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Measurement performance of an optical CCD-based pyrometer system
ARTICLE IN PRESS Optics & Laser Technology 42 (2010) 586–593
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Measurement performance of an optical CCD-based pyrometer system Tairan Fu a,n, Zangjian Yang b, Luping Wang b, Xiaofang Cheng b, Maohua Zhong c, Congling Shi c a b c
Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, PR China Department of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei 230026, PR China China Academy of Safety Science and Technology, Beijing 100029, PR China
a r t i c l e in f o
a b s t r a c t
Article history: Received 13 June 2009 Received in revised form 20 August 2009 Accepted 27 October 2009 Available online 20 November 2009
The measurement performance of a CCD-based pyrometer system using a three-color method was evaluated for scientific and engineering metrology. The relationships between the system parameters (exposure time and sensor gain) and the intensity measurements in an integrating sphere experiment were determined for a specific CCD sensor. The pyrometer system uses the three-color method based on the intensity ratio without geometry calibrations. The field measurement characteristics and the effectiveness of coupling the three-color channels were investigated in terms of the temperature measurement uniformity, temperature sensitivity and temperature range of the pyrometer system in standard blackbody tests. The results showed that the temperature non-uniformity is not proportional to the intensity non-uniformity and is in the range of 0.13–2.14%. The relative temperature sensitivities of intensity ratios for different channel combinations are different, which may provide a way to improve the measurement results. The temperature range bandwidth for object with a non-uniform temperature distribution varies from 190 to 270 K for this specific CCD-based pyrometer. The performance evaluation conclusions for the system with this specific CCD sensor are general and applicable for pyrometer systems using other CCD sensors. & 2009 Elsevier Ltd. All rights reserved.
Keywords: Pyrometer Optical diagnostics Temperature
1. Introduction Optical radiation pyrometry, the determination of the temperature of an object based on its luminosity caused by thermal self-radiation, is an effective and practical method for measuring combustion temperatures or surface temperatures. In recent years, optical pyrometers have been built with a charge coupled device (CCD) for temperature distribution measurements through optical visualization [1–8]. A CCD is a light-sensitive integrated circuit that stores and displays the data for an image in such a way that each pixel in the image is converted into an electrical charge. CCDs are used in the astronomical telescopes, scanners, machine vision system, optical character recognition and meteorology. The availability of CCD sensors conveniently provides temperature field measurements which overcomes the shortcoming of traditional spot pyrometers only detecting several points. Existing CCD-based pyrometer systems based on the multicolor method use various means to separate the measurement wavelengths/wavebands with single CCD or multiple CCDs. The former is more advantageous due to the simple system design. In a single CCD system, images for different colors may be sequentially formed on the same monochrome sensor array
n
Corresponding author. E-mail address: [email protected] (T. Fu).
0030-3992/$ - see front matter & 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.optlastec.2009.10.008
through a beam splitting/filtering assembly with narrow-band interference filters [2–4] or they can be simultaneously obtained from a color sensor array with a mosaic pixel filter (for example, an R-G-B Bayer filter) [6–8]. The method using narrow-band interference filters corresponds to multi-color pyrometry with wavelength measurements, while that using an R-G-B Bayer mosaic pixel filter is looked upon as multi-color pyrometry with waveband measurements. If R-G-B waveband measurements are simplified as three effective wavelengths measurements, it will cause great error even though the conversion relationship is calibrated with blackbody experiments. Previous research on CCD-based pyrometer systems has mainly focused on two approaches to calculate the temperatures. One approach is to beforehand calibrate the system to determine the relationship between the radiation intensity and the corresponding sensor output using the same geometric parameters for the system and the measured object [4]. This relationship is only suitable for the measurements at the same geometric condition. Once the condition is changed, the calibration process needs to be undertaken again. The other approach is to utilize the radiation intensity ratio of different wavelengths/wavebands as a relative intensity. The geometric factor,F (Eq. (1)), is eliminated through the ratio processing (Eq. (10)) and it avoids the calibrations for the geometry condition [6,7]. The measurement uncertainties of these two approaches were theoretically evaluated by Fu et al. [9]. The correlation theory and other aspects of CCD-based pyrometry applications have been analyzed in many references [10–19].
ARTICLE IN PRESS T. Fu et al. / Optics & Laser Technology 42 (2010) 586–593
Although optical pyrometers based on color CCDs have been applied in research studies of high-temperature measurement with promising results, there are few commercially available CCD-based multi-color pyrometers for temperature field measurements in engineering applications. Some technology issues are still worth further studying. The measurement ability of the CCD-based pyrometers using the multi-color method has not received sufficient attention or been scientifically analyzed in the literature. In applications of CCD sensor as a scientific temperature metrology device, it is necessary to evaluate the system measurement performance, including the measurement uncertainty [20,21], system parameters, measurement range and measurement sensitivity. The image processing and CCD-sensor characteristics are generally related to the system parameters (exposure time, sensor gain, etc.), but the quantitative relationships between these parameters and the intensity/temperature measurements are not clear. This analysis is based on a threecolor pyrometer system using a color CCD to evaluate the system performance for scientific and engineering metrology as a function of the system parameters, measurement uniformity, measurement sensitivity and measurement range. The coupling characteristics of the three-color channels in the pyrometer system, based on the intensity ratios, cause the analysis of the measurement performance to be much different from analyses of traditional and commercial single/dual-channel pyrometer systems, arising from the intensity ratio analyses of more channels. In addition, performance analyses of field measurements with CCD-based pyrometers also differ from analyses of other systems measuring only several points. The analysis presented in this paper provides a valuable description of the performance of CCDbased pyrometers using the multi-color method to make such systems more practical for scientific and engineering applications.
The system applies gains and then does an A/D conversion to get the digital output signals. The pixel values of the recorded CCD frame image are the outputs of the array of micro-sensors. The instrument sensor parameters, including the image LUT (lookup-table), aperture, shutter, global gain and R/G/B gain, are the important adjustable quantities in the CCD-based pyrometer system. These parameters control the intensity measurements of the micro-sensors which affect the temperature measurements. The equation relating the spectral irradiation to the pixel output of the frame image is: ! Z Dt le ð1Þ si ðlÞUI ðlÞ dl þ ni ; i ¼ R; G; B Ci ¼ Zki FU 2 F ls Where Ci is the pixel digital value with non-dimension in channel i, obtained by A/D conversion. For a 8 bit output, this value range is from 0 to 255. I(l) is the spectral distribution of the irradiance reaching the CCD sensor per unit time at wavelength l, W m 2 sr 1 mm 1; si(l) is the spectral sensitivity for the combinations of lens/image-optics/color-filter/sensor in channel i; F is a geometric factor that is a function of the radiation attenuation, observation distance, observation angle and lens properties; Dt is the exposure time, s; F is f-number of the aperture; ni is the dark noise in channel i and may be estimated by capturing frame images with the lens cap on the pyrometer; (ls,le) are the system wavelength range, nm; Z is the zooming coefficient relative with the global gain; and ki is the zooming coefficient relative to the R/G/B channel gain. In Eq. (1), different channels (i= R, G, B) correspond to different micro-sensors with different spectral response distributions in the CCD-based system. Therefore, the image pixel values (CR, CG, CB) may be looked upon as three channels of system outputs. Rl Defining Ei ¼ F=F 2 ð lse si ðlÞIðlÞdlÞ: Ci ¼ Zki ðDt Ei þ ni Þ;
2. Calibration of CCD-based pyrometer system The design of a CCD-based pyrometer system is shown in Fig. 1. The color CCD is the key part of the optical pyrometer system, with its characteristics determining the measurement performance of the optical pyrometer system. The system data processing procedure is shown in Fig. 2. The light rays are focused on the CCD focal plane and then translated into electronic signals.
587
i ¼ R; G; B
When Z = 1 and ki = 1, Ci,0 = Dt Ei + ni. This research used a pyrometer system based on the IMC 147FT CCD camera with the ICX285AL chip (progressive scanning, 1,450,000 pixels 1392(H) 1036(V), cell size 6.45 6.45 mm, 12 bit data depth, S/N ratio 456 dB, 20 FPS at maximum resolution), for the following analysis. The spectral sensitivity curves si(l) of IMC 147FT CCD camera may be determined by spectrum experiments [7]. Here only a brief description of the measurement
Hardware construction
Software analysis
High-temperature objects Color Optical
Data processing
CCD sensor
lens
Temperarture result Fig. 1. Design of a CCD-based pyrometer system.
Optical lens Aperture parameter
Color CCD sensor Exposure time
ð2Þ
Global gain
R/G/B gain
Input irradiation
A/D conversion
Output data Fig. 2. System data processing.
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1 Relative spectral sensitivity
0.9
Channel R Channel G Channel B
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
370 400 430 460 490 520 550 580 610 640 670 700 730 760 790 Wavelength (nm) Fig. 3. Relative spectral sensitivity curves.
18 Level 8
Spectral radiation intensity (µw/(cm2 × Sr × nm))
16
14 Level 6
12
10
optical axis to be perpendicular to the exit plane and the uniform exit radiation filling the entire field of view. Eliminate the interference from background light sources and keep the environment dark. Maintain steady working conditions by pre-heating the integrating sphere for half an hour.
Level 4
8
2.2. LUT setting
6 Level 2
4
Level 1
2 0 300
400
500
600
700
800
900
1000
1100
Wavelength (nm) Fig. 4. Spectral radiation intensity distribution.
progress was introduced. The spectral sensitivity curves were measured by presenting the monochromatic light stimuli, obtained with a monochromator and a 250 W bromine tungsten lamp, to the camera at every spaced wavelength (5 nm interval) in the spectrum range 370–810 nm. Simultaneously, the monochromatic radiation intensities at different wavelengths were recorded with a Si-photodiode. Then, the relative spectral sensitivity curves of the camera were obtained, shown in Fig. 3. The results show that when l 4730 nm, the spectral sensitivity is zero. Therefore, (ls, le) are set to (370, 730 nm). 2.1. Experimental conditions To verify the influences of the system parameters on the radiation intensity measurement, an IS2500-1000 integrating sphere was used as the standard calibration source to provide steady, uniform reference irradiation. The sphere diameter was 2500 mm and the opening diameter was 1000 mm. The sphere contained sixty four 250 W bromine tungsten lamps which were symmetrically distributed in the sphere, classified in 8 levels (leve1 8: 64 lamps open; level 4: 32 lamps open; level 1: 8 lamps open). The filament length of each lamp was 5 mm. The spectrum range of the radiation output was 250–2500 nm, shown in Fig. 4. The stability of the source was up to 99.2% with an opening irradiation uniformity of 99.81%. The experimental condition was based on the following:
Fix the position of the CCD system at a distance of 1.1 m to the sphere exit plane and adjust the iris aperture. Fix the system
The 12 bit CCD output data was first converted into 8 bit data based on the LUT. LUT= 0 means that bits 1–8 were used from the 12 bit data as the output data, LUT= 1 means that bits 2–9 were used, and so on. Therefore, the output Ci was calibrated based on the LUT setting with the actual calibrated maximum being up to 4095 (LUT=4). The LUT setting enables the pyrometer system to work with different light intensities. 2.3. Exposure time The adjustment of exposure time prevents the image data to be saturated or dark, and also makes the measurements suitable for high dynamic frequency conditions using a shorter exposure time. The electrical shutter, accurately controlled by the software, theoretically determines the exposure time in Eq. (1). However, the exposure linearity of the intensity response described in the Eq. (1) still needs to be verified for actual measurements. Frame images at different exposure times were captured for a global gain and R/G/B gains of 0. Fig. 5 illustrates the relationship between Ci and the exposure time which shows that Ci is proportional to the exposure time when Ci is less than the critical value. The critical value CB (about 2950) of channel B is slightly lower than the critical values (about 3100) of other channels, R and G, which results from the differences of photo-electricity conversion capacity of different channels of CCD sensor. In the very short exposure time range, this linearity relationship is still satisfied for applications. Therefore, the linear exposure response described in Eq. (1) is correct for reasonable Ci, but Ci can reach a maximum critical value when the response is no longer linear. This nonlinearity arises from the CCD physical characteristics and does not fit for actual measurements. Therefore, the LUT setting should be less than 4 to avoid this non-linearity. 2.4. Sensor gain The global gain and R/G/B gains varied from 0 to 511. For gains of 0, Z =1 and ki =1 in Eq. (1). The relationship between these
ARTICLE IN PRESS T. Fu et al. / Optics & Laser Technology 42 (2010) 586–593
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2500 3500
2250
i=R
3000
2000
i=G
2500
1750
i =B
1500
Ci
1500
Ci
i=R i=G i=B
2000
1250 1000
1000
750
500
500 250
0 0
0
1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Exposure Time (µs)
50
100 150 200 250 300 350 400 450 500 GainR
Fig. 7. Pixel values for various R gains for a global gain of 0.
1600 1400
i=R i=G i=B
1200 1000
2500 2250
i=R
800
2000
i=G
600
1750
i=B
400
1500
200
1250
Ci
Ci
0
1000
0 100 200 300 400 500 600 700 800 900 1000 1100 Exposure Time (µs)
750
Fig. 5. (a) Pixel values for various exposure times, (b) Local magnification of (a).
250
0
500 0
2500
0
2250
50
100
150
200
i=R
2000
i=G
1750
250
300
350
400
450
500
GainG Fig. 8. Pixel values for various G gains for a global gain of 0.
i=B
Ci
1500
The fitting results are given by:
1250
GcoefR ¼ 0:001782;
1000 750 500 250 0 0
50
100
150
200
250
300
350
400
450
500
GGain Fig. 6. Pixel values for various global gains with the R/G/B gains set to 0.
values and the actual zooming coefficients, Z and ki, is unknown. The gain can be adjusted to broaden the effective dynamic range of the measurement channels. For example, if the signal in channel R is too weak to be analyzed, the data quality can be improved by setting a higher R gain. Frame images were grabbed at various global gains for R/G/B gains of 0 (ki = 1). The relationship between Ci and the global value (represented by GGain) shown in Fig. 6 can be fit by: C log i ¼ Gcoefi GGain; Ci;0
i ¼ R; G; B
ð3Þ
where Gcoefi is the fitting coefficient for the channel i. When ki = 1, the zooming value, Z, can be expressed as: Gcoefi GGain
Z ¼ 10
ð4Þ
GcoefG ¼ 0:001781;
GcoefB ¼ 0:001778
ð5Þ
The results show that the influence of the global gain on the intensity responses of the three channels is almost same, GcoefR EGcoefG EGcoefB. Through adjusting the global gain value, the maximum zooming rates Zmax for three channels are about 8.19 (R channel), 8.18 (G channel) and 8.14 (B channel). It means that for 8 bit output data 0–255 of three channels may be respectively broadened to 0–2088 (R channel), 0–2086 (G channel) and 0–2076 (B channel). Frame images for various R/G/B gains values were captured for a global gain of 0(Z = 1). The relationships between Ci and the R/G/ B gains (represented by GainR, GainG, GainB) shown in Figs. 7–9 can be fit by: log
Ci ¼ coefi Gaini ; Ci;0
i ¼ R; G; B
ð6Þ
Where coefi is the fitting coefficient for channel i. When Z = 1, the zooming value, ki, is expressed as,
ki ¼ 10coefi Gaini
ð7Þ
The fitting results are: CoefR ¼ 0:001791;
CoefG ¼ 0:001791;
CoefB ¼ 0:001786
ð8Þ
The results show that the influences of the R/G/B gains on the intensity responses are also same, CoefR ECoefG ECoefB. The change of the R gain does not affect other two channels of G and B,
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2500
3.0
i=R
2000
i=G
1750
i=B
1500 Ci
2.5
Non-uniformity distribution, %
2250
1250 1000 750 500 250
2.0 1.5 1.0
i=R i=G
0.5
i=B 0.0
0 0
50
100
150
200
250 300 GainB
350
400
450
0
500
50
100
150
200
250
300
350
400
450
500
GGain
Fig. 9. Pixel values for various B gains for a global gain of 0.
Fig. 10. Non-uniformity distribution.
which is same for the G gain and the B gain. Through adjusting the R/G/B gains values, the maximum zooming rates of three channels are about kR,max E kG,max E kB,max E8.25. It means that for 8 bit output data 0–255 may be broadened to 0–2104.
geometry calibrations. First, normalize the measured signals (CR, CG, CB). as (u, v),
2.5. Uniformity analysis
where Ib (l,T) is the spectral radiance intensity of an ideal blackbody at the same temperature T and e(l,T) is the spectral emissivity. From Eq. (10), we know that the geometric factor F of Eq. (1) is eliminated and it effectively avoids the calibrations for the geometry quantity F in temperature calculations. The pyrometer performance is based on the typical standard blackbody, e(l,T) E1.0, so the normalized data for a blackbody measurement (mb,vb) is:
u¼
R kR U llse sR ðlÞUeðl; TÞUIb ðl; TÞdl CR ¼ ; R CG kG U llse sG ðlÞUeðl; TÞUIb ðl; TÞdl
v¼
R kR U llse sR ðlÞUeðl; TÞUIb ðl; TÞdl CR ¼ R CB kB U llse sB ðlÞUeðl; TÞUIb ðl; TÞdl
ð10Þ
The uniformity of the frame image data depends upon the uniformity of the standard source and the system itself which experiences random noise in the CCD sensor and inherent differences in the micro-sensors. The integrating sphere is very uniform (99.81%) and stable (99.2%), thus, the non-uniformity of the recorded two-dimensional data can be used to evaluate the non-uniformity of the pyrometer system itself. The non-uniformity can be quantified by: "
N;M X 1 ðCi ðp; qÞ Ci ðp; qÞÞ2 Ci ðp; qÞ N M p;q ¼ 1
1
whereCi ðp; qÞ ¼
1 NM
N;M P
Ci ðp; qÞ;
ub ¼
#0:5
R kR llse sR ðlÞUIb ðl; TÞdl CR;b ¼ ; R CG;b kG llse sG ðlÞUIb ðl; TÞdl
vb ¼
R kR llse sR ðlÞUIb ðl; TÞdl CR;b ¼ R CB;b kB llse sB ðlÞUIb ðl; TÞdl
ð11Þ ð9Þ
When the spectral sensitivities (sR(l), sG(l), sB(l)) are fixed, (ub,vb) uniquely depend on the temperature T. Therefore, averaging of the pixel values for a blackbody image gives:
N M is the effective number
i;j ¼ 1
of pixels in the frame image and (p, q) are the coordinates of each pixel in the image. Fig. 10 shows the uniformity distribution of the pixel values as a function of GGain which is acceptable for these measurements. The non-uniformities for the R and G channels are less than 1.5%, but the non-uniformity of the B channel is about 2.5%. The difference is mainly due to smaller values for the B channel compared with the other channels. Higher pixel values make the influence of the random noise insignificant, so the uniformity distribution is improved.
ub ¼
N;M X 1 u ðp; qÞ; N M p;q ¼ 1 b
vb ¼
N;M X 1 v ðp; qÞ N M p;q ¼ 1 b
ð12Þ
3. Temperature measurement performance of CCD-based pyrometer system
Where N M is the effective number of pixels in the frame image. The relationship between ðub ; vb Þ and T can be determined through measurements with a blackbody with the results stored in a database. This relationship is not a function of the geometry quantity F. In actual applications, the measured normalized data (umeas, vmeas) are often affected by measurement uncertainties so they deviate from the fitting relationship between ðub ; vb Þ and T. Thus, the temperature is calculated iteratively by minimizing the following equation in a selected temperature range: @T 2 @T 2 þ ðvmeas: vb Þ ) min ð13Þ ðumeas: ub Þ @ub @vb
3.1. Measurement method
3.2. Temperature uniformity
In the CCD-based pyrometer system, the images are recorded simultaneously from the three R-G-B micro-sensors with spectral sensitivities (sR(l), sG(l), sB(l)). These may be analyzed as three waveband measurements. The measurements are combined with emissivity models to calculate the temperatures using threecolor pyrometry method based on the intensity ratios without
A Mikron M330 blackbody was used as the calibration reference to illustrate the pyrometer performance. The blackbody can produce any temperature between 300 and 1700 1C. The blackbody consists of a closed end tube with a 25 mm diameter aperture with the tube heated by specially manufactured elements which provide excellent uniformity and a heat-up time
ARTICLE IN PRESS T. Fu et al. / Optics & Laser Technology 42 (2010) 586–593
" #0:5 N;M X 2 1 1 Tðp; qÞ Tðp; qÞ Tðp; qÞ N M p;q ¼ 1
ð14Þ
1.5
Temperature Error, %
1.0 0.5 0.0 1083 -0.5
1183
1283
1383
1483
1583
1683
1783
1683
1783
-1.0 -1.5 -2.0 Temperature (K) Fig. 13. Relative temperature error.
2.5 Temperature Non-uniformity, %
of 80 min to reach 1600 1C. A self-tuning digital PID (Proportion Integration Differentiation) controller with an adjustable set point holds the temperature to within 1 1C at 1600 1C, assuring high accuracy calibration ( 70.25% of reading71digit for temperatures above 600 1C). The measurements were carried out at temperatures of 1083, 1093, 1113, y 1753, 1773 K. To avoid saturation or excessively small data values for the high-temperature blackbody measurements, the shutter and LUT were adjusted to appropriate values for the blackbody images. The data post-processing used a medium filter to eliminate random noise. This filter is suitable for real-time elimination of random noise in dynamic measurements. The non-uniformity distributions for the blackbody images at various temperatures are shown in Fig. 11. At higher temperatures, the uniformity is not good as the results in Fig. 10 due to the characteristics of the blackbody source itself. Also, the pixel values for channel B are smaller which results in more nonuniformity for channel B at higher temperature ranges. The relationship between ðub ; vb Þ and T was experimentally determined by averaging the pixel values of the blackbody images at various temperatures shown in Fig. 12. Note that ub and vb do not change monotonically with the temperature. The intensity non-uniformities for each blackbody image cause the temperature distributions to be non-uniform. The temperature results would be obtained from Eq. (13) with the relative error between this calculated average temperature and the blackbody standard temperature shown in Fig. 13. The range is within( 2.0, 1.5%). The temperature non-uniformity is given as in Eq. (9) by:
591
2.0 1.5 1.0 0.5 0.0 1083
1183
1283
1383
1483
1583
Temperature (K)
5.0
Fig. 14. Temperature non-uniformity.
4.5
i=R i=G i=B
Non-uniformity, %
4.0 3.5 3.0
Where Tðp; qÞ ¼
1 NM
N;M P
Tðp; qÞ;
N M is the effective number
p;q ¼ 1
of pixels in each image, and (p, q) are the coordinates of each pixel in the image. Fig. 12 shows that the temperature non-uniformity is 0.13–2.14%. Comparison of Fig. 14 with Fig. 11 shows that the temperature non-uniformity is not proportional to the pixel value non-uniformity, but they are similar.
2.5 2.0 1.5 1.0 0.5
3.3. Temperature sensitivity
83
33
17
83
17
33
16
83
16
33
15
83
15
33
14
83
14
33
13
83
13
33
12
83
12
11
83
11
10
33
0.0
Temperature (K) Fig. 11. Non-uniformity distribution at various temperatures.
6.3
1393K
5.8 5.3 vb
4.8 4.3 1753K
3.8
1133K 1093K 1113K 1083K
1773K
3.3 2.8 2.3 1.4
1.5
1.6
1.7
1.8
1.9 ub
2
2.1
Fig. 12. ðub ; vb Þ at various temperatures.
2.2
2.3
2.4
The relative temperature sensitivities for u and v are expressed as: 8 Du=u DCR =CR DCG =CG > > ¼ > RTSu ¼ < DT=T DT=T DT=T ð15Þ D v=v D C =C D CB =CB > R R > > : RTSv ¼ DT=T ¼ DT=T DT=T RTSu and RTSv are defined as the ratios of the relative changes in the radiation intensity Du/u and Dv/v relative to the relative change in the temperature DT/T. Large absolute values of RTSi(i=u, v) mean that the measurement radiation intensity signal ratios are more sensitive to the temperature, so the temperature sensitivity is higher. The results in Fig. 15 are based on the blackbody experiment data. For most of the temperatures, the absolute value of RTSv is larger than the absolute value of RTSu indicating that the signal ratio Dv/v is more sensitive to the temperature which may explain the difference between Fig. 11 and Fig. 14. Thus, the much greater non-uniformity for channel B at higher temperatures is expected because RTSv, which is related to channel B, is greater.
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280
i=u
10
270
i=v Temperature bandwidth (K)
Relative Temperature Sensitivity
12
8 6 4 2 0
260 250 240 230 220 210 200 190
-2 1050
1150
1250
1350 1450 1550 Temperature (K)
1650
1750
180 1083 1133 1183 1233 1283 1333 1383 1433 1483 1533 Lower temperature limit (K)
Fig. 15. Absolute value of RTSi at different temperatures.
Fig. 16. Effective temperature range.
3.4. Temperature range The dynamic range, b, of a sensor is defined as the ratio of the maximum detection signal due to the saturation to the minimum detection signal restricted by the noise. If the signal range exceeds the dynamic range of the sensor, the signal will become saturated or be lost in the noise. Generally, the temperature range is determined by requiring that the ratio of the maximum value to the minimum value of the three channel measured signals must be less than the dynamic range b of the sensors [15]. The temperature range (1083–1773 K) of the pyrometer investigated here was verified by the blackbody experiments. Since the temperature variations significantly change the measured values on each channel, not all temperatures in the temperature range can be simultaneously measured in one measurement. The signals range for each channel is restricted by the dynamic range of the sensor. Therefore, the temperature range needs to be partitioned with different LUT, exposure time and gain. The allowable temperatures that can be simultaneously measured are specified by: ( CR ðTHigh Þ=CR ðTLow Þ r b; CG ðTHigh Þ=CG ðTLow Þ r b; CB ðTHigh Þ=CB ðTLow Þr b; 1=b r CR =CG r b; 1=b r CR =CB r b: ð16Þ If any condition in Eq. (16) cannot be satisfied, then the signal for one of the channels at that temperature is beyond the dynamic range of the sensor. The temperature range must then be partitioned into N sub-zones ðTLow ; T1 Þ; ðT1 ; T2 Þ ðTN2 ; TN1 Þ; ðTN1 ; THigh Þ, to ensure that the signal variations for the different temperatures are all within the restrictions of Eq. (16). The proportionality relationships between the sub-zone signals can be used to identify transitions among different sub-zones with the instrument parameters adjusted for the different sub-zones. The temperature range satisfying Eq. (16) is defined as the effective temperature range when THigh is the upper temperature limit, TLow is the lower temperature limit, and DT= THigh TLow is the temperature bandwidth. For this CCD-based pyrometer system, the output signal range is 0–255 for any LUT setting although it has 12 bit data conversion precision. Tests showed that for values higher than 254, the output signal was prone to distortion caused by saturation while for values lower than 15, the signal was greatly influenced by noise. Therefore, the effective dynamic range b could be expressed as 254/15= 16.93. The results in Fig. 16 calculated based on Eq. (16) that the temperature bandwidth is about 190–270 K with the bandwidth increasing as the lower temperature limit increases for blackbody/gray body measurements. If the
temperature distributions on the measured objects are uniform, the temperature field processing will not have to be partitioned. However for objects with highly non-uniform temperature distributions that exceed the temperature bandwidths in Fig. 16, the temperature field must be partitioned. For objects that are not ideal gray bodies, the temperature bandwidths will be slightly different, but the difference is not significant.
4. Conclusions An optical CCD-based pyrometer system has been developed for high-temperature measurements for many possible applications in optical diagnostics. The measurement performance of the CCD-based system was evaluated in detail. Measurements of the irradiation emitted by an integrating sphere were used to investigate the influence of the system parameters (exposure time, global gain, R/G/B gain and LUT) on the intensity measurements. Expressions for Dt, Z and ki can be used to control the intensity measurements of the micro-sensor channels to improve the temperature measurements, for example the data quality and temperature range. The intensity measurement uniformity of the pyrometer system measured for an integrating sphere as a blackbody source was found to be acceptable. A modified threecolor method based on the ratios of the signals from the three channels is used to calculate the temperature without any geometry calibration. The temperature uniformity, temperature sensitivity and temperature range were analyzed for blackbody irradiation to show that the temperature non-uniformity is not proportional to the intensity non-uniformity and is in the range of 0.13–2.14%. The relative temperature sensitivities of RTSu and RTSv differ, which may provide a way to improve the measurement results. For example, due to RTSv 4RTSu, we need to enhance the measurement precision for the ratio signal u to optimize the results. In addition, combining with Eqs. (1), (10) and (15), improving RTSu and RTSv by varying the design of spectral sensitivity curves si(l) will be also to optimize the results. For temperatures in the range (1083, 1773 K), the temperature range bandwidth for object with a non-uniform temperature distribution varies from 190 to 270 K for this specific CCD-based pyrometer. Although these performance results were obtained for the standard blackbody experiments, the conclusions are general and can be applied to gray body measurements in practice. If the objects are not ideal gray bodies, the results may differ slightly. The object’s radiative characteristics can then be combined with the system spectral sensitivity response to improve the results. These results provide valuable information
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on CCD-based pyrometer system performance that will facilitate the use of CCD-based pyrometer systems in practice.
Acknowledgement The paper is supported by the National Natural Science Foundation of China (Grant No. 50606033 & 50704027), National High Technology Research and Development Program of China (2007AA04Z178), and China Research for the 11th Five-year Plan (2008BAB29B06). We thank Prof. D.M. Christopher for editing the English. References [1] Vattulainen J, Nummela V, Hernberg R, Kytola J. A system for quantitative imaging diagnostics and its application to pyrometric in-cylinder flametemperature measurements in large diesel engines. Measurement Science & Technology 2000;11:103–19. [2] Cignoli F, De Iuliis S, Manta V, Zizak G. Two-dimensional two-wavelength emission technique for soot diagnostics. Applied Optics 2001;40(30):5370–8. [3] Lu G, Yan Y, Riley G, Bheemul HC. Concurrent measurements of temperature and soot concentration of pulverized coal flames. IEEE Trans Inst Meas 2002;51(5):990–5. [4] Lu G, Yan Y. Temperature Profiling of Pulverized Coal Flames Using Multicolor Pyrometric and Digital Imaging Techniques. IEEE Trans Inst Meas 2006;55(4):1303–8. [5] Payri F, Pastor JV, Garcıa JM, Pastor JM. Contribution to the application of twocolour imaging to diesel combustion. Measurement Science and Technology 2007;18:2579–98. [6] Lu H, Ip L, Mackrory A, Werrett L, Scott J, Tree D, Baxter L. Particle surface temperature measurements with multicolor band pyrometry. AIChE Journal 2009;55(1):243–55. [7] Fu TR, Cheng XF, Shi CL, Zhong MH, Liu TM, Zheng XB. The set-up of a vision pyrometer. Measurement Science & Technology 2006;17:659–65.
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[8] Luo ZX, Zhou HC. A Combustion-Monitoring System With 3-D Temperature Reconstruction Based on Flame-Image Processing Technique. IEEE Trans Inst Meas 2007;56(5):1877–82. [9] Fu TR, Cheng XF, Yang ZJ. Theoretical evaluation of measurement uncertainties of two-color pyrometry applied to optical diagnostics. Applied Optics 2008;47(32):6112–23. [10] Tsyba GA, Salamatov VG, Polyakov VL. A Video Pyrometer. Instruments and Experimental Techniques 2003;46(4):480–3. [11] Hwang JH, Kompella S, Chandrasekar S, Farris TN. Measurement of Temperature Field in Surface Grinding Using Infra-Red (IR) Imaging System. Journal of Tribology 2003;125:377–83. [12] Price JR, Meriaudeau F, editors. Industrial Inspection XII, 5303. SPIE; 2004 treatment processes. [13] Ranc N, Pina V, Sutter G, Philippon S. Temperature Measurement by Visible Pyrometry: Orthogonal Cutting Application. Journal of Heat Transfer 2004;126:931–6. [14] Simmons DF, Fortgang CM, Holtkamp DB. Using multispectral imaging to measure temperature profiles and emissivity of large thermionic dispenser cathodes. Review of Scientific Instruments 2005;76:044901. [15] Fu TR, Cheng XF, Zhong MH, Liu TM. The theoretical prediction analyses of the measurement range for multi-band pyrometry. Measurement Science & Technology 2006;17:2751–6. [16] Meriaudeau F. Real time multispectral high temperature measurement: Application to control in the industry. Image and Vision Computing 2007;25:1124–33. [17] Zauner G, Heim D, Niel K, Hendorfer G, Stoeri H. CCD Cameras as thermal Imaging devices in heat A.W. Jacksona, A.C. Gossard, Thermal imaging of wafer temperature in MBE using a digital camera. Journal of Crystal Growth 2007;301–302:105–8. [18] Zhao H, Feng HJ, Xu ZH, Li Q. Research on temperature distribution of combustion flames based on high dynamic range imaging. Optics & Laser Technology 2007;39:1351–9. [19] Liu D, Wang F, Cen KF, Yan JH, Huang QX, Chi Y. Noncontact temperature measurement by means of CCD cameras in a participating medium. Optics Letters 2008;33(5):422–4. [20] Chrzanowski K, Matyszkiel R, Fischer J, Bare"a J. Uncertainty of temperature measurement with thermal cameras. Optical Engineering 2001;40(6): 1106–14. [21] Chrzanowski K. Evaluation of commercial thermal cameras in quality systems. Optical Engineering 2002;41(10):2556–67.
Contents lists available at ScienceDirect
Optics & Laser Technology journal homepage: www.elsevier.com/locate/optlastec
Measurement performance of an optical CCD-based pyrometer system Tairan Fu a,n, Zangjian Yang b, Luping Wang b, Xiaofang Cheng b, Maohua Zhong c, Congling Shi c a b c
Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084, PR China Department of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei 230026, PR China China Academy of Safety Science and Technology, Beijing 100029, PR China
a r t i c l e in f o
a b s t r a c t
Article history: Received 13 June 2009 Received in revised form 20 August 2009 Accepted 27 October 2009 Available online 20 November 2009
The measurement performance of a CCD-based pyrometer system using a three-color method was evaluated for scientific and engineering metrology. The relationships between the system parameters (exposure time and sensor gain) and the intensity measurements in an integrating sphere experiment were determined for a specific CCD sensor. The pyrometer system uses the three-color method based on the intensity ratio without geometry calibrations. The field measurement characteristics and the effectiveness of coupling the three-color channels were investigated in terms of the temperature measurement uniformity, temperature sensitivity and temperature range of the pyrometer system in standard blackbody tests. The results showed that the temperature non-uniformity is not proportional to the intensity non-uniformity and is in the range of 0.13–2.14%. The relative temperature sensitivities of intensity ratios for different channel combinations are different, which may provide a way to improve the measurement results. The temperature range bandwidth for object with a non-uniform temperature distribution varies from 190 to 270 K for this specific CCD-based pyrometer. The performance evaluation conclusions for the system with this specific CCD sensor are general and applicable for pyrometer systems using other CCD sensors. & 2009 Elsevier Ltd. All rights reserved.
Keywords: Pyrometer Optical diagnostics Temperature
1. Introduction Optical radiation pyrometry, the determination of the temperature of an object based on its luminosity caused by thermal self-radiation, is an effective and practical method for measuring combustion temperatures or surface temperatures. In recent years, optical pyrometers have been built with a charge coupled device (CCD) for temperature distribution measurements through optical visualization [1–8]. A CCD is a light-sensitive integrated circuit that stores and displays the data for an image in such a way that each pixel in the image is converted into an electrical charge. CCDs are used in the astronomical telescopes, scanners, machine vision system, optical character recognition and meteorology. The availability of CCD sensors conveniently provides temperature field measurements which overcomes the shortcoming of traditional spot pyrometers only detecting several points. Existing CCD-based pyrometer systems based on the multicolor method use various means to separate the measurement wavelengths/wavebands with single CCD or multiple CCDs. The former is more advantageous due to the simple system design. In a single CCD system, images for different colors may be sequentially formed on the same monochrome sensor array
n
Corresponding author. E-mail address: [email protected] (T. Fu).
0030-3992/$ - see front matter & 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.optlastec.2009.10.008
through a beam splitting/filtering assembly with narrow-band interference filters [2–4] or they can be simultaneously obtained from a color sensor array with a mosaic pixel filter (for example, an R-G-B Bayer filter) [6–8]. The method using narrow-band interference filters corresponds to multi-color pyrometry with wavelength measurements, while that using an R-G-B Bayer mosaic pixel filter is looked upon as multi-color pyrometry with waveband measurements. If R-G-B waveband measurements are simplified as three effective wavelengths measurements, it will cause great error even though the conversion relationship is calibrated with blackbody experiments. Previous research on CCD-based pyrometer systems has mainly focused on two approaches to calculate the temperatures. One approach is to beforehand calibrate the system to determine the relationship between the radiation intensity and the corresponding sensor output using the same geometric parameters for the system and the measured object [4]. This relationship is only suitable for the measurements at the same geometric condition. Once the condition is changed, the calibration process needs to be undertaken again. The other approach is to utilize the radiation intensity ratio of different wavelengths/wavebands as a relative intensity. The geometric factor,F (Eq. (1)), is eliminated through the ratio processing (Eq. (10)) and it avoids the calibrations for the geometry condition [6,7]. The measurement uncertainties of these two approaches were theoretically evaluated by Fu et al. [9]. The correlation theory and other aspects of CCD-based pyrometry applications have been analyzed in many references [10–19].
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Although optical pyrometers based on color CCDs have been applied in research studies of high-temperature measurement with promising results, there are few commercially available CCD-based multi-color pyrometers for temperature field measurements in engineering applications. Some technology issues are still worth further studying. The measurement ability of the CCD-based pyrometers using the multi-color method has not received sufficient attention or been scientifically analyzed in the literature. In applications of CCD sensor as a scientific temperature metrology device, it is necessary to evaluate the system measurement performance, including the measurement uncertainty [20,21], system parameters, measurement range and measurement sensitivity. The image processing and CCD-sensor characteristics are generally related to the system parameters (exposure time, sensor gain, etc.), but the quantitative relationships between these parameters and the intensity/temperature measurements are not clear. This analysis is based on a threecolor pyrometer system using a color CCD to evaluate the system performance for scientific and engineering metrology as a function of the system parameters, measurement uniformity, measurement sensitivity and measurement range. The coupling characteristics of the three-color channels in the pyrometer system, based on the intensity ratios, cause the analysis of the measurement performance to be much different from analyses of traditional and commercial single/dual-channel pyrometer systems, arising from the intensity ratio analyses of more channels. In addition, performance analyses of field measurements with CCD-based pyrometers also differ from analyses of other systems measuring only several points. The analysis presented in this paper provides a valuable description of the performance of CCDbased pyrometers using the multi-color method to make such systems more practical for scientific and engineering applications.
The system applies gains and then does an A/D conversion to get the digital output signals. The pixel values of the recorded CCD frame image are the outputs of the array of micro-sensors. The instrument sensor parameters, including the image LUT (lookup-table), aperture, shutter, global gain and R/G/B gain, are the important adjustable quantities in the CCD-based pyrometer system. These parameters control the intensity measurements of the micro-sensors which affect the temperature measurements. The equation relating the spectral irradiation to the pixel output of the frame image is: ! Z Dt le ð1Þ si ðlÞUI ðlÞ dl þ ni ; i ¼ R; G; B Ci ¼ Zki FU 2 F ls Where Ci is the pixel digital value with non-dimension in channel i, obtained by A/D conversion. For a 8 bit output, this value range is from 0 to 255. I(l) is the spectral distribution of the irradiance reaching the CCD sensor per unit time at wavelength l, W m 2 sr 1 mm 1; si(l) is the spectral sensitivity for the combinations of lens/image-optics/color-filter/sensor in channel i; F is a geometric factor that is a function of the radiation attenuation, observation distance, observation angle and lens properties; Dt is the exposure time, s; F is f-number of the aperture; ni is the dark noise in channel i and may be estimated by capturing frame images with the lens cap on the pyrometer; (ls,le) are the system wavelength range, nm; Z is the zooming coefficient relative with the global gain; and ki is the zooming coefficient relative to the R/G/B channel gain. In Eq. (1), different channels (i= R, G, B) correspond to different micro-sensors with different spectral response distributions in the CCD-based system. Therefore, the image pixel values (CR, CG, CB) may be looked upon as three channels of system outputs. Rl Defining Ei ¼ F=F 2 ð lse si ðlÞIðlÞdlÞ: Ci ¼ Zki ðDt Ei þ ni Þ;
2. Calibration of CCD-based pyrometer system The design of a CCD-based pyrometer system is shown in Fig. 1. The color CCD is the key part of the optical pyrometer system, with its characteristics determining the measurement performance of the optical pyrometer system. The system data processing procedure is shown in Fig. 2. The light rays are focused on the CCD focal plane and then translated into electronic signals.
587
i ¼ R; G; B
When Z = 1 and ki = 1, Ci,0 = Dt Ei + ni. This research used a pyrometer system based on the IMC 147FT CCD camera with the ICX285AL chip (progressive scanning, 1,450,000 pixels 1392(H) 1036(V), cell size 6.45 6.45 mm, 12 bit data depth, S/N ratio 456 dB, 20 FPS at maximum resolution), for the following analysis. The spectral sensitivity curves si(l) of IMC 147FT CCD camera may be determined by spectrum experiments [7]. Here only a brief description of the measurement
Hardware construction
Software analysis
High-temperature objects Color Optical
Data processing
CCD sensor
lens
Temperarture result Fig. 1. Design of a CCD-based pyrometer system.
Optical lens Aperture parameter
Color CCD sensor Exposure time
ð2Þ
Global gain
R/G/B gain
Input irradiation
A/D conversion
Output data Fig. 2. System data processing.
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1 Relative spectral sensitivity
0.9
Channel R Channel G Channel B
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
370 400 430 460 490 520 550 580 610 640 670 700 730 760 790 Wavelength (nm) Fig. 3. Relative spectral sensitivity curves.
18 Level 8
Spectral radiation intensity (µw/(cm2 × Sr × nm))
16
14 Level 6
12
10
optical axis to be perpendicular to the exit plane and the uniform exit radiation filling the entire field of view. Eliminate the interference from background light sources and keep the environment dark. Maintain steady working conditions by pre-heating the integrating sphere for half an hour.
Level 4
8
2.2. LUT setting
6 Level 2
4
Level 1
2 0 300
400
500
600
700
800
900
1000
1100
Wavelength (nm) Fig. 4. Spectral radiation intensity distribution.
progress was introduced. The spectral sensitivity curves were measured by presenting the monochromatic light stimuli, obtained with a monochromator and a 250 W bromine tungsten lamp, to the camera at every spaced wavelength (5 nm interval) in the spectrum range 370–810 nm. Simultaneously, the monochromatic radiation intensities at different wavelengths were recorded with a Si-photodiode. Then, the relative spectral sensitivity curves of the camera were obtained, shown in Fig. 3. The results show that when l 4730 nm, the spectral sensitivity is zero. Therefore, (ls, le) are set to (370, 730 nm). 2.1. Experimental conditions To verify the influences of the system parameters on the radiation intensity measurement, an IS2500-1000 integrating sphere was used as the standard calibration source to provide steady, uniform reference irradiation. The sphere diameter was 2500 mm and the opening diameter was 1000 mm. The sphere contained sixty four 250 W bromine tungsten lamps which were symmetrically distributed in the sphere, classified in 8 levels (leve1 8: 64 lamps open; level 4: 32 lamps open; level 1: 8 lamps open). The filament length of each lamp was 5 mm. The spectrum range of the radiation output was 250–2500 nm, shown in Fig. 4. The stability of the source was up to 99.2% with an opening irradiation uniformity of 99.81%. The experimental condition was based on the following:
Fix the position of the CCD system at a distance of 1.1 m to the sphere exit plane and adjust the iris aperture. Fix the system
The 12 bit CCD output data was first converted into 8 bit data based on the LUT. LUT= 0 means that bits 1–8 were used from the 12 bit data as the output data, LUT= 1 means that bits 2–9 were used, and so on. Therefore, the output Ci was calibrated based on the LUT setting with the actual calibrated maximum being up to 4095 (LUT=4). The LUT setting enables the pyrometer system to work with different light intensities. 2.3. Exposure time The adjustment of exposure time prevents the image data to be saturated or dark, and also makes the measurements suitable for high dynamic frequency conditions using a shorter exposure time. The electrical shutter, accurately controlled by the software, theoretically determines the exposure time in Eq. (1). However, the exposure linearity of the intensity response described in the Eq. (1) still needs to be verified for actual measurements. Frame images at different exposure times were captured for a global gain and R/G/B gains of 0. Fig. 5 illustrates the relationship between Ci and the exposure time which shows that Ci is proportional to the exposure time when Ci is less than the critical value. The critical value CB (about 2950) of channel B is slightly lower than the critical values (about 3100) of other channels, R and G, which results from the differences of photo-electricity conversion capacity of different channels of CCD sensor. In the very short exposure time range, this linearity relationship is still satisfied for applications. Therefore, the linear exposure response described in Eq. (1) is correct for reasonable Ci, but Ci can reach a maximum critical value when the response is no longer linear. This nonlinearity arises from the CCD physical characteristics and does not fit for actual measurements. Therefore, the LUT setting should be less than 4 to avoid this non-linearity. 2.4. Sensor gain The global gain and R/G/B gains varied from 0 to 511. For gains of 0, Z =1 and ki =1 in Eq. (1). The relationship between these
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589
2500 3500
2250
i=R
3000
2000
i=G
2500
1750
i =B
1500
Ci
1500
Ci
i=R i=G i=B
2000
1250 1000
1000
750
500
500 250
0 0
0
1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Exposure Time (µs)
50
100 150 200 250 300 350 400 450 500 GainR
Fig. 7. Pixel values for various R gains for a global gain of 0.
1600 1400
i=R i=G i=B
1200 1000
2500 2250
i=R
800
2000
i=G
600
1750
i=B
400
1500
200
1250
Ci
Ci
0
1000
0 100 200 300 400 500 600 700 800 900 1000 1100 Exposure Time (µs)
750
Fig. 5. (a) Pixel values for various exposure times, (b) Local magnification of (a).
250
0
500 0
2500
0
2250
50
100
150
200
i=R
2000
i=G
1750
250
300
350
400
450
500
GainG Fig. 8. Pixel values for various G gains for a global gain of 0.
i=B
Ci
1500
The fitting results are given by:
1250
GcoefR ¼ 0:001782;
1000 750 500 250 0 0
50
100
150
200
250
300
350
400
450
500
GGain Fig. 6. Pixel values for various global gains with the R/G/B gains set to 0.
values and the actual zooming coefficients, Z and ki, is unknown. The gain can be adjusted to broaden the effective dynamic range of the measurement channels. For example, if the signal in channel R is too weak to be analyzed, the data quality can be improved by setting a higher R gain. Frame images were grabbed at various global gains for R/G/B gains of 0 (ki = 1). The relationship between Ci and the global value (represented by GGain) shown in Fig. 6 can be fit by: C log i ¼ Gcoefi GGain; Ci;0
i ¼ R; G; B
ð3Þ
where Gcoefi is the fitting coefficient for the channel i. When ki = 1, the zooming value, Z, can be expressed as: Gcoefi GGain
Z ¼ 10
ð4Þ
GcoefG ¼ 0:001781;
GcoefB ¼ 0:001778
ð5Þ
The results show that the influence of the global gain on the intensity responses of the three channels is almost same, GcoefR EGcoefG EGcoefB. Through adjusting the global gain value, the maximum zooming rates Zmax for three channels are about 8.19 (R channel), 8.18 (G channel) and 8.14 (B channel). It means that for 8 bit output data 0–255 of three channels may be respectively broadened to 0–2088 (R channel), 0–2086 (G channel) and 0–2076 (B channel). Frame images for various R/G/B gains values were captured for a global gain of 0(Z = 1). The relationships between Ci and the R/G/ B gains (represented by GainR, GainG, GainB) shown in Figs. 7–9 can be fit by: log
Ci ¼ coefi Gaini ; Ci;0
i ¼ R; G; B
ð6Þ
Where coefi is the fitting coefficient for channel i. When Z = 1, the zooming value, ki, is expressed as,
ki ¼ 10coefi Gaini
ð7Þ
The fitting results are: CoefR ¼ 0:001791;
CoefG ¼ 0:001791;
CoefB ¼ 0:001786
ð8Þ
The results show that the influences of the R/G/B gains on the intensity responses are also same, CoefR ECoefG ECoefB. The change of the R gain does not affect other two channels of G and B,
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2500
3.0
i=R
2000
i=G
1750
i=B
1500 Ci
2.5
Non-uniformity distribution, %
2250
1250 1000 750 500 250
2.0 1.5 1.0
i=R i=G
0.5
i=B 0.0
0 0
50
100
150
200
250 300 GainB
350
400
450
0
500
50
100
150
200
250
300
350
400
450
500
GGain
Fig. 9. Pixel values for various B gains for a global gain of 0.
Fig. 10. Non-uniformity distribution.
which is same for the G gain and the B gain. Through adjusting the R/G/B gains values, the maximum zooming rates of three channels are about kR,max E kG,max E kB,max E8.25. It means that for 8 bit output data 0–255 may be broadened to 0–2104.
geometry calibrations. First, normalize the measured signals (CR, CG, CB). as (u, v),
2.5. Uniformity analysis
where Ib (l,T) is the spectral radiance intensity of an ideal blackbody at the same temperature T and e(l,T) is the spectral emissivity. From Eq. (10), we know that the geometric factor F of Eq. (1) is eliminated and it effectively avoids the calibrations for the geometry quantity F in temperature calculations. The pyrometer performance is based on the typical standard blackbody, e(l,T) E1.0, so the normalized data for a blackbody measurement (mb,vb) is:
u¼
R kR U llse sR ðlÞUeðl; TÞUIb ðl; TÞdl CR ¼ ; R CG kG U llse sG ðlÞUeðl; TÞUIb ðl; TÞdl
v¼
R kR U llse sR ðlÞUeðl; TÞUIb ðl; TÞdl CR ¼ R CB kB U llse sB ðlÞUeðl; TÞUIb ðl; TÞdl
ð10Þ
The uniformity of the frame image data depends upon the uniformity of the standard source and the system itself which experiences random noise in the CCD sensor and inherent differences in the micro-sensors. The integrating sphere is very uniform (99.81%) and stable (99.2%), thus, the non-uniformity of the recorded two-dimensional data can be used to evaluate the non-uniformity of the pyrometer system itself. The non-uniformity can be quantified by: "
N;M X 1 ðCi ðp; qÞ Ci ðp; qÞÞ2 Ci ðp; qÞ N M p;q ¼ 1
1
whereCi ðp; qÞ ¼
1 NM
N;M P
Ci ðp; qÞ;
ub ¼
#0:5
R kR llse sR ðlÞUIb ðl; TÞdl CR;b ¼ ; R CG;b kG llse sG ðlÞUIb ðl; TÞdl
vb ¼
R kR llse sR ðlÞUIb ðl; TÞdl CR;b ¼ R CB;b kB llse sB ðlÞUIb ðl; TÞdl
ð11Þ ð9Þ
When the spectral sensitivities (sR(l), sG(l), sB(l)) are fixed, (ub,vb) uniquely depend on the temperature T. Therefore, averaging of the pixel values for a blackbody image gives:
N M is the effective number
i;j ¼ 1
of pixels in the frame image and (p, q) are the coordinates of each pixel in the image. Fig. 10 shows the uniformity distribution of the pixel values as a function of GGain which is acceptable for these measurements. The non-uniformities for the R and G channels are less than 1.5%, but the non-uniformity of the B channel is about 2.5%. The difference is mainly due to smaller values for the B channel compared with the other channels. Higher pixel values make the influence of the random noise insignificant, so the uniformity distribution is improved.
ub ¼
N;M X 1 u ðp; qÞ; N M p;q ¼ 1 b
vb ¼
N;M X 1 v ðp; qÞ N M p;q ¼ 1 b
ð12Þ
3. Temperature measurement performance of CCD-based pyrometer system
Where N M is the effective number of pixels in the frame image. The relationship between ðub ; vb Þ and T can be determined through measurements with a blackbody with the results stored in a database. This relationship is not a function of the geometry quantity F. In actual applications, the measured normalized data (umeas, vmeas) are often affected by measurement uncertainties so they deviate from the fitting relationship between ðub ; vb Þ and T. Thus, the temperature is calculated iteratively by minimizing the following equation in a selected temperature range: @T 2 @T 2 þ ðvmeas: vb Þ ) min ð13Þ ðumeas: ub Þ @ub @vb
3.1. Measurement method
3.2. Temperature uniformity
In the CCD-based pyrometer system, the images are recorded simultaneously from the three R-G-B micro-sensors with spectral sensitivities (sR(l), sG(l), sB(l)). These may be analyzed as three waveband measurements. The measurements are combined with emissivity models to calculate the temperatures using threecolor pyrometry method based on the intensity ratios without
A Mikron M330 blackbody was used as the calibration reference to illustrate the pyrometer performance. The blackbody can produce any temperature between 300 and 1700 1C. The blackbody consists of a closed end tube with a 25 mm diameter aperture with the tube heated by specially manufactured elements which provide excellent uniformity and a heat-up time
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" #0:5 N;M X 2 1 1 Tðp; qÞ Tðp; qÞ Tðp; qÞ N M p;q ¼ 1
ð14Þ
1.5
Temperature Error, %
1.0 0.5 0.0 1083 -0.5
1183
1283
1383
1483
1583
1683
1783
1683
1783
-1.0 -1.5 -2.0 Temperature (K) Fig. 13. Relative temperature error.
2.5 Temperature Non-uniformity, %
of 80 min to reach 1600 1C. A self-tuning digital PID (Proportion Integration Differentiation) controller with an adjustable set point holds the temperature to within 1 1C at 1600 1C, assuring high accuracy calibration ( 70.25% of reading71digit for temperatures above 600 1C). The measurements were carried out at temperatures of 1083, 1093, 1113, y 1753, 1773 K. To avoid saturation or excessively small data values for the high-temperature blackbody measurements, the shutter and LUT were adjusted to appropriate values for the blackbody images. The data post-processing used a medium filter to eliminate random noise. This filter is suitable for real-time elimination of random noise in dynamic measurements. The non-uniformity distributions for the blackbody images at various temperatures are shown in Fig. 11. At higher temperatures, the uniformity is not good as the results in Fig. 10 due to the characteristics of the blackbody source itself. Also, the pixel values for channel B are smaller which results in more nonuniformity for channel B at higher temperature ranges. The relationship between ðub ; vb Þ and T was experimentally determined by averaging the pixel values of the blackbody images at various temperatures shown in Fig. 12. Note that ub and vb do not change monotonically with the temperature. The intensity non-uniformities for each blackbody image cause the temperature distributions to be non-uniform. The temperature results would be obtained from Eq. (13) with the relative error between this calculated average temperature and the blackbody standard temperature shown in Fig. 13. The range is within( 2.0, 1.5%). The temperature non-uniformity is given as in Eq. (9) by:
591
2.0 1.5 1.0 0.5 0.0 1083
1183
1283
1383
1483
1583
Temperature (K)
5.0
Fig. 14. Temperature non-uniformity.
4.5
i=R i=G i=B
Non-uniformity, %
4.0 3.5 3.0
Where Tðp; qÞ ¼
1 NM
N;M P
Tðp; qÞ;
N M is the effective number
p;q ¼ 1
of pixels in each image, and (p, q) are the coordinates of each pixel in the image. Fig. 12 shows that the temperature non-uniformity is 0.13–2.14%. Comparison of Fig. 14 with Fig. 11 shows that the temperature non-uniformity is not proportional to the pixel value non-uniformity, but they are similar.
2.5 2.0 1.5 1.0 0.5
3.3. Temperature sensitivity
83
33
17
83
17
33
16
83
16
33
15
83
15
33
14
83
14
33
13
83
13
33
12
83
12
11
83
11
10
33
0.0
Temperature (K) Fig. 11. Non-uniformity distribution at various temperatures.
6.3
1393K
5.8 5.3 vb
4.8 4.3 1753K
3.8
1133K 1093K 1113K 1083K
1773K
3.3 2.8 2.3 1.4
1.5
1.6
1.7
1.8
1.9 ub
2
2.1
Fig. 12. ðub ; vb Þ at various temperatures.
2.2
2.3
2.4
The relative temperature sensitivities for u and v are expressed as: 8 Du=u DCR =CR DCG =CG > > ¼ > RTSu ¼ < DT=T DT=T DT=T ð15Þ D v=v D C =C D CB =CB > R R > > : RTSv ¼ DT=T ¼ DT=T DT=T RTSu and RTSv are defined as the ratios of the relative changes in the radiation intensity Du/u and Dv/v relative to the relative change in the temperature DT/T. Large absolute values of RTSi(i=u, v) mean that the measurement radiation intensity signal ratios are more sensitive to the temperature, so the temperature sensitivity is higher. The results in Fig. 15 are based on the blackbody experiment data. For most of the temperatures, the absolute value of RTSv is larger than the absolute value of RTSu indicating that the signal ratio Dv/v is more sensitive to the temperature which may explain the difference between Fig. 11 and Fig. 14. Thus, the much greater non-uniformity for channel B at higher temperatures is expected because RTSv, which is related to channel B, is greater.
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T. Fu et al. / Optics & Laser Technology 42 (2010) 586–593
280
i=u
10
270
i=v Temperature bandwidth (K)
Relative Temperature Sensitivity
12
8 6 4 2 0
260 250 240 230 220 210 200 190
-2 1050
1150
1250
1350 1450 1550 Temperature (K)
1650
1750
180 1083 1133 1183 1233 1283 1333 1383 1433 1483 1533 Lower temperature limit (K)
Fig. 15. Absolute value of RTSi at different temperatures.
Fig. 16. Effective temperature range.
3.4. Temperature range The dynamic range, b, of a sensor is defined as the ratio of the maximum detection signal due to the saturation to the minimum detection signal restricted by the noise. If the signal range exceeds the dynamic range of the sensor, the signal will become saturated or be lost in the noise. Generally, the temperature range is determined by requiring that the ratio of the maximum value to the minimum value of the three channel measured signals must be less than the dynamic range b of the sensors [15]. The temperature range (1083–1773 K) of the pyrometer investigated here was verified by the blackbody experiments. Since the temperature variations significantly change the measured values on each channel, not all temperatures in the temperature range can be simultaneously measured in one measurement. The signals range for each channel is restricted by the dynamic range of the sensor. Therefore, the temperature range needs to be partitioned with different LUT, exposure time and gain. The allowable temperatures that can be simultaneously measured are specified by: ( CR ðTHigh Þ=CR ðTLow Þ r b; CG ðTHigh Þ=CG ðTLow Þ r b; CB ðTHigh Þ=CB ðTLow Þr b; 1=b r CR =CG r b; 1=b r CR =CB r b: ð16Þ If any condition in Eq. (16) cannot be satisfied, then the signal for one of the channels at that temperature is beyond the dynamic range of the sensor. The temperature range must then be partitioned into N sub-zones ðTLow ; T1 Þ; ðT1 ; T2 Þ ðTN2 ; TN1 Þ; ðTN1 ; THigh Þ, to ensure that the signal variations for the different temperatures are all within the restrictions of Eq. (16). The proportionality relationships between the sub-zone signals can be used to identify transitions among different sub-zones with the instrument parameters adjusted for the different sub-zones. The temperature range satisfying Eq. (16) is defined as the effective temperature range when THigh is the upper temperature limit, TLow is the lower temperature limit, and DT= THigh TLow is the temperature bandwidth. For this CCD-based pyrometer system, the output signal range is 0–255 for any LUT setting although it has 12 bit data conversion precision. Tests showed that for values higher than 254, the output signal was prone to distortion caused by saturation while for values lower than 15, the signal was greatly influenced by noise. Therefore, the effective dynamic range b could be expressed as 254/15= 16.93. The results in Fig. 16 calculated based on Eq. (16) that the temperature bandwidth is about 190–270 K with the bandwidth increasing as the lower temperature limit increases for blackbody/gray body measurements. If the
temperature distributions on the measured objects are uniform, the temperature field processing will not have to be partitioned. However for objects with highly non-uniform temperature distributions that exceed the temperature bandwidths in Fig. 16, the temperature field must be partitioned. For objects that are not ideal gray bodies, the temperature bandwidths will be slightly different, but the difference is not significant.
4. Conclusions An optical CCD-based pyrometer system has been developed for high-temperature measurements for many possible applications in optical diagnostics. The measurement performance of the CCD-based system was evaluated in detail. Measurements of the irradiation emitted by an integrating sphere were used to investigate the influence of the system parameters (exposure time, global gain, R/G/B gain and LUT) on the intensity measurements. Expressions for Dt, Z and ki can be used to control the intensity measurements of the micro-sensor channels to improve the temperature measurements, for example the data quality and temperature range. The intensity measurement uniformity of the pyrometer system measured for an integrating sphere as a blackbody source was found to be acceptable. A modified threecolor method based on the ratios of the signals from the three channels is used to calculate the temperature without any geometry calibration. The temperature uniformity, temperature sensitivity and temperature range were analyzed for blackbody irradiation to show that the temperature non-uniformity is not proportional to the intensity non-uniformity and is in the range of 0.13–2.14%. The relative temperature sensitivities of RTSu and RTSv differ, which may provide a way to improve the measurement results. For example, due to RTSv 4RTSu, we need to enhance the measurement precision for the ratio signal u to optimize the results. In addition, combining with Eqs. (1), (10) and (15), improving RTSu and RTSv by varying the design of spectral sensitivity curves si(l) will be also to optimize the results. For temperatures in the range (1083, 1773 K), the temperature range bandwidth for object with a non-uniform temperature distribution varies from 190 to 270 K for this specific CCD-based pyrometer. Although these performance results were obtained for the standard blackbody experiments, the conclusions are general and can be applied to gray body measurements in practice. If the objects are not ideal gray bodies, the results may differ slightly. The object’s radiative characteristics can then be combined with the system spectral sensitivity response to improve the results. These results provide valuable information
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on CCD-based pyrometer system performance that will facilitate the use of CCD-based pyrometer systems in practice.
Acknowledgement The paper is supported by the National Natural Science Foundation of China (Grant No. 50606033 & 50704027), National High Technology Research and Development Program of China (2007AA04Z178), and China Research for the 11th Five-year Plan (2008BAB29B06). We thank Prof. D.M. Christopher for editing the English. References [1] Vattulainen J, Nummela V, Hernberg R, Kytola J. A system for quantitative imaging diagnostics and its application to pyrometric in-cylinder flametemperature measurements in large diesel engines. Measurement Science & Technology 2000;11:103–19. [2] Cignoli F, De Iuliis S, Manta V, Zizak G. Two-dimensional two-wavelength emission technique for soot diagnostics. Applied Optics 2001;40(30):5370–8. [3] Lu G, Yan Y, Riley G, Bheemul HC. Concurrent measurements of temperature and soot concentration of pulverized coal flames. IEEE Trans Inst Meas 2002;51(5):990–5. [4] Lu G, Yan Y. Temperature Profiling of Pulverized Coal Flames Using Multicolor Pyrometric and Digital Imaging Techniques. IEEE Trans Inst Meas 2006;55(4):1303–8. [5] Payri F, Pastor JV, Garcıa JM, Pastor JM. Contribution to the application of twocolour imaging to diesel combustion. Measurement Science and Technology 2007;18:2579–98. [6] Lu H, Ip L, Mackrory A, Werrett L, Scott J, Tree D, Baxter L. Particle surface temperature measurements with multicolor band pyrometry. AIChE Journal 2009;55(1):243–55. [7] Fu TR, Cheng XF, Shi CL, Zhong MH, Liu TM, Zheng XB. The set-up of a vision pyrometer. Measurement Science & Technology 2006;17:659–65.
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