VISUAL MONITORING METHOD FOR CROSS-SECTION TEMPERATURE FIELDS AND RADIATION CHARACTERISTICS OF BOILER FURNACES BY COMBINING RADIATION IMAGES AND SPECTRA

Abstract

Disclosed in the present invention is a visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra. Image detectors can be directly inserted into observation holes of a boiler to acquire flame image data, so that when the detection system is applied to a power station boiler, extra holes are not required to be drilled, and therefore, there is no risk that the strength of a furnace wall of the boiler is reduced by drilling holes. According to cross-section temperature fields of a furnace measured by the detection system, the state of combustion in the furnace can be accurately judged, which can play an accurate and effective guiding role in boiler combustion control, and reduce the temperature deviation in each combustion area of the boiler so as to keep the boiler running smoothly, thereby improving the combustion efficiency of the boiler.

Claims

1. A visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra, wherein flame radiation images and spectra in a furnace are synchronously acquired respectively by image detectors and a spectrometer, a flame image temperature is corrected according to an emissivity ratio obtained by analysis on the flame radiation spectra, and according to a reconstruction algorithm based on a radiation intensity imaging model, a temperature distribution and an absorption coefficient distribution in the furnace are reconstructed simultaneously.

2. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 1, wherein a dual-narrow-band pass color filter is installed in front of the image detectors, two central wavelengths ?.sub.G and ?.sub.R of the dual-narrow-band pass color filter correspond to peaks of spectral response curves of G and R channels of an industrial camera respectively, a half-band width is less than 20 nm, and the emissivity ratio is a ratio ?.sub.?.sub.G/?.sub.?.sub.R of emissivities of a flame at the central wavelengths of ?.sub.G and ?.sub.R.

3. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 1, wherein the reconstruction algorithm based on the radiation intensity imaging model comprises the following steps: 1) meshing a cross-section of the furnace: dividing the cross-section of the furnace into m space medium units and n wall units; 2) constructing the radiation intensity imaging model; 3) reconstructing a monochromatic blackbody radiation intensity distribution by using a regularization algorithm, and in the process of calculation, introducing the emissivity ratio obtained by spectrum analysis to correct a cross-section temperature field reconstruction matrix; 4) updating an absorption coefficient and a scattering coefficient by using a Newton iteration algorithm, and calculating a temperature distribution when a residual is extremely small; and 5) calculating an absorption coefficient distribution by taking the scattering coefficient as a known parameter.

4. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 3, wherein the radiation intensity imaging model is as follows: a flame monochromatic radiation intensity received by each pixel unit of the image detectors is expressed by Equation (1): $\begin{array}{cc}{I}_{?}\left(O,s\right)={?}_0^{l_w}\left[\frac{1}{?}{e}^{-\underset{l}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(l\right)n^2\right]I_{b?}\left(T,v\right)\mathrm{dl}+\underset{S}{?}\left[{?}_0^{l_w}\frac{1}{?}{e}^{-\underset{l}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(v\right)n^2{R}_d^s\left(v,l,s\right)\mathrm{dl}+\frac{4}{?}{e}^{-\underset{l_w}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(v\right)n^2{R}_d^s\left(v,w,s\right)\right]I_{b?}\left(T,v\right)\mathrm{ds}& \left(1\right)\end{array}$ where, l and l represent paths of a radiation transmission of the space medium units, l.sub.w represents a path of a radiation transmission of the wall unit, and w represents the wall unit; v and v represent the space medium units; s represents a whole space medium area; ? is a Stefan-Boltzmann constant, 5.67?10.sup.-8, W/(m.sup.2.Math.K.sup.4); a parameter in a shape of Rd.sup.s (a, b, s) is called DRESOR number and represents a product of 4? and a share of energy emitted from a volume element centered on a point a scattered by a unit volume centered on a point b within a unit solid angle with s as a center line; k and n are a medium absorption coefficient and a refractive index; ?=?+K is an attenuation coefficient, and ? is a medium scattering coefficient; ? is a wall emissivity; and I.sub.b? is a monochromatic blackbody radiation intensity, W/m.sup.3.sr; according to the Planck's Blackbody radiation law: $\begin{array}{cc}{I}_{b?}\left(T\right)=\frac{1}{?}\frac{C_1}{{?}^5}\exp \left(-\frac{C_2}{?T}\right)& \left(2\right)\end{array}$ the Equation (1) is discretized to obtain: $\begin{array}{cc}\begin{array}{c}{I}_{?}\left(i\right)=\underset{j=1}{\overset{m}{.Math.}}{R}_{d,{\mathrm{gI}}_{?}}\left(j.fwdarw.i\right)4{?}_j\frac{1}{?}\frac{C_1}{{?}^5}\exp \left(-\frac{C_2}{?T_{g,j}}\right)))?S_{g,j}\\ =\underset{j=1}{\overset{m}{.Math.}}{A}_{I_{?}}\left(i,j\right)I_{b?}\left(j\right),i=1,.Math.,p\end{array}& \left(3\right)\end{array}$ where, R.sub.d,gI(j.fwdarw.i) represents the share of radiation from each unit in the furnace to each pixel unit of the image detectors; T.sub.g,j is the temperature of the space medium unit; ?S.sub.g,j is a space medium area element; and A.sub.I.sub.?(i, j)=R.sub.d,gI.sub.?(j.fwdarw.i)4?.sub.j is a radiation intensity imaging matrix; and for a R channel of the image detectors, the Equation (3) is matrixed to obtain: $\begin{array}{cc}{I}_{{?}_R}=A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{b{?}_R}\left(T\right).& \left(4\right)\end{array}$

5. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 3, wherein in step 3), in the process of calculation, it is first assumed that the absorption coefficient and the scattering coefficient ?.sub.?.sub.R and ?.sub.?.sub.R of a R channel at the corresponding wavelength ?.sub.R are uniformly distributed, so that a coefficient matrix $A_{I_{{?}_R}}$ is a known parameter, and a monochromatic blackbody radiation intensity distribution I.sub.b?.sub.R(T) is calculated by using the regularization algorithm; and one I.sub.b?.sub.R(T) is found to minimize the following Equation: $\begin{array}{cc}R\left(I_{{?}_R},?\right)={.Math.I_{{?}_R}-A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{b{?}_R}\left(T\right).Math.}^2+?{.Math.{\mathrm{DI}}_{b{?}_R}\left(T\right).Math.}^2& \left(5\right)\end{array}$ where a is a regularization parameter, and D is a regularization matrix; when the Equation (5) is minimized, a solution of the Equation (4) is: $\begin{array}{cc}\begin{array}{c}{I}_{b{?}_R}\left(T\right)={\left(A_{I_{{?}_R}}^T\left({?}_{{?}_R},{?}_{{?}_R}\right)A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)+?D^{T}D\right)}^{-1}{A}_{I_{{?}_R}}^T\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_R}\\ =B_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_R}\end{array}& \left(6\right)\end{array}$ where $B_{I_{{?}_R}}$ is a cross-section temperature field reconstruction matrix of the R channel; for a G channel, the solution of the Equation (4) is capable of being written as: $\begin{array}{cc}\begin{array}{c}{I}_{b{?}_G}\left(T\right)=B_{I_{{?}_G}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_G}\\ =B_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right).Math.\frac{{?}_{{?}_G}}{{?}_{{?}_R}}.Math.I_{{?}_G}\end{array}& \left(7\right)\end{array}$ where $B_{I_{{?}_G}}$ is a cross-section temperature field reconstruction matrix of the G channel, and ?.sub.?.sub.G/?.sub.?.sub.R is an emissivity ratio obtained by spectrum analysis.

6. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 5, wherein temperatures in the Equations (6) and (7) is capable of being calculated by the following Equation: $\begin{array}{cc}T=-\frac{C_2}{?}/\ln \left(\frac{I_{b?}{?}^5}{C_1}\right);& \left(8\right)\end{array}$ in the process of calculation, the absorption coefficient and the scattering coefficient ?.sub.?.sub.R and ?.sub.?.sub.R are updated by using the Newton iteration algorithm, temperature distributions reconstructed by the radiation intensities I.sub.?.sub.R and I.sub.?.sub.G acquired by the image detectors in the R and G channels are calculated respectively, the two temperature distributions after being averaged are substituted into the Equation (5) until the residual is minimized, so as to obtain a temperature field under an assumption of uniform ?.sub.?.sub.R and ?.sub.?.sub.R.

7. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 6, wherein the step 5) is based on an Equation (9), $\begin{array}{cc}{I}_{?}=A_{I_{?}}^{}?I_{b?}\left(T\right)& \left(9\right)\end{array}$ where, A.sub.I.sub.? is a new coefficient matrix that does not contain ?, and ?.sub.s is a known parameter; ?I.sub.b? (T) is calculated by using the regularization algorithm, and then the temperature distribution T calculated by the Equation (8) is substituted into ?I.sub.b?(T) so as to obtain a distribution of the absorption coefficient ?.

8. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 1, wherein there are four image detectors disposed at observation holes on a same layer of the furnace, the image detectors are perpendicular to an external fa?ade of the furnace and penetrates an inner side of a water-cooled wall, and the four image detectors communicate with a computer equipped with a control software.

9. The visual monitoring method for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra according to claim 1, wherein the spectrometer is bundled together with any one of the image detectors, and communicates with a computer through a data line, and a collimating lens is disposed at a front end of an optical fiber of the spectrometer, and the collimating lens is perpendicular to the external fa?ade of the furnace.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0037] FIG. 1 is a schematic diagram of a visual monitoring system for cross-section temperature fields and radiation characteristics of boiler furnaces by combining radiation images and spectra;

[0038] FIG. 2 is a schematic diagram of a field detection experiment;

[0039] FIG. 3 shows a typical flame radiation image acquired by an image detector;

[0040] FIG. 4 shows a flame radiation spectrum acquired by a fiber optic spectrometer;

[0041] FIG. 5 shows a detection result of a furnace cross-section temperature distribution;

[0042] FIG. 6 shows a detection result of a furnace cross-section absorption coefficient distribution; and

[0043] FIG. 7 is a comparison diagram of a calculated value and an initial value of a boundary radiation intensity.

DETAILED DESCRIPTION OF THE INVENTION

[0044] The present invention will be further described below with reference to the accompanying drawing and embodiments:

1. Composition of an Image Detector

[0045] With a common color industrial camera as an example, a flame image detector is formed by arranging a dual-narrow-band pass color filter in front of a camera sensor in combination with a long lens rod. Two central wavelengths ?.sub.R and ?.sub.G of the dual-narrow-band pass color filter are located near peaks of spectral response curves of R and G channels of the industrial camera respectively, and a half bandwidth is less than 20 nm, so as to cooperate with the camera to obtain an approximate monochromatic flame image with a high signal-to-noise ratio.

2. Arrangement Forms of Image Detectors and a Spectrometer

[0046] As shown in FIG. 1, four image detectors are arranged at observation holes on the same layer of a furnace, the image detectors are perpendicular to an external facade of the furnace and penetrates a certain distance inside a water-cooled wall to obtain a better field of view. The four image detectors are connected to a gigabit network switch via gigabit network cables, and then communicate with a computer equipped with control software via the gigabit network switch. The fiber optic spectrometer is bundled together with any one of the image detectors, and communicates with the computer via a USB data line, and a collimating lens is disposed at the front end of an optical fiber, and perpendicular to the external facade of the furnace.

3. Reconstruction of a Cross-Section Temperature Field

[0047] 1) The detectors and the spectrometer respectively acquire flame radiation images and spectra inside the furnace synchronously.

[0048] 2) A ratio ?.sub.?.sub.G/?.sub.?.sub.R of emissivities of a flame at wavelengths of ?.sub.G and ?.sub.R is calculated according to analysis on the flame radiation spectra.

[0049] 3) According to the size of the furnace, a cross-section of the furnace is divided into m space medium units and n wall units; if a furnace wall is a gray emission, absorption and diffuse reflection surface, the emissivity of the furnace wall is &, and it is assumed that ?=0.9.

[0050] Since a biquadrate relation is formed between the radiation intensity and the temperature, and the wall is covered with a water-cooled wall, the temperature of the wall is obviously lower than the flame temperature, so the radiation of the furnace wall is not considered, and only the flame radiation reflected by the furnace wall is considered.

[0051] 4) A flame monochromatic radiation intensity received by each pixel unit of the detector may be expressed by Equation (1):

[00013]$\begin{array}{cc}{I}_{?}\left(O,s\right)={?}_0^{l_w}\left[\frac{1}{?}{e}^{-\underset{l}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(l\right)n^2\right]I_{b?}\left(T,v\right)\mathrm{dl}+\underset{S}{?}\left[{?}_0^{l_w}\frac{1}{?}{e}^{-\underset{l}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(v\right)n^2{R}_d^s\left(v,l,s\right)\mathrm{dl}+\frac{4}{?}{e}^{-\underset{l_w}{?}?\left(l^{}\right){\mathrm{dl}}^{}}?\left(v\right)n^2{R}_d^s\left(v,w,s\right)\right]I_{b?}\left(T,v\right)\mathrm{ds}& \left(1\right)\end{array}$

[0052] where, l and l represent paths of radiation transmission of the space medium units, l.sub.w represents a path of radiation transmission of the wall unit, and w represents the wall unit; ? and ? represent the space medium units; s represents a whole space medium area; ? is a Stefan-Boltzmann constant, 5.67?10.sup.-8, W/(m.sup.2.Math.K.sup.4); a parameter in the shape of Rd.sup.s (a, b, s) is called DRESOR number and represents a product of 4? and the share of energy emitted from a volume element centred on point a scattered by a unit volume centred on point b within a unit solid angle with s as a center line; k and n are a medium absorption coefficient and a refractive index; ?=?+? is an attenuation coefficient, and ? is a medium scattering coefficient; ? is a wall emissivity; and I.sub.b? is a monochromatic blackbody radiation intensity, W/m.sup.3.sr. According to the Wien's radiation law:

[00014]$\begin{array}{cc}{I}_{b?}\left(T\right)=\frac{1}{?}\frac{C_1}{{?}^5}\exp \left(-\frac{C_2}{?T}\right)& \left(2\right)\end{array}$

[0053] Equation (1) is discretized to obtain:

[00015]$\begin{array}{cc}\begin{array}{c}{I}_{?}\left(i\right)=\underset{j=1}{\overset{m}{.Math.}}{R}_{d,{\mathrm{gI}}_{?}}\left(j.fwdarw.i\right)4{?}_j\frac{1}{?}\frac{C_1}{{?}^5}\exp \left(-\frac{C_2}{?T_{g,j}}\right)))?S_{g,j}\\ =\underset{j=1}{\overset{m}{.Math.}}{A}_{I_{?}}\left(i,j\right)I_{b?}\left(j\right),i=1,.Math.,p\end{array}& \left(3\right)\end{array}$

[0054] where, R.sub.d,gI(j.fwdarw.i) represents the share of radiation from each unit in the furnace to each pixel unit of the image detector; T.sub.g,j is the temperature of the space medium unit; ?S.sub.g,j is a space medium area element; and A.sub.I.sub.?(i,j)=R.sub.d,gI.sub.?(j.fwdarw.i)4?.sub.j is a radiation intensity imaging matrix; and for a R channel of the image detector, Equation (3) is matrixed to obtain:

[00016]$\begin{array}{cc}{I}_{{?}_R}=A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{b{?}_R}\left(T\right)& \left(4\right)\end{array}$

[0055] 5) In the process of calculation, it is first assumed that the absorption coefficient and the scattering coefficient ?.sub.?.sub.R and ?.sub.?.sub.R of the R channel at the corresponding wavelength ?.sub.R are uniformly distributed. In this case, a coefficient matrix

[00017]$A_{I_{{?}_R}}$

is a known parameter, and a monochromatic blackbody radiation intensity distribution I.sub.b?.sub.R(T) can be calculated by using the regularization algorithm. The base principle is to find one I.sub.b?.sub.R(T) to minimize the following Equation:

[00018]$\begin{array}{cc}R\left(I_{{?}_R},?\right)={.Math.I_{{?}_R}-A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{b{?}_R}\left(T\right).Math.}^2+?{.Math.{\mathrm{DI}}_{b{?}_R}\left(T\right).Math.}^2& \left(5\right)\end{array}$

[0056] where a is a regularization parameter, and D is a regularization matrix. When Equation (5) is minimized, a solution of Equation (4) is:

[00019]$\begin{array}{cc}\begin{array}{c}{I}_{b{?}_R}\left(T\right)={\left(A_{I_{{?}_R}}^T\left({?}_{{?}_R},{?}_{{?}_R}\right)A_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)+?D^{T}D\right)}^{-1}{A}_{I_{{?}_R}}^T\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_R}\\ =B_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_R}\end{array}& \left(6\right)\end{array}$

[0057] where

[00020]$B_{I_{{?}_R}}$

is a cross-section temperature field reconstruction matrix of the R channel.

[0058] For a B channel, the solution of Equation (4) can be written as:

[00021]$\begin{array}{cc}\begin{array}{c}{I}_{b{?}_G}\left(T\right)=B_{I_{{?}_G}}\left({?}_{{?}_R},{?}_{{?}_R}\right)I_{{?}_G}\\ =B_{I_{{?}_R}}\left({?}_{{?}_R},{?}_{{?}_R}\right).Math.\frac{{?}_{{?}_G}}{{?}_{{?}_R}}.Math.I_{{?}_G}\end{array}& \left(7\right)\end{array}$

[0059] where

[00022]$B_{I_{{?}_G}}$

is a cross-section temperature field reconstruction matrix of the G channel, and ?.sub.?.sub.G/?.sub.?.sub.R is an emissivity ratio obtained by spectrum analysis.

[0060] 6) The temperatures in Equations (6) and (7) can be calculated by the following Equation:

[00023]$\begin{array}{cc}T=-\frac{C_2}{?}/\ln \left(\frac{I_{b?}{?}^5}{C_1}\right)& \left(8\right)\end{array}$

[0061] in the process of calculation, the absorption coefficient and the scattering coefficient ?.sub.?.sub.R and ?.sub.?.sub.R are updated by using the Newton iteration algorithm, temperature distributions reconstructed by the radiation intensities I.sub.?.sub.R and I.sub.?.sub.G acquired by the image detector in the R and G channels are calculated respectively, and the two temperature distributions after being averaged are substituted into Equation (5) until the residual is minimized, so as to obtain a temperature field under an assumption of uniform ?.sub.?.sub.R and ?.sub.?.sub.R.

[0062] 7) ?.sub.?.sub.R is a known parameter, and Equation (4) can be amended to:

[00024]$\begin{array}{cc}{I}_{{?}_R}=A_{I_{{?}_R}}^{}{?}_{{?}_R}{I}_{b{?}_R}\left(T\right)& \left(9\right)\end{array}$

[0063] where,

[00025]$A_{I_{{?}_R}}^{}$

is a new coefficient matrix that does not contain ?.sub.?.sub.R.Math.?.sub.?.sub.RI.sub.b?(T) is calculated by using the regularization algorithm, and then the temperature distribution T calculated by Equation (8) is substituted into ?.sub.?.sub.RI.sub.b?(T) so as to obtain a distribution of the absorption coefficient ?.sub.?.sub.R.

4. Implementation of Real-Time Visual Monitoring for Cross-Section Temperature Fields and Radiation Characteristics of Boiler Furnaces by Combining Radiation Images and Spectra in a Boil Site

[0064] In this embodiment, the real-time visual monitoring of cross-section temperature distribution and radiation characteristics of boiler furnaces by combining radiation images and spectra is performed at three heights above a burner layer of a 600 MW tangentially fired boiler in a coal-fired power plant somewhere, and a field detection experiment is schematically shown in FIG. 2. FIG. 2 shows the furnace size of each layer and the positions of the four image detectors, shaded areas indicate actual cross-section of the furnace, and the fiber optic spectrometer is bundled together with the image detector #1.

[0065] Typical flame radiation images acquired by the image detectors under five operating conditions (330 MW at the first layer, 330 MW at the second layer, and 330 MW, 500 MW and 550 MW at the third layer) are shown in FIG. 3, where exposure time is marked. It can be seen that when a load is 330 MW, there is no significant difference in the brightness of flame images acquired by the same image detector at the 1st to 3rd layers, but the exposure time decreases with the decrease of the height of the detection layer. This is due to that the detection layer at a lower position is closer to a burner region, and the flame radiation is stronger. In order to avoid image saturation, acquisition software of the image detectors moderately reduces the exposure time of an acquired image, so that the flame image has a high signal-to-noise ratio while it is unsaturated. In the third layer of field detection, with the increase of the boiler load, the exposure time of flame image acquisition also decreases. After the image detectors are subjected to blackbody furnace radiation calibration, acquired flame images can be converted into radiation intensity images.

[0066] The flame radiation spectrum acquired by the fiber optic spectrometer is shown in FIG. 4. The emissivity ratios obtained by spectrum analysis under five operating conditions are 0.9153 (1-330 MW), 0.9341 (2-330 MW), 0.8801 (3-330 MW), 0.8845 (3-500 MW) and 0.9032 (3-550 MW) respectively.

[0067] A flame radiation intensity corresponding to a horizontal position in each typical flame image in FIG. 3, after being interpolated by pixels from right to left to 100 pixel units, is used for reconstruction calculation so as to obtain cross-section temperature field and absorption coefficient distributions inside the furnace under four operating conditions as shown in FIGS. 5 and 6, and a cross-section grid resolution is 10?10. In FIG. 7, with an operating condition 3-330 MW as an example, a comparison between a calculated value and an initial value of a boundary radiation intensity is given according to the pixel units after interpolation (4 image detectors?100 pixel units). It can be seen that the reconstructed boundary radiation intensity is relatively smooth in comparison with an initial radiation intensity, but the two are basically consistent, which indicates that the reconstructed results of the cross-section temperature field and the space medium radiation parameters are very reliable.