(MSW) Combustion by Spectral Analysis and Image

Article pubs.acs.org/EF

Experiments on Measurement of Temperature and Emissivity of Municipal Solid Waste (MSW) Combustion by Spectral Analysis and Image Processing in Visible Spectrum Weijie Yan,† Huaichun Zhou,*,‡ Zhiwei Jiang,† Chun Lou,*,† Xiaoke Zhang,§ and Donglin Chen†† †

State Key Laboratory of Coal Combustion, Huazhong University of Science & Technology, Wuhan, 430074, China Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China § Shanghai Environment Protection Group, Shanghai 200123, China †† Key Laboratory for Power Technology of Renewable Energy Sources of Hunan Province, Changsha University of Science and Technology, Changsha, 410015, China ‡

ABSTRACT: This paper presents an experimental investigation on the measurement of temperature and emissivity in a 46 ton/ h Municipal Solid Waste (MSW) incinerator using a spectrometer system and a flame image detection system. The spectroscopy analysis shows that strong Na (590 nm) and K (767 nm) emission occurs in the visible spectrum of the flame in the MSW incinerator, which demonstrates a typical nongray property of radiation. The two-color method is used to calculate the temperature and emissivity of the flame from the continuous spectrum and the visible flame image, and the results indicate that except for the Na (590 nm) and K (767 nm) emission lines, the continuous spectrum from the particulate medium in the flame meets the gray property. Since the strong but narrow Na and K emission lines deviate away from the central wavelengths of red (R) and green (G) in the spectral response curves of the CCD camera, the two-color method can be used to calculate the temperature and emissivity images by the flame image detection system. The preliminary experimental results show that these two techniques will be helpful for combustion research and monitoring in MSW incinerators.

1. INTRODUCTION More and more municipal solid waste is being generated with the development of the economy and urbanization in China; so reducing the amount of MSW, making it innocuous, and/or converting it into fuel has become an important issue for the government. Incineration technology is considered as one of the best practical choices at present, through generating heat and then transforming the heat to electricity by urban energy system with fast treatment speed, high efficiency in waste reduction, energy reutilization, and so on. Combustion in an MSW incinerator is a complex phenomenon involving mass and heat transfer, and chemical reactions. Powerful and reliable combustion measuring and monitoring technologies are required for the development and optimization of MSW incineration equipment. Many methods for measuring temperatures in furnaces have been developed in the past. In practice, the most widely applied methods are thermocouples and pyrometers, which can only provide single-point measurement and suffer from degradation in harsh environments. Optical methods based on laser diagnostic techniques can measure flame temperatures distributions.1−4 However, due to the large dimensions of a furnace whose size may be more than 10 m and the limited power of a laser that will be almost absorbed by the particle medium and is hard to transmit from one side to another one, these methods are difficult for applications in flame measurements for large-scale, industrial furnaces. There are also reports in the literature on the application of spectroscopic measurements5−9 for furnace combustion control, burner balancing, and pollutant emission monitoring. The © 2013 American Chemical Society

basic idea is to process spectral signals using complex algorithms to provide radiative intensity of flame that can be used for feedback combustion control. The multiwavelength method10,11 has been developed by many researchers with the assumption that the change of emissivity with wavelength satisfies certain regularity. Flame image processing techniques in the visible spectrum have been used as effective tools for measurements of flame temperature and radiative properties12−26 during the recent years. In this technology, the twocolor method is usually utilized based on the assumption that the emissivity at the two wavelengths is the same. A method for judging the gray property of flames based on spectral analysis and the two-color method for determining the temperature and emissivity of a flame has been reported.8 The results showed that the gasoline flame can be assumed to be a gray body in the range between 550 and 900 nm; for the coal-fired flame, the range is between 500 and 1000 nm, while the red phosphorus flame cannot be assumed to be a gray body within the measurement wavelength range. This paper aims to investigate the applicability of the measurement method of temperature and emissivity by spectral analysis and image processing in the visible spectrum for the combustion in a MSW incinerator. First, the spectrometer system and the flame image detection system are introduced. Then, based on the continuous spectrum in the visible Received: July 18, 2013 Revised: September 14, 2013 Published: October 15, 2013 6754

dx.doi.org/10.1021/ef401374y | Energy Fuels 2013, 27, 6754−6762

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spectrum, the method is described to select the proper wavelength regime where the assumption of gray radiation of flames is satisfied and the measurement method for the temperature and emissivity of the flames using the two-color method is applicable. Experiments are conducted on a 46 ton/h MSW incinerator to analyze the flame spectrum, and to examine the applicability of utilization of R and G color data from the two-dimensional flame images obtained by the flame image detection system with a color digital camera. Finally, some concluding remarks are given.

2. EXPERIMENTAL METHODS The spectrometer system consists of a spectrometer, a probe, and a portable computer. The measuring probe consists of a special collimating lens and a fiber-optic cable. The MeChrome plated brass casing was constructed to allow the insertion of the fiber-optic cable into the high-temperature environment inside a MSW incinerator. The COL-UV/vis, collimating lens, screws onto the end of the fiber optic entrance connector and converts the divergent beam of radiation into a parallel beam. An AvaSpec-2048 Fiber-Optic Spectrometer is used to process the incoming light data. The AvaSpec-2048 Fiber Optic Spectrometer is based on the AvaBench-75 symmetrical Czerny-Turner design with 2048 pixel CCD Detector Array, and advantages for the CCD detector are many pixels, high sensitivity, and high speed. A choice of 16 different gratings with different dispersion and blaze angles enable applications in the 200−1100 nm range. The spectral resolution of this spectrometer is 0.4−0.6 nm. The spectrometer connected to a portable computer through a USB cable via an AvaSoft−7.4 USB2 interface. For the spectrometer, its sampling period is 1.1 ms, and the data transferring speed is 1.8 ms per time of sampling. According to the magnitude of the intensity of radiation of the object, it allows integration time from 1.1 ms to 600 s to ensure adequate S/N ratio. In the experiments reported in this paper, the exposure (integration) time of the spectroscopy is about several hundred milliseconds, that means the measurement of radiative intensities at different wavelengths by the spectrometer is performed almost simultaneously. Figure 1a shows the entire spectrometer system in a nonintrusive environment. The constituent elements and structure of the flame image detection system is shown in Figure 1b. The system consists of a notebook PC with a frame-grabber and an optical detector. The optical detector consists of an image guide, a Samsung SCC-2313P color CCD camera and a lithium battery. The image guide is constructed from a stainless steel pipe and a group of optical lenses. An objective lens is fixed at the front end of the optical detector with a viewing angle of 90°. The light conveyed by the optical detector enters the color camera. The shutter speed of the color camera is adjustable from 1/120 to 1/10 000 s. The lithium battery is used to supply the power for the camera. The video signals from the color camera are transferred into the portable computer through a video cable. A MVT-610 PCMCIA frame grabber transfers the color camera’s signal into a 2D digital color image with 8-bit digitization. Notably, the material of the optical detector is austenitic stainless steel which can resist a high temperature of 1675 K, and the material of the objective lens is a single crystal of Al2O3, which is resistant to high temperature of 2100 K. So, there is no cooling air for the optical detector, this makes the flame image detection system more flexible.

Figure 1. (a) Schematic of the spectrometer system; (b) schematic of the flame image detection system.

3. THEORETICAL BASIS The intensity of radiation emitted by an object at wavelength λ, is dependent on the object’s emissivity ε(λ) and the temperature T according to Planck’s Law: I (λ , T ) = ε (λ )

2πhc 2 λ 5(ehc / λkT − 1)

(1)

where h is Planck’s constant, c is the speed of light, and k is the Boltzmann constant. For wavelength range from 300 to 1000 nm and a temperature range from 800 to 2000 K, since hc/λkT ≫ 1, Planck’s law can be replaced by Wien’s radiation law: I (λ , T ) = ε( λ )

2πhc 2 = ε(λ)Ib(λ , T ) λ 5(ehc / λkT )

(2)

where Ib(λ,T) is the monochromatic blackbody radiation intensity. The spectrometer system can get the monochromatic radiation intensity within a certain wavelength range, and the flame image detection system could get approximately monochromatic radiation images of red (R), green (G), and blue (B).19,24−26 However, the output of two systems is just a voltage value converted from the radiation signal through photoelectric conversion. So, it is necessary to calibrate the output value to get the monochromatic radiation intensity. A Mikron Model M330 blackbody furnace with temperature range from 500 to 2000 K (with temperature errors within ±1 K) was used to calibrate the two systems. The characteristic calibration profiles of the spectrometer system at the different temperatures are shown in Figure 2, and Figure 3 shows the variations of Ir and Ig with the R and G data, when the shutter speed of the color camera is 1/250 s. The principle of judging the gray property of flames based on spectral analysis and the two-color method for determining the 6755


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ε(λ) = I(λ , T )/Ib(λ , T )

(4)

The wavelength range meeting the gray property is determined as where the emissivity does not change obviously with the wavelength. Once it is determined, the nearly constant temperature calculated by the two-color method within this wavelength range can be taken as the temperature to be measured, as well as the averaged emissivity calculated from those obtained from eq 4. It is a process that an assumption is validated. One can always select a small enough wavelength internal Δλ to make the variation of emissivity over this small spectral interval “negligible”. But the judgment used to confirm if the property is gray is done over a large range of wavelength, not over a small spectral interval. According to the spectroscopic responses of the CCD camera of the color flame image detector, the central wavelengths of red and green are λr = 625 nm and λr = 520 nm, respectively. For the flame image detection system, T can be calculated from the ratio of two monochromatic intensity images Ir and Ig by the two-color method,

Figure 2. Characteristic calibration curves for the spectrometer at three temperatures.

⎡ I (λ , T ) λ 5 ε ⎤ ⎛1 1⎞ r r⎥ T = −C2⎜⎜ − ⎟⎟ /ln⎢ r 5 ⎢ λ λ λ ε I ( , T ) λ ⎝ r g⎠ g⎥ ⎣ g ⎦ g

(5)

If the central wavelengths λr and λg are within the wavelength range meeting the gray property deduced from the spectral analysis method using the spectrometer mentioned above, it is reasonable to set εr/εg ≈ 1, and the flame temperature image can be got from the above equation. At the same time, the flame emissivity image ε can also be calculated from one monochromatic intensity image as follows: ε = Irπλr5/(C1 e−C2 / λrT )

(6)

Before being used in experiments, the flame image detection system was calibrated using the blackbody furnace. Tables 1 Table 1. Comparison of the Calculated Temperature and Emissivity with Those of the Blackbody Furnace Using the Spectrometer System temp.

Figure 3. Variations of (a) Ir and (b) Ig with the R, and G data.

temperature and emissivity of a flame has been described.8 Based on the assumption of a constant emissivity at wavelengths λ and λ + Δλ, the temperature T is given by

emissivity

blackbody temp. (K)

blackbody emissivity

calc. (K)

errors (%)

calc.

errors (%)

960 1160 1221 1285 1344 1399 1499 1566

0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99

964 1152 1206 1270 1319 1392 1485 1556

0.42 0.69 1.23 1.17 1.86 0.50 0.93 0.64

0.94 0.98 0.98 0.98 1.03 0.97 1.01 1.02

5.05 1.01 1.01 1.01 4.04 2.02 2.02 3.03

and 2 give a comparison of the measured values of temperature and emissivity by the flame image detection system and the setting values of the blackbody furnace. The maximum errors for the temperature and the emissivity are within 2% and 6%, respectively. It is noted that both the spectrometer system and the flame image detection system detect line-of-sight radiation intensity. Actually, since combustion in a MSW incinerator is turbulent and nonuniform in temperature and species concentrations, it is best to reconstruct the 2D and/or 3D distribution of local quantities inside the isothermal and homogeneous combustion

⎤ ⎛1 1 ⎞ ⎡ I (λ , T ) λ5 ⎟ /ln⎢ T = − C 2⎜ − ⎥ ⎝λ λ + Δλ ⎠ ⎣ I(λ + Δλ , T ) (λ + Δλ)5 ⎦ (3)

After the temperature T is obtained, the emissivity ε(λ) can be found from the following simple equation, it equals the ratio of the radiation intensity of an object to the blackbody intensity at the same temperature: 6756


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Table 2. Comparison of the Calculated Temperature and Emissivity with Those of the Blackbody Furnace by Flame Image Detection System temp.

emissivity

blackbody temp. (K)

blackbody emissivity

calc. (K)

errors (%)

calc.

errors (%)

1081 1127 1173 1212 1244 1273 1300 1324 1351 1373 1409 1425 1449 1473 1499

0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99 0.99

1080 1125 1171 1208 1240 1270 1298 1320 1348 1371 1404 1420 1446 1469 1495

0.12 0.20 0.20 0.33 0.32 0.26 0.15 0.32 0.21 0.14 0.38 0.35 0.22 0.25 0.23

0.97 0.96 0.96 0.94 0.94 0.95 0.97 0.94 0.96 0.98 0.94 0.94 0.96 0.96 0.96

1.66 3.21 3.06 5.24 4.92 3.71 1.73 4.68 2.69 1.40 5.17 4.70 2.55 2.95 2.66

Figure 4. Schematic of the MSW incinerator and the experimental measurement ports.

chamber, as done for a large-scale, coal-fired boiler furnace through a visible flame image processing system with 20 flame image detectors.9 As a preliminary step reported in this paper without the installation of a system with multiple flame image detectors, we just try to obtain and analyze the line-of-sight information of flame temperature and emissivity by spectrometer system and the flame image detection system with a single flame detector.

4. RESULTS AND DISCUSSION 4.1. Measurements by Spectral Analysis. Experiments were conducted on a MSW incinerator with a steam capacity of 46 ton/h in a 12.5 MW power generation unit. The MSW incinerator was manufactured by the German FBE Company with reciprocating push machinery of moving grate, its inclination angle is 78° and the area of the grate is 86 m2. The schematic of the incinerator is shown in Figure 4. As shown in Figure 4, the measurements were carried out at three different cross sections along the height of the furnace and eight measurement points are available in all. The calibrated spectral radiant intensity profiles between 500 and 900 nm at the eight measurement points of the MSW incinerator are shown in Figure 5. As seen in Figure 5, the spectral radiant intensity profiles of #5 are the most powerful among all the eight measurement points. It is obvious that two different emission lines exist within the wavelength range of the 500 and 900 nm, originating from the alkali metals Na (590 nm) and K (767 nm) most likely found in the household garbage, which demonstrates a typical nongray property. The alkali metal K combines with Cl to form KCl, which has a low melting point and can condense on particles in the flue gas and on the super heater tubes. This increases the deposit rate on the tubes. In a complicated series of reactions, the KCl destroys the protective layer of chromium iron oxide on the tubes, thereby also increasing corrosion.27 These corrosion problems increase if the deposit is partly in the liquid phase. The spectral radiant intensity profiles at the 8 measurement points are taken to calculate the temperature and emissivity, and the calculation results for the wavelength range 500 to 900 nm are shown in Figure 6. In the calculation, the wavelength

Figure 5. Measured emission spectrum of the flame at the eight measurement points.

interval Δλ in eq 3 is chosen to be 3 nm. In principle, the wavelength interval should be very small, in order to make the variation of emissivity of the medium much smaller, which is the condition for the application of the two-color method to get the temperature and emissivity profiles reliably. The spectral resolution of the spectrometer used in this article is 0.4−0.6 nm, which meets the requirement mentioned above. In this case, the existence and effects of the Na and K emissions lines can be distinguished and then extracted from the examined range of wavelength suitable for estimation of the temperature which essentially does not change with the wavelength. However, this choice is limited by the increasing fluctuation in the calculated profiles of the temperature and emissivity profiles as the wavelength interval decreases. So, 3 nm is the trade-off for the wavelength interval to meet the requirements of both the approximately constant emissivity for application of the two-color method and not large variation in the calculation results for the temperature and emissivity profiles. Except for the two narrow wavelength bands in Figure 6, centered at 590 nm for Na and 767 nm for K, the emissivity of the flame seems to be fluctuating significantly in this wavelength range. From Figure 7, it can be seen that the fluctuation of the temperature with the wavelength clearly decreases with respect to that of the emissivity in Figure 6, and 6757


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radiant intensity profiles and intensified by the division of intensities at two wavelengths in eq 3. Actually, a temperature varying with wavelength does not exist; only one temperature exists and needs to be measured from one spectral radiant intensity profile, which can be obtained from the averaged temperature over the wavelength range from 500 to 900 nm, except the two emission lines. This temperature is then used to calculate again the emissivity of the flame varying with the wavelength from the spectral radiant intensity profiles, and the results are shown in Figure 8. The

Figure 8. Emissivity profiles of the flame at the eight measurement points between 500 and 900 nm with a constant averaged temperature for each intensity profile.

Figure 6. Profiles of emissivity of the flame at the eight measurement points between 500 and 900 nm.

fluctuation of the emissivity, except the two emission lines, is reduced tremendously compared to that in Figure 6, indicating that, except for the Na (590 nm) and K (767 nm) emissions lines, the continuous spectra from the particulate medium in the flame meets the gray property, and the two-color method can be used to measure the temperature and emissivity of the particulate medium in the MSW flame. The measured emissivity for the flame can be found from the averaged one within the wavelength range, except near the two emissions lines. The relative mean square deviations (RMS) of the temperature and emissivity between 500 and 900 nm, except that near the two emissions lines are shown in Table 3, which shows that all RMS are less than 5%. It should be noted that the emissivity across the Na (590 nm) and K (767 nm) emission lines is related to the average concentrations of the two elements along the line-of-sight of measurements, which can be studied and analyzed in future work. 4.2. Measurements by Image Processing. For the flame image detection system, as shown in Figure 9, the Na (590 nm) and K (767 nm) emission lines deviate away from the central wavelengths λr and λg, that is, 520 nm for red (R) and 625 nm for green (G) in the spectral response curves of the CCD camera. Since the emission lines are much narrower than the band widths of the red (R) and green (G) response curves of the CCD camera, it is guessed that the contribution of the Na (590 nm) and K (767 nm) emission lines to the red (R) and green (G) responses of the CCD camera would not be large. A sensitive analysis for the influence of Na and K emission lines on temperature measurement is made. In the analysis, the temperature varies between 1000 and 2000 K and emissivity is kept constant (0.25). The relative error of temperature affected by Na and K emission lines is shown in Figure 10. It is found that even though the intensity of single emission lines (Na or

Figure 7. Profiles of temperature of the flame at the eight measurement points between 500 and 900 nm.

except the two emission lines, the temperatures seem to keep nearly constant as the wavelength varies. The nature of the fluctuation in the temperature and emissivity profiles is caused by the measurement errors and fluctuation in the spectral 6758


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Table 3. Temperatures and Emissivity, and Their Relative Mean Square Deviations (RMS), between 500 and 900 nm Calculated for the 8 Measurement Points of the MSW Incinerator measurement points items

#1

#2

#3

#4

#5

#6

#7

#8

Ta (K) σT (%) εa σε

1392 3.87 0.33 4.42

1407 3.97 0.48 4.69

1370 3.98 0.45 4.38

1398 3.84 0.29 4.35

1448 4.08 0.51 4.30

1498 3.90 0.30 4.54

1189 3.90 0.21 4.84

1215 4.05 0.22 4.72

Figure 9. Spectral response curves of the R and G bands of the color digital camera and the measured emission spectrum of the flame.

Figure 11. Typical flame images taken at three measurement points, (a) #1 measurement point, (b) #3 measurement point, and (c) #5 measurement point.

Figure 10. Relative error of temperature affected by the intensity of Na and K emission lines.

K) varies simultaneously between zeros and 50 times, there has little influence on temperature measurement, since the spectral response curves of the R and G bands of the CCD camera is much broader than the bandwidth of the Na and K emission lines. From Figure 10, we could also see that the intensity of Na and K emission lines mainly affect the low temperature measurement. For the high temperature measurement, even if the intensity of Na and K emission lines vary 50 times, it only leads to a small relative error (no more than 2%). So, the twocolor method can be used to deliver the temperature and emissivity images from the flame images. Using the flame image detection system, many flame images were captured during the experiments. Figure 11 depicts the

typical images obtained from #1, #3, and #5 measurement points, and the corresponding temperature and emissivity images obtained from the same measurement points are shown in Figures 12 and 13, respectively. An online continuous monitoring of the flame was conducted over a period of 30 min by the two detection systems when the MSW incinerator was working steadily. Table 4 shows the operating parameters of MSW incinerator throughout the experiment period to relate the experiment results with characters of the MSW incinerator. The measurement results from the spectrometer system have been compared with those by the flame image detection system shown in Figure 14. Both 6759


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Figure 13. 2-D emissivity distributions at (a) #1, (b) #3, and (c) #5 measurement points. Figure 12. 2-D temperature distributions at (a) #1, (b) #3, and (c) #5 measurement points.

Table 4. Operating Parameters of MSW Incinerator Throughout the Experiment Period

the average temperatures and emissivity measured by the two systems agree well with each other, and the maximum relative difference of the average temperature and the emissivity are within 5% and 10%, respectively.

5. CONCLUSIONS This paper reports the experimental investigations on simultaneous measurement of temperature and emissivity in a MSW incinerator by spectral analysis and image processing in the visible spectrum. The spectrometer and the flame image detection system used for the measurements have been calibrated by using a blackbody furnace. Through the spectroscopic analysis, we know that the flame of the MSW incinerator has strong Na (590 nm) and K (767 nm) emissions lines in the visible spectrum. The two color method is used to calculate the temperature and emissivity of the flame from the spectral radiant intensity profiles. The emissivity of the flame

operation param.

values

units

steam flow primary air flow hot primary air temp. primary air pressure roof temp. CO content NOX content

30 54 226 100 751 4 299

ton/h ton/h °C mmH2O °C mg/m3 mg/m3

seems to be fluctuating significantly in the visible spectrum, while, except for the two emission lines, the temperatures seem to keep nearly constant across the range of wavelength used. An averaged temperature is found across the wavelength range from 500 to 900 nm, except for the two emission lines, and this temperature is then used to calculate again the emissivity of the flame varying with the wavelength from the spectral radiant intensity profiles. The results indicated that, except the Na (590 nm) and K (767 nm) emissions lines, the continuous spectra 6760


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(2) Zhao, H.; Ladommatos, N. Optical Diagnostics for Soot and Temperature Measurement in Diesel Engines. Prog. Energy Combust. 1998, 24, 221−255. (3) Berry Yelverton, T. L.; Roberts, W. L. Soot Surface Temperature Measurements in Pure and Diluted Flames at Atmospheric and Elevated Pressures. Exp Therm Fluid Sci. 2008, 33, 17−22. (4) Lou, C.; Chen, C.; Sun, Y.-P.; Zhou, H.-C. Review of Soot Measurement in Hydrocarbon−Air Flames. Sci. China Technol. Sci. 2010, 53, 2129−2141. (5) Keyvan, S.; Rossow, R.; Romero, C.; Li, X.-X. Comparison between Visible and Near-IR Flame Spectra from Natural Gas-Fired Furnace for Blackbody Temperature Measurements. Fuel 2004, 83, 1175−1181. (6) Romero, C.; Li, X.-C.; Keyvan, S.; Rossow, R. SpectrometerBased Combustion Monitoring for Flame Stoichiometry and Temperature Control. Appl. Thermal Eng. 2005, 25, 659−676. (7) Keyvan, S.; Rossow, R.; Romero, C. Blackbody-Based Calibration for Temperature Calculations in the Visible and Near-IR Spectral Ranges Using a Spectrometer. Fuel 2006, 85, 796−802. (8) Sun, Y.-P.; Lou, C.; Zhou, H.-C. A Simple Judgment Method of Gray Property of Flames Based on Spectral Analysis and the TwoColor Method for Measurements of Temperatures and Emissivity. Proc. Combust Inst. 2011, 33, 735−741. (9) Wang, H.-J.; Huang, Z.-F.; Wang, D.-D.; Luo, Z.-X.; Sun, Y.-P.; Fang, Q.-Y.; Lou, C.; Zhou, H.-C. Measurements on Flame Temperature and Its 3D Distribution in a 660 MWe Arch-fired Coal Combustion Furnace by Visible Image Processing and Verification by Using an Infrared Pyrometer. Meas. Sci. Technol. 2009, 20 (12pp), 114006. (10) Fu, T.-R.; Peng, T.; Huan, Z.; Yi, S. Fast Fiber-Optic MultiWavelength Pyrometer. Rev. Sci. Instrum. 2011, 82, 064901−064908. (11) Wen, C.-D.; Mudawar, I. Mathematical Determination of Emissivity and Surface Temperature of Aluminum Alloys Using Multispectral Radiation Thermometry. Int. Commun. Heat Mass 2006, 33, 1063−1070. (12) Huang, Y.; Yan, Y.; Riley, G. Vision-Based Measurement of Temperature Distribution in a 500-Kw Model Furnace Using the Two-Color Method. Measurement 2000, 28, 175−183. (13) Vattulainen, J.; Nummela, V.; Hernberg, R.; Kytola, J. A System for Quantitative Imaging Diagnostics and Its Application to Pyrometric In-Cylinder Flame-Temperature Measurements in Large Diesel Engines. Meas. Sci. Technol. 2000, 11, 103−119. (14) Lu, G.; Yan, Y.; Riley, G.; Bheemul, H. C. Concurrent Measurement of Temperature and Soot Concentration of Pulverized Coal Flames. IEEE Trans. Instrum. Meas. 2002, 51, 990−995. (15) Wang, F.; Wang, X.-J.; Ma, Z.-Y.; Yan, J.-H.; Chi, Y.; Wei, C.-Y. The Research on the Estimation for the NOx Emissive Concentration of the Pulverized Coal Boiler by the Flame Image Processing Technique. Fuel 2002, 81, 2113−2120. (16) Lu, G.; Yan, Y.; Colechin, M. A Digital Imaging Based Multifunctional Flame Monitoring System. IEEE Trans. Instrum. Meas. 2004, 53, 1152−1158. (17) Zhou, H C; Lou, C.; Cheng, Q.; Jiang, Z W. Experimental Investigations on Visualization of Three-Dimensional Temperature Distributions in a Large-Scale Pulverized-Coal-Fired Boiler Furnace. Proc. Combust. Inst. 2005, 30, 1699−1706. (18) Lu, G.; Gilabert, G.; Yan, Y. Vision Based Monitoring and Characterisation of Combustion Flames. Sensors & Their Applications XII. 2005, 194−200. (19) Lou, C.; Zhou, H.-C.; Yu, P.-F.; Jiang, Z.-W. Measurements of the Flame Emissivity and Radiative Properties of Particulate Medium in Pulverized-Coal-Fired Boiler Furnaces by Image Processing of Visible Radiation. Proc. Combust. Inst. 2007, 31, 2771−2778. (20) Jha, S. K.; Fernando, S.; Flip To, S. D. Flame Temperature Analysis of Biodiesel Blends and Components. Fuel 2008, 87, 1982− 1988. (21) Lu, G.; Yan, Y.; Cornwell, S.; Whitehouse, M.; Riley, G. Impact of Co-Firing Coal and Biomass on Flame Characteristics and Stability. Fuel 2008, 87, 1133−1140.

Figure 14. Comparison between the temperature and emissivity measured by the spectrometer system and the flame image detection system in the experiments.

from the particulate medium in the flame meets the gray property; and the two-color method can be used to measure the temperature and emissivity of the particulate medium in the MSW flame. For the flame image detection system, since the Na (590 nm) and K (767 nm) emission lines deviate from the central wavelengths of red (R) and green (G) in the spectral response curves of the CCD camera, the two-color method can be used to deliver the temperature and emissivity images from the flame images. An online continuous monitoring of the flame was conducted over a period of 30 min by the two detection systems while the MSW incinerator was working steadily. Both the average temperatures and emissivity measured by the two systems agree well with each other, and the maximum relative difference of the average temperature and the emissivity is within 5% and 10%, respectively.

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AUTHOR INFORMATION

Corresponding Authors

*Phone: (+86) 010-62784538. E-mail: [email protected]. edu.cn. *Phone: (+86) 027-87545526. E-mail: [email protected]. Author Contributions

Weijie Yan: Experiments and data analysis. Huaichun Zhou: Analysis principle and explanation of results. Zhiwei Jiang: Experimental instrumentation and calibration. Chun Lou: Data analysis and explanation. Xiaoke Zhang: Organizing the experiments in the incinerator. Donglin Chen: Proposed and supported the research. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The present study has been supported by the National Natural Science Foundation of China (Nos. 51025622, 51176059, and 51021065) and partially by Key Laboratory for Power Technology of Renewable Energy Sources, Hunan Province (No. 2010KFJJ002).

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REFERENCES

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(MSW) Combustion by Spectral Analysis and Image

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