Temperature Profiling of Pulverized Coal Flames ... - Semantic Scholar

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 55, NO. 4, AUGUST 2006

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Temperature Profiling of Pulverized Coal Flames Using Multicolor Pyrometric and Digital Imaging Techniques Gang Lu, Senior Member, IEEE, and Yong Yan, Senior Member, IEEE

Abstract—This paper presents an imaging-based multicolor pyrometric system for the monitoring of temperature and its distribution in a coal-fired flame. A novel optical splitting/filtering device is designed and used to split the light of flame into three beams at three selected wavelengths as required in the multicolor principle. A high-resolution charge-coupled device camera is employed to collect the three beams of the light of flame. The three resulting images provide the basis for the determination of temperature and its distribution in the flame field. The system is evaluated on a 0.5-MWth coal-fired combustion test facility under various combustion conditions. Results obtained demonstrate that the system is capable of measuring the temperature and its distribution concurrently in the flame field. Quantitative relationships between the measured results and the main combustion process data are also discussed. Index Terms—Charge-coupled device (CCD) camera, combustion flame, image processing, multicolor pyrometry, pulverized coal, temperature distribution.

I. I NTRODUCTION

T

HE TEMPERATURE and its distribution of a pulverized coal flame in an industrial furnace provide useful information for the in-depth understanding of combustion processes including coal devolatilization, radiative heat transfer, pollutant formation process, and the cause of combustion problems such as slagging and fouling [1]–[3]. However, accurate and reliable temperature profiling of a pulverized coal flame remains a challenge. Optical radiation pyrometry has been recognized as the only practical nonintrusive method of measuring the temperature of flying particles in a flame [4]. However, common total radiation or single-wavelength pyrometers cannot provide the accurate temperature measurement of the flame because the emissivities of particles in the flame are normally unknown. A two-color pyrometric system measures the temperature by determining the radiative intensities of the object to be measured for two given wavelengths regardless of the absolute emissivity and has therefore been widely applied to the temperature measurement of flames in various situations. The availability of low-cost charge-coupled device (CCD) sensors and recent advances in digital image processing techniques have overcome the drawback of a conventional twocolor pyrometer where only the average temperature within a

Manuscript received June 15, 2005; revised March 27, 2006. This work was supported by the U.K. Engineering and Physical Sciences Research Council under Grant GR/S76953/01. The authors are with the Department of Electronics, University of Kent, Canterbury, CT2 7NT Kent, U.K. (e-mail: [email protected]; [email protected]). Digital Object Identifier 10.1109/TIM.2006.876393

small area of the flame field is detected. A number of CCDbased two-color systems have been developed in recent years for the measurement of temperature distribution of pulverized coal flames [5], [6]. In such systems, the emissivity of the flame had been assumed to be evenly distributed, i.e., exhibits graybody behavior. This assumption may be valid for flames fired from coals of the same source but may not be suitable for one with different radiative and optical properties, particularly in cases where fuel blends, biomass, and wastes are fired. This paper presents an instrumentation system for the measurement of temperature and its distribution in a coal-fired flame field based on the three-color technique. A unique beam-splitting/beamfiltering device is designed that splits and filters the light of flame into three narrow-band beams. A high-resolution CCD camera collects the three beams of the flame light and forms three images that are identical in size but are of different wavelengths. The three resulting images give three combinations of either two images. Three two-color temperature distributions of the flame are then computed simultaneously using the three image pairs. The final temperature of each point in the flame is estimated from the weighted average of the three two-color temperature values for improved accuracy and reliability. Key design aspects of the system together with the experimental results obtained on an industrial-scale combustion test facility are addressed and discussed. It should be stressed that although a number of multicolor pyrometric devices have been developed and used in various applications [4], [7], there are no multicolor instrumentation systems available for online, continuous, and two-dimensional (2-D) temperature profiling of a pulverized coal flame. II. S YSTEM D ESCRIPTION A. Measurement Principle The principle of the two-color pyrometry along with a detailed description of the temperature calculation has been reported elsewhere [4], [8]. The technique of the three-color pyrometry is an extended version of the two-color method. In the interests of convenience and clarity, a brief summary of the operating principles is given here. In this paper, the emissivity of the flame is considered to be unevenly distributed in consideration of the fuel blends being fired. By applying Planck’s radiation law, the monochromatic emissivity ελ of a nonblack body at a given wavelength λ can be expressed as

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ελ =

exp(C2 /λT ) − 1 exp(C2 /λTa ) − 1

(1)

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where Ta (K) is the apparent temperature of the nonblack body, which is defined as the temperature of a black body that emits the same radiation intensity as the nonblack body at temperature T , and C2 is the second Planck’s constant (1.4388 × 10−2 mK). For sooting particles in a flame, ελ can also be estimated by the widely used empirical equation [9] expressed as follows: ελ = 1 − exp(kl/λα )

(2)

where k(m−1 ) is the absorption coefficient, l(m) is the geometrical flame thickness along the optical axis of the imaging system (i.e., length of the optical path), and α is an empirical parameter depending upon λ. For the visible spectral range, α is considered to be a fixed value of 1.39 for a steady luminous flame [9]. Substituting (2) into (1) yields exp(C2 /λT ) − 1 kl = −λα ln 1 − . (3) exp(C2 /λTa ) − 1 The unknown product kl can be eliminated by rearranging (3) for two different wavelengths λ1 and λ2 , i.e., λα λα exp(C2 /λ1 T )−1 1 exp(C2 /λ2 T ) − 1 2 1− = 1− . exp(C2 /λ1 Ta1 )−1 exp(C2 /λ2 Ta2 )−1 (4) The unknown temperature T can be determined by solving (4), provided that the apparent temperatures Ta1 and Ta2 are known for λ1 and λ2 , respectively. In practice, the values of Ta1 and Ta2 are obtained by calibrating the system using a standard temperature source (Section II-D). Because the third optical path at wavelength λ3 is available in the three-color system, three two-color temperatures can be calculated using (4) for the three image pairs, i.e., λ1 /λ2 , λ1 /λ3 , and λ2 /λ3 . The true temperature of the flame can then be determined by the weighted average of the three two-color temperatures, i.e., T =

3

Wi T i

(5)

i=1

where 3

Wi = 1

(6)

i=1

where Ti is the two-color temperature for the ith wavelength pair, and Wi is the weighting factor for Ti . A larger weighting factor is assigned to the temperature of smaller variance, whereas a smaller weighting factor is assigned to the temperature of larger variance. It should be stressed that a multicolor pyrometric system measures the temperature of small substances in a flame because Planck’s radiation law only fits the continuous spectra of the solid particles rather than the band spectra of gas molecules [10]. During pulverized coal combustion, both solid particles and gaseous combustion products are present. There exists a temperature difference between a particle and its surrounding gas. This difference depends upon the rate at which heat is

Fig. 1.

Block diagram of the system.

transferred by radiation from the particle to the gas and by convection between the gas and the particle. In view of the fact that the diameters of the distinct soot particles range from 0.025 to 0.06 µm [1], the temperature difference between the soot particles and their surrounding gas is expected to be less than 10 ◦ C [8]. On the other hand, although coal particles can be as large as over a hundred micrometers, they are surrounded by a soot cloud that is generated from the volatile matter decomposed from the particles at high temperature, particularly at the early stage of the combustion [11]. Therefore, the temperature obtained using the proposed method is more likely the soot temperature rather than that of the coal particles. It should also be noticed that, in this paper, the temperature measurement is made along horizontal optical paths perpendicular to the burner axis. Due to the fact that the temperature may not be constant along the optical path, the measured temperatures represent line-of-sight averages weighted by the particle concentration across the thickness of the flame. It has been proven that the line-of-sight temperatures were reasonably representative of those in the particle-laden regions of the flame, particularly the root region. Furthermore, along the optical path, hotter particles weighed more than cooler particles, and therefore the calculated temperature would be close to that of hotter particles along the optical path [12]. B. Implementation of the System Fig. 1 shows the block diagram of the system design. The system consists of a CCD camera, a beam-splitting/beamfiltering device, a frame grabber, and a microcomputer with application software, whereas Fig. 2 illustrates the arrangement of the light-transmitting, light-splitting, and light-filtering elements. The beam-splitting/beam-filtering device receives the light of the flame through an optical probe and split the light into three identical beams for three different wavelengths. The high-resolution monochromatic camera (2/3-in CCD, 1300 H × 1030 V, progressive scanning system) collects the three beams of the light of flame and forms three images that are identical in size but responsible for different wavelengths. The frame grabber, which incorporates with the microcomputer, transfers the image signal into 2-D digital images with an eight-bit digitization. The entire imaging system provides a frame rate of 24 frames/s. Application software, as an integral part of the system, processes the digital images and then derives the flame temperature on an online and continuous basis. C. Choice of Wavelengths The choice of the wavelengths is one of the crucial factors in the design of the multicolor system, and there are a number of considerations that must be taken into account. First, visible and infrared wavelengths can be used in a two-color system, but visible wavelengths are preferred because the rate of change of the spectral radiance with respect to temperature is greater in

LU AND YAN: TEMPERATURE PROFILING USING MULTICOLOR PYROMETRIC AND DIGITAL IMAGING TECHNIQUES

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Fig. 2. Arrangement of the light-transmitting, light-splitting, and lightfiltering elements.

Fig. 4. Calibration curves (shutter speed: 1/400 s; iris: 5.6).

Fig. 3.

True and apparent temperatures of the tungsten lamp.

the visible spectral range than in the infrared spectral range, resulting in a higher sensitivity and signal-to-noise ratio of the image signal. In addition, α in (4) is fairly independent of the wavelength and most types of fuel in the visible spectral range [8], [9], and therefore, the calculation can be simplified. Second, the wavelengths must be far from the absorption bands of gas molecules and free radicals in the reaction zone of the flame such as OH, CH, C2 , HCO, and NH, which may be formed and give appreciable emission in the visible and near-ultraviolet regions [8]. Third, the bandwidths of the filters should be as narrow as possible to acquire a single-wavelength radiation and, meanwhile, allow enough light passing through. Finally, the pair of the selected wavelengths should be separated to achieve a higher signal-to-noise ratio of two image signals. However, a farther-apart wavelength pair can cause overexposure of the imaging sensor at one wavelength and underexposure at the other. Compromising the factors addressed previously has given rise to the selection of the three wavelengths at 550, 632, and 700 nm with a bandwidth of 40 nm. It should be noted that the use of wavelengths in the visible region also minimizes the disturbance of the radiation from the refractory wall of the furnace. D. Calibration and Accuracy The system was calibrated to determine the apparent temperatures Ta1 , Ta2 , and Ta3 at the chosen wavelengths λ1 , λ2 , and λ3 to establish the relationships between the apparent temperatures and the corresponding gray levels of the images. A gas-filled tungsten lamp was used as a standard light source for the calibration. Calibration using a tungsten lamp has been

Fig. 5. Comparison between the measured and reference temperatures.

proven to be practical, reliable, and reasonably accurate. The lamp was precalibrated at a wavelength of 662.4 nm with regard to the apparent temperature ranging between 700 and 1500 ◦ C [13]. It is understood that these precalibrated data have to be corrected against the selected three wavelengths, i.e., determining the apparent temperatures of the tungsten lamp for 550, 632, and 700 nm wavelengths, respectively, prior to calibration of the imaging system. This can be done by, first, determining the true temperature of the tungsten lamp. In view of the fact that in (1), exp(C2 /λT ) 1 throughout the visible region for the temperatures up to approximately 3500 K [10], (1) can be written by applying Wien’s radiation law, i.e., C2 C2 − ελ = exp . (7) λT λTa Rearranging (7) gives 1 λ 1 = + ln(ελ ). T Ta C2

(8)

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Fig. 6. Typical temperature distribution of the flame for different volumes of excess air; (a) 10.6% and (b) 32.10%.

This means that the true temperature of the tungsten lamp can be obtained if the emissivity ελ is known. The emissivity of tungsten is a function of the wavelength and the true temperature and can be computed based on the experiential equations proposed by Larrabee [14], which are given as follows: ελ = 0.4655 + 0.01558λ + 0.2675 × 10−4 T − 0.7305 × 10−4 λT,

where λ = 450−680 nm (9)

and ελ = 0.6552 − 0.26333λ − 0.7333 × 10−4 T + 0.7417 × 10−4 λT,

where λ = 680−800 nm.

(10)

As can be seen, there are two variables, i.e., T and λ, in (9) and (10). An iterative process has to be taken to obtain the true temperature and the emissivity, i.e., emissivity ελ is first computed using the apparent temperature Ta at the 662.4-nm wavelength provided by the calibration certificate of the tungsten lamp based on (9). An intermediate value of the true temperature is then computed using ελ obtained from the first step based on (8). With the intermediate value of the true temperature, a new value for ελ is calculated using (9). The preceding procedures are repeated until the difference between the two consecutive values of the true temperature is insignificant. The true temperature of the tungsten lamp can be determined for each setting of the apparent temperature, which is controlled by the current provided by a high-stability and high-capacity dc power supply. Fig. 3 shows the curves of the apparent temperature and the computed true temperature of the tungsten lamp versus the current. Once the true temperature of tungsten has been determined, the apparent temperatures can be computed against the selected three spectral wavelengths using (8) and (9) (for 550 and 632 nm) or (8) and (10) (for 700 nm). The procedure of the calibration was, first, to reproduce the geometrical relationship between the imaging system and the flame to be measured. Three banded images of the filament were captured, and the gray levels of the images were averaged. The relationships between the apparent temperatures of the tungsten filament and the gray levels of the images were then identified for the given spectral wavelengths, respectively. It was found that the calibration results were sensitive to the settings of the imaging system, particularly the camera shutter speed and iris. The calibration was therefore conducted for different camera settings. Fig. 4

Fig. 7.

Variations of flame temperature with excess air.

shows the calibration curves for the camera shutter speed of 1/400 s and the iris of 5.6. It can be seen that the relationships between the apparent temperatures of the tungsten filament and the gray levels of the images appear to be nonlinear. It is impossible to produce regression equations without losing the accuracy of the measurement. In practice, therefore, the calibration data are stored in the form of lookup tables, through which a unique relationship between every possible gray level in banded images and the corresponding apparent temperature is defined for a given wavelength. The accuracy of the measurement was verified by applying the system to measure the reference temperature generated by the tungsten lamp over the temperature range between 1280 and 1690 ◦ C. The results, as shown in Fig. 5, are the average temperatures of 20 measurements for each temperature setting. The relative errors are not greater than 1% for all the three pairs. III. R ESULTS AND D ISCUSSIONS To evaluate the performance of the system in an industrial environment, a series of tests was conducted on a 0.5-MWth coal-fired combustion test facility. The detailed descriptions on the test facility and the system installation have been given elsewhere [5], [6]. In the tests, a typical pulverized coal was fired under various operating conditions including variations in excess air and mass flow rate of coal. Two different-sized coals (i.e., finely and coarsely ground coal from the same source)

LU AND YAN: TEMPERATURE PROFILING USING MULTICOLOR PYROMETRIC AND DIGITAL IMAGING TECHNIQUES

Fig. 8.

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Typical temperature distribution of the flame for two different mass flow rates of coal. (a) 39 kg · h−1 and (b) 64 kg · h−1 .

were also tested to reveal the impact of coal particle size on the thermal characteristics of the flame. Fig. 6 illustrates the typical temperature distribution in the flame field for the excess air of 10.6% and 32.0%. The excess air indicates the volume of air exceeding the stoichiometric airflow required by the coal fed into the furnace, which is considered to be an important factor influencing the temperature in the flame field. As can be seen, there exists a hightemperature region (where T > 1540 ◦ C) in the flame, the size and the location of which vary significantly with the volume of excess air. The flame with a higher volume of excess air has a greater high-temperature region, indicating more intensive thermal reaction taking place. Fig. 7 shows the variations of the maximum, mean, and minimum temperatures with excess air. The value at each data point in the figure is the average of 25 continuous readings. Standard deviations of the data are also given as “error” bars. A slight increasing trend can be observed in both maximum and mean temperatures when the volume of excess air increased. The minimum value reflects more or less the refractory wall temperature and remains relatively stable at approximately 1420 ◦ C. Fig. 8 depicts the temperature distribution of the flame for two different mass flow rates of coal. It is clear that the sizes and locations of the high-temperature regions (where T > 1558 ◦ C) in the flame are affected by the mass flow rate of coal. For instance, at 64 kg · h−1 (i.e., the full-furnace load), the two high-temperature regions are much greater and distinguished in comparison with that at 39 kg · h−1 , resulting in a hotter flame. Fig. 9 shows the variations of the maximum, mean, and minimum temperatures with the mass flow rate of coal. As expected, the maximum and mean temperatures increase with the mass flow rate of coal. The difference between the maximum and mean temperatures can be as high as 120 ◦ C. A significant fluctuation in the mean temperature occurs under the coal flow rate of 39 kg · h−1 , suggesting an unstable flame under such a condition. The minimum temperature remains stable and much similar to that of the flame under different volumes of excess air. Fig. 10 shows the temperature distributions of the flames for the fine and coarse coals. It has been found that the coarse coal produces two distinct high-temperature regions (where T > 1558 ◦ C), resulting in a higher temperature overall the flame. This can also be observed in Fig. 11, which illustrates the variations of the maximum, mean, and minimum temperatures. The maximum temperature of the coarse coal flame is as high

Fig. 9. Variation of flame temperature with mass flow rate of coal.

as 1700 ◦ C, whereas that of the fine coal flame is approximately 1660 ◦ C. Although the difference is not significant, it may be attributed by the fact that the measured temperature is the weighted average of the surface temperatures of the particles. It is known that larger particles burn at a higher temperature than the smaller ones because of a lower heat loss rate during combustion [15]. An increase in the number of larger particles would therefore result in a higher weighted temperature. In other words, the coarse coal produces a higher temperature and consequently may lead to more serious fouling and slagging problems. IV. C ONCLUSION An instrumentation system for the monitoring of temperature and its distribution in a coal-fired flame has been developed based on the three-color pyrometric and digital imaging techniques. A high-resolution CCD camera, together with a sophisticated beam-splitting/beam-filtering device, enables receiving the light of flame and produces three images for three distinct wavelengths. The three resulting images provide the basis of the determination of three two-color temperatures. The true temperature of the flame is estimated by the three weighted two-color temperatures, hence, the accuracy and reliability of the measurement have been improved. Experimental results obtained on a 0.5-MWth combustion test facility have

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Fig. 10. Typical temperature distribution of the flame for different sized coal particles. (a) Fine coal. (b) Coarse coal. [10] D. P. Dewitt and G. D. Nutter, Theory and Practice of Radiation Thermometry. New York: Wiley, 1989. [11] W. L. Grosshandler, “The effect of soot on pyrometric measurements of coal particle temperature,” Combustion and Flame, vol. 55, no. 1, pp. 59–71, Jan. 1984. [12] K. L. Cashdollar, “Three-wavelength pyrometer for measuring flame temperature,” Appl. Opt., vol. 18, no. 15, pp. 1595–1597, 1979. [13] National Physical Laboratory, Certiﬁcate of Calibration (TungstenRibbon Lamp Vacuum No. P251C), 1999, PM06/LN98/026. [14] R. D. Larrabee, “Spectral emissivity of tungsten,” J. Opt. Soc. Amer., vol. 49, no. 6, pp. 619–625, 1959. [15] P. M. Willson and T. E. Chappell, “Pulverized fuel flame monitoring in utility boilers,” Meas. Control, vol. 18, no. 2, pp. 66–72, 1985.

Fig. 11. Variations of flame temperature with coal particle size.

demonstrated that the system is capable of measuring the temperature and its distribution in coal-fired flames under a real industrial environment and therefore providing very useful information on the thermal- and fluid-dynamic characteristics of the flame under various operating conditions. R EFERENCES [1] T. H. Fletcher, J. Ma, J. R. Rigby, A. L. Brown, and B. W. Webb, “Soot in coal combustion systems,” Progress Energy Combustion Sci., vol. 23, no. 3, pp. 283–301, 1997. [2] D. W. Shaw and R. H. Essenhigh, “Temperature fluctuations in pulverized coal (P.C.) flames,” Combustion Flame, vol. 86, no. 4, pp. 333–346, Sep. 1991. [3] T. Merklein, “Optimal firing management with varying fuels by means of combustion diagnoses,” VGB PowerTech, vol. 78, no. 8, pp. 55–59, 1998. [4] Y. A. Levendis, K. R. Estrada, and H. C. Hottel, “Development of multicolor pyrometers to monitor the transient response of burning carbonaceous particles,” Rev. Sci. Instruments, vol. 63, no. 7, pp. 3608–3622, Jul. 1992. [5] Y. Huang and Y. Yan, “Transient two-dimensional temperature measurement of open flames by dual spectral image analysis,” Trans. Inst. Meas. Control, vol. 22, no. 5, pp. 371–384, 2000. [6] G. Lu, Y. Yan, G. Riley, and H. C. Bheemul, “Concurrent measurements of temperature and soot concentration of pulverized coal flames,” IEEE Trans. Inst. Meas., vol. 51, no. 5, pp. 990–995, Oct. 2002. [7] T. Panagiotou, Y. A. Levendis, and M. Delichatsios, “Measurements of particles flame temperatures using three-color optical pyrometry,” Combustion Flame, vol. 104, no. 3, pp. 272–287, Feb. 1996. [8] H. Zhao and N. Ladommato, “Optical diagnostics for soot and temperature measurement in diesel engines,” Progress Energy Combustion Sci., vol. 24, no. 3, pp. 24221–24255, 1998. [9] H. C. Hottel and F. P. Broughton, “Determination of true temperature and total radiation from luminous flame,” Industrial and Engineering Chemistry (Analytical Edition), vol. 4, no. 2, pp. 166–175, Apr. 1932.

Gang Lu (SM’05) received the B.Eng. degree in mechanical engineering from Central South University, Changsha, China, in 1982 and the Ph.D. degree in advanced combustion instrumentation from the University of Greenwich, Greenwich, U.K., in 2000. He started his career as a Research Engineer and worked on mechanical design and engineering development for iron- and steel-making industry in China for more than ten years. He worked as a Postdoctoral Research Fellow in both the University of Greenwich and the University of Kent, Canterbury, Kent, U.K. from 2000 to 2006. He is currently a Lecturer in electronics and instrumentation with the Department of Electronics, University of Kent. His main area of research is combustion instrumentation. He has been involved in a range of projects on advanced monitoring and characterization of fossil fuel flames. Dr. Lu is a Chartered Engineer and a member of the Energy Institute (U.K.).

Yong Yan (M’04–SM’04) received the B.Eng. and M.Sc. degrees in instrumentation and control engineering from Tsinghua University, Beijing, China, in 1985 and 1988, respectively, and the Ph.D. degree in solids flow instrumentation from the University of Teesside, Middlesbrough, U.K., in 1992. He started his academic career in 1988 as an Assistant Lecturer at Tsinghua University. He entered the U.K. as a Research Assistant in 1989. After a short period of postdoctoral research, he worked initially as a Lecturer with the University of Teesside from 1993 to 1996 and then as a Senior Lecturer, Reader, and Professor, respectively, with the University of Greenwich from 1996 to 2004. He is currently a Professor of electronic instrumentation and the Head of the Embedded Systems and Instrumentation Research Group at the University of Kent, Canterbury, Kent, U.K. He has published more than 170 research papers and has supervised ten Ph.D. research students to successful completion. Dr. Yan is a Fellow of the Institute of Physics (U.K.) and the Institute of Measurement and Control (U.K.) and a member of four U.K. national technical committees and expert panels. He was awarded the Achievement Medal by the Institution of Electrical Engineers in 2003.