - S(T)\mathit{\Phi }(\nu , p, x, T)pxL]} \end{array}{\rm{ }} $
(1) 式中,L是测量路径长度, p为压强, 温度为T, 体积分数为x, αν是吸光度, S表示谱线线强, Iin, ν和Iν分别是入射激光和透射激光强度, 线型函数Φ满足归一化条件$\int_{ - \infty }^\infty \mathit{\Phi } {\rm{d}}\nu \equiv 1$。气体温度2可通过下式进行计算:
$ \begin{array}{*{20}{c}} {T = }\\ {\frac{{\left( {\frac{{hc}}{k}} \right)\left( {E_1^{\prime \prime } - E_2^{\prime \prime }} \right)}}{{ - \ln r(T) + \ln \frac{{{S_1}\left( {{T_{\rm{r}}}} \right)}}{{{S_2}\left( {{T_{\rm{r}}}} \right)}} + \left( {\frac{{hc}}{{k{T_{\rm{r}}}}}} \right)\left( {E_1^{\prime \prime } - E_2^{\prime \prime }} \right)}}} \end{array}{\rm{ }} $
(2) 式中,S1(Tr)和S2(Tr)分别为吸收谱线1和吸收谱线2在参考温度Tr下的线强, h为普朗克常数, c为光速, k为玻尔兹曼常数, E1″和E2″为吸收谱线1和谱线2跃迁对应的低态能级能量, r为两条谱线吸光度积分面积的比值。
-
重建算法分变换法和迭代法,在投影数据比较充分的情况下,变换法能够得到较高的重建精度。由于电厂锅炉的炉膛的条件所限,投影数据较少,采用代数迭代重建法(algebraic reconstruction technique,ART)能够较好地重建出图像。ART的表达式可以描述为[14]:
$ x_j^{(k + 1)} = x_j^{(k)} + \lambda \frac{{\left( {{P_i} - \sum\limits_{j = 1}^M {{a_{i, j}}} {x_j}} \right)}}{{\sum\limits_{j = 1}^M {{{\left| {{a_{i, j}}} \right|}^2}} }}{a_{i, j}} $
(3) 式中,下标i为测量路径序号,下标j代表网格序号,k为迭代次数,λ为松弛因子,M为网格总数,Pi为第i个测量路径的投影值,ai, j为投影系数矩阵中的元素,代表第i条测量路径经过第j个网格的权重。在ART算法中,每一个方程都对各xj的值修正一次,即第i条测量路径对各xj的值修正完以后,再用第i+1条测量路径对各xj进行修正,直到所有测量路径修正完成以后,完成一轮迭代。如果此时没有达到收敛条件,则进行第2次迭代,直到满足收敛条件。
-
炉膛燃烧气体通过辐射对水冷壁中的水蒸气进行加热,主蒸汽对汽轮机做工从而发电。根据斯特藩定律,燃烧气体在单位时间内辐射出的总能量称为辐射度J,与气体的热力学温度T成四次方关系:
$ J = \varepsilon \sigma {T^4} $
(4) 式中,ε为气体的辐射系数,σ为斯特藩常量,因此气体的温度T可以反映炉内的辐射量。由于分布反馈(distributed feedback, DFB)激光器的扫描速率可以达到千赫兹,因此温度测量可以达到很高的刷新速率,从而得到当前炉膛积蓄的总能量。
应用温度测量锅炉控制的优化主要体现在以下3个方面。
-
锅炉控制系统收到负荷调整指令后,运行人员通过控制燃料及风量对炉膛燃烧进行调整。当机组发电功率调度指令已经下达,投入的燃料量和风量将进行大幅度调节。由于锅炉燃烧存在惯性,主蒸汽流量相对于燃料量、风量的投入存在滞后,若待运行人员观察到当前负荷超过调节指令后再开始减少燃料量,将会导致负荷的超调。因此将温度测量作为辐射能的表征能够迅速的得知当前燃料量、风量的投入是否合适,并作出相应调整。
-
锅炉的设计燃料和实际运行采用的燃料通常存在很大的不同,燃料热值存在很大的波动,例如焦炉煤气的热值为17000kJ/m3,高炉煤气的热值则仅为3500kJ//m3,不仅每种煤气本身的热值有一定波动,不同煤气混合比例的波动也会极大的导致燃料总热值的波动。根据(4)式,锅炉内的温度可作为燃料辐射能的度量方式,通过TDLAS测量得到气体温度可及时对燃料投入量进行调整。
-
电厂锅炉通常有数个燃烧器,由于燃料管道和风道中的流量和压力测点通常不准确,每个燃烧器的燃料量投入存在不平衡的情况,导致水冷壁起皮,影响金属寿命。通过TDLAT技术得到炉内温度场的分布,可对各燃烧器进行调平。
-
电厂锅炉将煤气燃烧产生的辐射能量用于加热蒸汽,蒸汽再对汽轮机做功转换为电能,因此辐射总能量的大小应与主蒸汽流量成单调关系,即炉膛平均温度应与蒸汽流量呈单调关系。为研究炉膛温度与主蒸汽流量的具体关系,在电厂安装了3×3两个垂直投影方向共6对测量路径,图 5为电厂安装的测量探头。
图 6中将超过30h的主蒸汽流量和通过TDLAS方法测量到的炉膛平均温度进行了对比。该时间段内的蒸汽流量基本在70%负荷到100%负荷之间。将图 3中所示的6个测量路径进行平均得到炉膛平均温度,该平均温度有效代表了炉膛燃烧辐射能量。图 6中的蒸汽流量和平均温度变化趋势基本一致,其相关系数达到0.91,说明气体温度与负荷非常相关。
通过线性回归分析,从数据集中抽取1%的数据作为验证集,剩下的数据作为训练集,得到负荷Y作为因变量,将温度X作为自变量,两者之间的线性关系为:
$ Y = 0.178X - 139 $
(5) 用验证集的数据计算其决定系数为R2=0.88,说明有88%的主蒸汽流量值可以由炉膛温度决定,如图 7所示。
由于主蒸汽流量与温度有较高的相关性,从一方面可以知道该时间段内的锅炉的燃料投入量较为合理,负荷调整过程中燃烧也比较平稳。对于相关性不高的工况,可通过测量温度对燃料投入量的合理性进行评估,从而做出相应调整。
利用CT重建技术对锅炉横截面温度场分布进行重建。锅炉燃烧器布置在前后墙,前后墙各3层,每层各有3个,因此正常情况下,在燃烧器上方的前后墙温度相较侧墙温度更高。根据图 3中各路径上的测量数据,利用ART算法进行对炉膛温度场进行了重建。由于空间的限制,测量路径有限,重建后的温度分布空间分辨率不高,不利于观察和运行调整,于是对重建结果进行3次样条插值,得到平滑后的温度分布。图 8为实验过程中锅炉满负荷运行时所成的不同时刻的典型的温度分布图。从图 6中的负荷曲线可以看出,该时间段内锅炉运行相对比较稳定,图 8中锅炉温度场分布基本是前、后墙靠近燃烧器上方的位置温度较高,重建结果符合预期。
激光吸收光谱技术应用于锅炉优化控制研究
Application of tunable diode laser absorption to optimize boiler control
-
摘要: 为了提高电站锅炉自动化程度,为真实锅炉的优化控制提供新颖的实时在线测量手段,采用计算机层析重建和激光吸收光谱技术相结合的方法,进行了理论分析和实验验证。仿真实验证明了仅采用2个投影方向即能够实现温度峰值位置的重建及其相对高低的分辨;布置6条测量路径形成测量网格,得到真实锅炉炉膛的实时在线2-D温度场重建数据。结果表明,炉膛平均温度与锅炉蒸汽流量的相关系数达到0.91,回归分析得到决定系数为0.88;可将平均温度作为炉膛内实时的总辐射能的表征,用于避免锅炉超调,根据温度可获知燃料总的热值波动,2-D温度场的重建可用于锅炉调平。该研究为锅炉提供了非接触式测量手段,为提高锅炉自动化程度和研究燃烧优化控制提供了重要支持。Abstract: To improve the automation degree and provide a novel real-time, in situ measurement methods of optimizing real boiler control, tunable diode absorption spectroscopy (TDLAS) combined with computed tomography reconstruction was proposed by theoretical analysis and experimental validation. It was proved by simulation that the peak location could be reconstructed and the relative values could be distinguished in case of only two projections. Six measuring grid was arranged to obtain the reconstructed 2-D temperature distribution. The result showes that the correlation coefficient between the averaged temperature and load is 0.91. Linear regression analysis showes that the coefficient of determination is 0.88. The averaged temperature could represent the real-time total radiation, which can be used to avoid over adjusting and obtain the heat value. The 2-D temperature distribution can be used to leveling the boiler. It was concluded that this method provides important support to the non-intrusive in-situ temperature measurement and study of optimizing combustion control.
-
-
[1] CHEN J Y, LIU J G, HE Y B, et al. Temperature measurement of CO2 by use of a distributed-feedback diode laser sensor near 2.0μm[J]. Chinese Journal of Lasers, 2012, 39(11): 1108004(in Chin-ese). doi: 10.3788/CJL201239.1108004 [2] LINNERUD I, KASPERSEN P, JAEGER T. Gas monitoring in the process industry using diode laser spectroscopy[J]. Applied Physics, 1998, B67(3): 297-305. [3] TEICHERT H, FERNHOLZ T, EBERT V. Simultaneous in situ measurement of CO, H2O, and gas temperatures in a full-sized coal-fired power plant by near-infrared diode lasers[J]. Applied Optics(AIAA), 2003, 42(12): 2043-2051. [4] PALAGHITA T I, SEITZMAN J M. Absorption based temperature distribution sensing for combustor diagnostics and control[C]// 44th AIAA Aerospace Sciences Meeting and Exhibit. Reno, USA: American Institute of Aeronautics and Astronautics(AIAA), 2006: 0430. [5] LIU T C, JEFFRIES J B, HANSON R K. Wavelength modulation absorption spectroscopy with 2f detection using multiplexed diode lasers for rapid temperature measurements in gaseous flows[J]. Applied Physics, 2004, B78(3): 503-511. [6] TEICHERT H, FERNHOLZ T, EVERT V. In situ measurement of CO, H2O and gas temperature in a lignite-fired power-plant[C]//8th Topical Meeting on Laser Applications to Chemical and Environmental Analysis (8th LACEA). Washington DC, USA: Optical Society of America (OSA), 2002: ThB3. [7] PHOLIPPE L C, HANSON R K. Laser diode wavelength-modulation spectroscopy for simultaneous measurement of temperature, pressure, and velocity in shock-heated oxygen flows[J]. Applied Optics, 1993, 32(30): 6090-6103. doi: 10.1364/AO.32.006090 [8] CHYANG L S, STRAND C L, JEFFERIES J B, et al. Supersonic mass-flux measurements via tunable diode laser absorption and nonuniform flow modeling[J]. AIAA Journal, 2011, 49(12): 2783-2791. doi: 10.2514/1.J051118 [9] WANG G Y, HONG Y J, PAN H, et al. Diode laser absorption sensor for measurements of temperature and velocity in supersonic flow[J]. Acta Optica Sinica, 2013, 33(9): 0912009 (in Chinese). doi: 10.3788/AOS201333.0912009 [10] CHRISTOPHER S, GOLDNSTEIN, IAN A, et al. Tunable diode laser absorption sensor for measurements of temperature and water concentration in supersonic flows[C]// 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Orlando, USA: AIAA, 2011: 1-94. [11] LU W Y, ZHU X R, LI Y S, et al. Comparison of direct absorption and wavelength modulation methods for online measurement of CO2 by TDLAS[J]. Infrared and Laser Engineering, 2018, 47(7): 717002(in Chinese). doi: 10.3788/IRLA201847.0717002 [12] ZHAI Ch, YAN J, WANG X N, et al. The instrument research on high temperature measurement based on the tunable diode laser absorption spectroscopy[J]. Opto-Electronic Engineering, 2015, 42(8): 86-90(in Chinese). [13] SUN P S, ZHANG Zh R, CUI X J, et al. Multipath real-time measurement of temperature and H2O concentration for combustion diagnosis[J]. Chinese Journal of Lasers, 2015, 42 (9): 915002(in Chinese). doi: 10.3788/CJL201542.0915002 [14] GILLET B, HARDALUPAS Y, KAVOUNIDES C, et al. Infrared absorption for measurement of hydrocarbon concentration in fuel air mixtures[J]. Applied Thermal Engineering, 2004, 24(11/12): 1633-1653. [15] BUSA K M, ELLISION E N, McGOVERN B J, et al. Measurements on NASA langley durable combustor rig by TDLAT preliminary results[C]//51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. Grapevine, USA: AIAA, 2013: 0696. [16] MA L, CAI W W. Numerical investigation of hyperspectral tomography for simultaneous temperature and concentration imaging[J]. Applied Optics, 2008, 47(21): 3751-3759. doi: 10.1364/AO.47.003751 [17] CAI W W, MA L. Hyperspectral tomography based on proper orthogonal decomposition as motivated by imaging diagnostics of unsteady reactive flow[J]. Applied Optics, 2010, 49(4): 601-610. doi: 10.1364/AO.49.000601 [18] HUANG J Q, LIU H C, DAI J H, et al. Reconstruction for limited-data nonlinear tomography absorption spectroscopy via deep learning[J]. Journal of Quantitative Spectroscopy & Radiative Transfer, 2018, 218: 187-193. [19] YU T, CAI W W, LIU Y Z. Rapid tomography reconstruction based on machine learning for time-resolved combustion diagnostics[J]. Review of Scientific Instruments, 2017, 89(4): 043101. [20] QIU X B, WEI J L, SUN D Y, et al. A miniaturized laser measurement instrument of ammonia escaping from coal-fired power plants[J]. Laser Technology, 2019, 43(5): 697-701(in Chinese). [21] SHAO L G, QIU X B, WEI J L, et al. Multipass absorption spectroscopy based on calibration-free wavelength modulation[J]. Laser Technology, 2019, 43(6): 795-799(in Chinese).