Free emissivity temperature investigations by dual color applied physics methodology in the mid- and long-infrared ranges

International Journal of Thermal Sciences 117 (2017) 328e341

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Free emissivity temperature investigations by dual color applied physics methodology in the mid- and long-infrared ranges L. Savino a, M. De Cesare a, b, c, *, M. Musto d, G. Rotondo d, F. De Filippis e, A. Del Vecchio a, c, F. Russo d a

Department of Diagnostic Methodologies and Measurement Techniques, CIRA - Italian Aerospace Research Centre, Via Maiorise, 81043, Capua, Italy Department of Mathematics and Physics, CIRCE Laboratory, University of Campania “Luigi Vanvitelli”, viale Lincoln 5, 81100, Caserta, Italy INFN - National Institute for Nuclear Physics, Section of Naples, Via Cinthia, 80126, Napoli, Italy d Department of Industrial Engineering, University of Naples “Federico II”, Piaz.le Tecchio 80, 80125 Napoli, Italy e Department of Large Test Thermostructural Facilities, CIRA - Italian Aerospace Research Centre, Via Maiorise, 81043, Capua, Italy b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 July 2016 Received in revised form 29 March 2017 Accepted 29 March 2017 Available online 14 April 2017

In this work a free emissivity (dual color) thermographic technique, based on the ratio of monochromatic emissive power, is investigated. It can be performed by equipping the InfraRed (IR) camera of two band pass filters in such a way to consider the emissivity parameter as a constant value. Two colour technique can reveal its utility in fields of applied physics where intrusive techniques are not allowed and/or materials are characterized by unknown emissivity. This physics methodology can be really useful, for example, in temperature determination of (Aero) Space materials (such as TPS-Thermal Protection Systems), tested on ground Plasma Wind Tunnel, solid targets temperature determination due to ions bombarding by means of accelerators for nuclear (Astro) Physics and/or environmental physics applications. In this paper, temperature measurement investigations based on the choice of central wavelength distances of two filters are reported. In particular a numerical model simulation, experimentally validated in the Long and Mid (LW, MW) e Wavelength ranges, was built and used to determine the feasibility of the technique and to choose the best filters combinations. In addition, after the verification capability in MW range, the temperature measurements on an aluminium plate were carried out with the dual colour technique. Moreover the verified numerical model was used to analyze errors of the two color technique in MW range using different curves of materials with variable emissivity. The study was carried out up to 500
C and the results show that this innovative technique allows measurements of surface temperatures with errors of few % in MW range. © 2017 Elsevier Masson SAS. All rights reserved.

1. Introduction In the recent years, the simple use of thermal imaging to detect the temperature distribution of several objects has become a popular tool in many industrial fields. The research, therefore, is

* Corresponding author. Department of Diagnostic Methodologies and Measurement Techniques, CIRA - Italian Aerospace Research Centre, Via Maiorise, 81043, Capua, Italy. E-mail addresses: [email protected] (L. Savino), [email protected] (M. De Cesare), [email protected] (M. Musto), [email protected] (G. Rotondo), f. defi[email protected] (F. De Filippis), [email protected] (A. Del Vecchio), [email protected] (F. Russo). http://dx.doi.org/10.1016/j.ijthermalsci.2017.03.028 1290-0729/© 2017 Elsevier Masson SAS. All rights reserved.

focused to improve the thermographic measurement techniques in order to obtain values for temperatures as accurate and reliable as possible. For example materials used for Thermal Protection System (TPS) of space vehicles during the atmospheric re-entry, require special hypersonic Plasma Wind Tunnel test facility in which high temperature, due to the high power transferred by friction, is achieved [1]. The quantification of the temperature reached from the material during the tests represents a key factor to characterize the TPS. Over the years several techniques were developed to measure point-like objects temperature, in severe conditions, with different degrees of accuracy such as thermocouples or by means of inferential way using IR pyrometers [1,2], but on the contrary the IR thermal camera was preferred for temperature measurement of

L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

large surfaces. The main limitation of the contactless inferential temperature measurement techniques is due to the a priori knowledge of the material emissivity [2]. In the application in which the surface emissivity of the material changes considerably with the temperature, such as ablation and erosion/oxidation effects, these techniques fail. Dual color thermography is a non contact measurement temperature technique used mainly when the emissivity of surface is unknown. It is based on the ratio of monochromatic emissive power calculated by means of Planck radiation equation and allows a free emissivity temperature measurement of the surface objects [3e5]. For real surfaces, the emissivity varies with the surface temperature as well as the wavelength and the direction of radiation. Dependence of wavelength and direction of radiation can be elided by using a thermal camera provided with two filters. Therefore the crucial factor in this technique is the choice of the two wavelength filters. For many years inferring temperature from measured radiations, coming from the material surface, has been studied. When material exhibits behaviour different from the black body, emissivity compensations need to be performed and assumptions about the emissivity variations such as dependence on wavelength and the temperature, have to be considered. In this work, temperature measurement investigations up to 500
C on the choice of two central wavelength distances by means of dual color thermography technique are reported. In particular a Mathcad numerical simulation, experimentally validated in the Long and Mid - Wavelength (LW, MW) ranges, was developed and used to determine the best filter combinations. Moreover the first experimental attempt to verify the capability of the technique using a commercial LW FLIR camera (A655) was not satisfactory, while the experimental attempt using a commercial MW FLIR camera (SC5500) provided good results. In such a way to perform experimental verification of the detected couple of filters, a temperature measurement on an aluminium plate, heated by means ceramic heating device, was carried out. The SC5500 was previously calibrated using a blackbody device emitter for three band pass filters: 3.80, 3.90 and 3.97 mm. Since good results can be obtained for a target that exhibits a grey body or near grey body behavior, the filters selection was carried out in order to obtain the condition as the most valid possible. At the same time a good sensitivity in the ratio signals collected through the two filters, in function of the temperature, is required. This thermal camera, in contrast to the LW A655 camera used, is provided of a drum that can accommodate up to 4 filters which can be switched from one to another in a tenth of second. The surface plate temperature measured by IR camera by means of two narrow spectral band filters have been compared with ones measured by four K-type thermocouples positioned around the area focused by the camera. The results show that this innovative measurement technique allows measuring the surface temperature with an error lower than 5% in MW range, when appropriate narrow wavelength filters are adopted. In addition the numerical model was used to analyse the behaviour of the two colour technique for different materials in MW spectral range showing errors in temperature measurement lower than 10% of the real value in most cases.

2. Mathematical model The thermographic temperature measurement approach is based on the detection of monochromatic directional intensity of radiation E l ðεobj ; T obj Þ emitted by an object surface (with a temperature T obj and a directional emissivity εobj ). The spectral density of radiance emitted from the surface is given by Planck distribution function (eq. (1)):

329



) 
 E l εobj ; T obj ¼ εl 4 ; l; T obj E nl T obj
)  C1 ! ¼ εl 4 ; l; T obj

l5 exp

C2 lT obj

!

(1)

1

where -

C1 ¼ 1.191108 Wmm4m2sr1 (Planck radiation constant) C2 ¼ 14388 mm K (Planck radiation constant) ) 4 , direction of radiation El Enl , black body monochromatic directional intensity of radiation (Wmm1m2sr1)

Dual color thermography allows the calculation of the ratio of two monochromatic radiations evaluated from two spectral band filters with central wavelengths close to each other. The object surface temperature is determined by the ratio of the measured intensity radiation, obtaining the Intensity Radiation Ratio (IRR) value (eq. (2)):


.

 IRR li ; lj ; T obj ¼ εli E n;li T obj ε E lj n;lj T obj

(2)

If the two wavelengths are close to each other, the εli yεlj approximation can be carried out in such a way to obtain eq. (3):


.
IRR li ; lj ; T obj ¼ E n;li T obj E


n;lj

T obj



(3)

In the actual condition to obtain accurate temperature measurements, an evaluation of all the approximations related to the measurement method is needed. Therefore, it is necessary to analyze the signal contribution of the reflected radiation of the external environment and the behavior influence of a non-gray body object. In addition to these theoretical aspects based on the radiation laws, practical applications of this method require a discussion of additional parameters related to the thermal camera such as spectral sensitivity, spectral behavior of the filter, signal to noise ratio and calibration process when filters are used. In order to find the best conditions for the applicability of the dual color method, all these aspects have to be known. According to the author's knowledge, the two most theoretical aspects that affect the accuracy of temperature measurements are reported in the following: 1) The camera receives radiation not only from the focused object, but also from the reflections of the surrounding objects. Both these radiations are attenuated in a certain degree from the atmosphere that is present along the measurement path, where, the atmosphere contribution itself has to be considered as well (Fig. 1). The radiation coming from sunlight and scattered by the atmosphere as well as the radiance from the intense radiation sources outside the field of view are small enough to be neglected [6]. Considering all thermal energy that reaches the IR sensor, the spectral radiance impinging the camera sensor can be written:





E inc;l l; εobj ; T obj ¼ εobj;l l; T obj tatm E n;l l; T obj þ 1
  εobj;l l; T obj tatm E n;l ðl; T env Þ þ ð1  tatm ÞE n;l ðl; T atm Þ

(4)

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Fig. 1. Radiative contributions on thermal-camera.

where En;l is the monochromatic spectral black body emissive power, T env is the environment temperature, tatm is the atmosphere transmission coefficient, E atm;l is the spectral radiation emitted by the atmosphere at temperature T atm . Since the influence on the measurement of the atmosphere transmission is negligible, tatm is considered equal to 1, besides when T atm ≪T obj and T env ≪T obj , the 2nd and 3rd term in the second member of eq. (4) can be neglected in such a way to express IRR as eq. (3). 2) The filters wavelengths li and lj should be chosen as close as possible to consider valid the approximation of grey body, but not so close, since the signal ratio derivative decreases with the decrease of li and lj differences. Therefore a good compromise on this choice is needed. In paragraph 4 a detailed analysis for the choice of filters in order to satisfy the explained conditions is described.

3. Dual color thermography technique: LW range 3.1. Numerical simulation In order to determine the best pair of filters needed for the application of the dual color thermography technique, a numerical tool simulation, elaborated with Mathcad code which is able to predict and replicate the experimental behaviors was used. In particular the first analysis was focused to verify the possibility to use this technique in LW range (7e13 mm) reproducing numerically the behavior of the FLIR A655 commercial camera [8]. In the wavelengths range ½l1 ; l2 , at temperature T, the black body emissive power is written as:

Zl2 E n ðTÞ ¼ l1

l5



2phc2    dl hc exp kT  1 l



. W m2 sr

 (5)

and the radiance collected by the camera detector is written as:

Zl2 Gn ðTÞ ¼

RðlÞ* l1

l5



2phc2    dl hc exp kT  1 l



. W m2 sr

 (6)

where R(l) is the analytical function of the camera response curve. Furthermore if F1 ðlÞ and F2 ðlÞ are respectively the transmissivity curves of the two filters; the infrared radiation (Gn;1 ðTÞ and Gn;2 ðTÞ)

emitted by the source (black body in this case) that reaches the detector camera when filters are applied, are evaluated as:

Zl2 Gn;1 ðTÞ ¼

F1 ðlÞ*RðlÞ* l1

l5



2phc2    dl hc exp kT  1 l



. W m2 sr



(7) Zl2 Gn;2 ðTÞ ¼

F2 ðlÞ*RðlÞ* l1

l5



2phc2    dl hc exp kT  1 l

  . W m2 sr (8)

from eqs. (7) and (8) the signal ratio SR(T), Gn;2 ðTÞ/Gn;1 ðTÞ, can be determined as a function of temperature T. The reliability of the model was verified through the camera calibration in the 100e650
C selectable temperature range, obtained with Mikron M305 black body (ε ¼ 0.995) [11]. On the right side of Fig. 2 a comparison between the simulated Gn(T) and the experimental Object Signal (OS) data (that is Flir Research IR software output) is shown where no filter was applied in front of the camera. The simulated model is able to reproduce the experimental results with a maximum error of about 3%. Moreover the first attempt, using the dual color technique, was carried out with two SPECTROGON filters, BP-10400-737 and BP-10500-775 [7], applied in front of the FLIR A655 camera [8]. Filter features are indicated in Table 1. The choice was connected to the decision to use two band pass filters, within the camera working range, centered at wavelength for which is present a good camera response and so close to each other to keep as much as possible the grey body hypothesis valid (the difference of central wavelength is about 0.01 mm). The wide filter band width was preferable in LW range (since the emitted radiation is reduced respect to the MW range), in such a way to obtain a good Signal to Noise Ratio (SNR) when the radiation is coming from higher temperatures (from 300 to 650
C the optimized l is already about 4e5 mm on the bases of the Wien law). The Mathcad model allows the preliminarily identification of the ratio between radiations collected by the sensor when filters are applied (Gn;1 ðTÞ and Gn;2 ðTÞ). Theoretical curve of signal ratio (SR¼ OS2/OS1, where OS2 and OS1 represent the radiative power indicated as object signals (to be coherent with Flir Research IR software output “nomenclature”) detected by camera when filter2 and filter1 are respectively applied). Fig. 3, shows a monotonic

L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

331

Fig. 2. On the left the Flir A655 spectral response curve [8], on the right comparison between the radiation experimental trend emitted by a black body (circle red points) and the simulated one in function of the temperature (100e650
C range). Object signal range was 360e5000 W/m2Sr for experimental data and the simulated model is able to reproduce the experimental results with a maximum error of about 3%. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Table 1 LW filters specification. Model

Central Wavelength

Spectral width

SPECTROGON BP 10.400 mm Filter1 (OS1) SPECTROGON BP 10.500 mm Filter2 (OS2)

10.454 mm 10.464 mm

0.685 mm 0.685 mm

trend which allows to associate uniquely, each ratio value, to one temperature value. The area delimited between the upper and lower limit curves corresponds to a theoretical uncertainty of ±2% of the temperature value (i.e. curves are relative to SR(T), SR(Tþ2% T) (lower limit) and SR(T-2%T) (upper limit)). An experimental analysis was performed to test the quality of the technique in LW spectral range. 3.2. Model validation and first dual color attempt in LW range The first experimental attempt of the dual color application technique has been performed by using two SPECTROGON filters,

Fig. 3. Ratio (SR¼ OS2/OS1) between signals determined with Mathcad model associated to the couple of filters (BP10.500 and BP10.400 mm) in function of the temperature.

BP-10400-737 (indicated with OS1) and BP-10500-775 (indicated with OS2) series (see Table 1 for filters features), applied in front of the FLIR A655 camera equipped with a microbolometric detector. The camera does not contain an internal wheel to support and switch between two filters, hence an external wheel was used. On left part of Fig. 4, the object signals (OS1, OS2) experimental trends (that represent the radiance in W/m2sr coming from black body) as a function of the temperature are shown. The calibration data have been collected with the MIKRON M305 black body [11] from 100
C up to 625
C with a step of 25
C. On the right of Fig. 4, the SR (OS2/ OS1) trend (i.e. calibration curve to be used in dual color technique) in function of the temperature has been also reported. It is understandable, from the right side of Fig. 4, that with this configuration and with this camera, the ratio between the object signals are not useful to extract a unique temperature value for a given ratio (i.e. signal ratio OS2/OS1 is not univocally associated to temperature). For any of single filters applied, experimental data have been compared to the theoretical ones obtained through eqs. (7) and (8) implemented in Mathcad using the spectral response curves of filters indicated in Table 1 and spectral response curve of camera (Fig. 2 on the left). Despite the fact that the experimental data were collected at standard environment temperature condition (Tenv ¼ 20
C), much lower than black body temperature, and filters have been brought as much as possible close to the camera to avoid external environment reflection, the comparison between experimental and numerical data showed that signal ratio was affected significantly by this phenomenon (i.e. environment reflection). Matchad simulation tool has been used to determine the mean amount of reflection due to the external environment (corresponding to the offset between the two curves represented in Fig. 5). The Mathcad simulation hence allows to subtract the mean amount of reflection to the single OS, making the ratio between the two signals deprived from the reflection amount. Moreover, despite the subtraction to the detected radiation of the calculated reflection contribution an even bigger SR experimental ratio oscillation around the theoretical expected curve is still observed, Fig. 6. Hence the differences between experimental and Mathcad theoretical data (Fig. 6) are mainly due to the OS oscillations, for each acquisition, related to the camera sensitivity and black body stability. For this purpose a dispersion analysis has been carried out and for SR is

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L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

Fig. 4. On the left the experimental OS (OS1, OS2) trends in function of the temperature and, on the right the experimental ratio curve (SR¼ OS2/OS1). Object signal range was 150e600 W/m2sr.

Fig. 5. A comparison between Matchad simulation and experimental OS associated to the filters (BP10.400 mm) is shown, see text. Object Signal range is between 150 and 590 W/m2sr. That means a Raw Count (i.e. the digital output of RIR research pro software by FLIR) range between 15000 and 45000 counts for experimental data. Object Signal range is 30e470 W/m2sr for theoretical data. The offset (corresponding to the background radiation reflected by the filter) was 120 W/m2sr on the average.

obtained:

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2  2  DSR ¼ vSR=vOS *DOS 2 þ vSR=vOS *DOS 1 2

1

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi !2 u 2 u . t 1 DSR ¼ þ  OS 2 OS 2 *DOS 1 =OS 1 *DOS 2 1

(9)

(10)

Since the wavelength of the filters are close to each other, one can assume that OS1z OS2 z OS and DOS2 z DOS1 z DOS:

pffiffiffi

DSRy 2 DOS=OS

(11)

So one has

SR  DSR  SR  SR þ DSR

(12)

Fig. 6. Experimental signal ratio, obtained from the experimental OS data depleted of the mean amount of the estimated reflection. Its dispersion is mainly due to the camera sensitivity and black body stability. The theoretical values with its limits are shown as well, see text.

From the measurements performed in the 100e650
C range, it has been observed an OS sensibility on the last digit which oscillates of ±0.5 count (i.e. DOS z1) when temperature is 400
C (corresponding to OS z 250 W/m2sr). Assuming for simplicity, a constant ratio DOS/OS with temperature, the DSR can be deduced from eq. (11) and a theoretical band of dispersion can consequently be represented, Fig. 6. In Fig. 6 is shown that experimental data are confined into the area delimited from the blue (upper limit) and purple (lower limit) curves representing the predicted theoretical dispersion calculated from eq. (11), confirming that dispersion was mainly due to the camera sensitivity and black body stability. A solution to reduce the influence of the dispersion due to uncertainty on the OS, could consist in incresing the sensitivity (i.e. the slope) of the SR curve as function of the temperature. Furthermore the central wavelength of the two filters has been departed of one order of magnitude, from 0.01 mm to 0.1 mm. For this purpose two filters with a response curve centered at a distance of about 0.1 mm (centered at 10.400 mm e 10.500 mm) were mainly analyzed. The trend of the ratio is reported in Fig. 7.

L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

333

Fig. 7. Left - Normalized numerical SR trend for the couple of filters centered at 10.454 mm and 10.464 mm and centered at 10.400 mm e 10.500 mm. Right - area of dispersion referred to the couple 10.400e10.500 mm.

On the left side of Fig. 7 is shown how the signal ratio curve becomes more sensitive with temperature (going from red to the black curve) but that despite this effort, the theoretical dispersion of data due to OS oscillations, on right side, are excessive for a good determination of the temperature (a big width of band on the right side of Fig. 7 can be observed). The analysis carried out shows the limitation that prevents the use of dual color in LW range (for a maximum difference of 0.1 mm between central wavelengths of filters). Moreover increasing of another order of magnitude can be excessive to keep the grey body hypothesis. So an analysis to investigate the use of this technique in the MW spectral range has been performed.

4. Determination of a suitable couple of filters working in MW by numerical analysis Through the Mathcad tool, simulations to investigate both the possibility to implement the technique in MW range and to detect the best couple of filters has been carried out. A cooled IR camera with an internal wheel support for filters has been chosen, in such a way to remove the radiation reflected contribution. FLIR SC5500, used for this aim, can perform measurements with and without spectral filters: it is furnished with a rotating drum which accommodates up to four different filters. For this camera, differently from FLIR A655, also the integration time can be modified and the output value of the Digital Level (DL is proportional to the radiation coming from the body) with an uncertainty of 1 per mill (DDL z 1 for DL ¼ 1000) was observed. Hence, assuming, as done for eqs. (9) and (10), SR ¼ DL2/DL1, DL1z DL2z DL and DDL2z DDL1z DDL, the DSRðTÞ value is:

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2  2  DSRðT Þ ¼ vSR=vDL DDL2 þ vSR=vDL DDL1 2

1

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi !2 u 2 u . þ  DL2 DL2 DDL1 ¼ t 1=DL DDL2 1 1 pffiffiffi pffiffiffi ¼ DDL=DL 2 ¼ 0:001* 2z0:001

(13)

Furthermore since DSRðTÞ is the uncertainty on SR and if a t % accuracy is required on the T value ðDT  t%TÞ, by approximating DSRydSR and DTyvT, the following relation has to be satisfied for

each value of T:

vSRðTÞ=vT  0:001=t% T

(14)

This means that when SR (T) for a given pair of filters satisfies eq. (14), a relative uncertainty of about 1 per mill on the DL can be associated to an uncertainty less than t % in the temperature reading value. In order to obtain a good SNR a reference filter has been centered at 3.99 m, (i.e. at a medium point of the response curve, a wavelength shifted to the left side of the working spectral range (Fig. 8, left side) is associated to a low response of the detector, while using a value chosen on the right side of spectral working range would give a reduction in sensitivity of signal ratio, besides a fast drop in the detector response in that region can be observed). In other words, fixing a filter centered at 3.99 mm, to obtain a 2% (t ¼ 2) uncertainty on temperature, the second filter must be chosen in order that the derivative of SR(T), obtained from the ratio between eqs. (7) and (8), satisfies eq. (14). Moreover the distance between the wavelengths should be held as minimum as possible to keep the grey body hypothesis. In this case the RðlÞ camera response curve in eqs. (7) and (8) is referred to the FLIR SC5500 and the filters (F 1 ðlÞ and F 2 ðlÞ in eqs.(7) and (8)) to MW range, fixing one at 3.990 mm and varying the second. Graphically this corresponds to consider curves with minimum filters distance above the hatched one, representing the 2% of temperature T, Fig. 8 right side. The figure on the right shows that 0.1 mm distance is the minimum value that seems to satisfy the condition represented by eq. (14) up to about 900
C (i.e. black line is the first curve above the dashed line). In addition in Fig. 9 is also reported the theoretical SR values (as well as the upper and lower curves) obtained with MathCad simulation code. The ratio dispersion area, in the MW case, is very small (Fig. 9) and useful to determinate the temperature value for the pair of filters centered at 3.90 mm and 3.99 mm. For this purpose three filters have been acquired, working at central wavelength 3.80 mm, 3.90 mm, 3.97 mm (since the 3.99 mm filter was not commercially available). 5. Dual color thermography technique: MW range The detailed results for the MW Mathcad simulation model validation are reported in an accompanying paper [5]. In this section both the main results, in such a way to be compared with those

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L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

Fig. 8. On the left Flir SC5500 spectral response curve [8], on the right numerical values of the SR derivatives for different couple of filters working in MW range, fixing one filter at 3.99 mm. The lower hatched one is the 2% reference value and all the others the values obtained increasing the distance between filters.

Fig. 9. Mathcad numerical signal ratio trend for the couple of filters centered at 3.99 mm and 3.90 mm and the upper, SRðTÞ þ DSRðTÞ, and lower, SRðTÞ  DSRðTÞ, curves due to the camera sensitivity and black body stability.

obtained at LW range, and the experiment by means the dual color technique are discussed.

Fig. 10. Comparison between analytical digital level DLa ¼ k  Gn;3:80 ðTÞ (red curve) f and experimental values DL 3:80 ¼ DL3:80  DL0 (black curve) for filters centered at 3.80 mm . In particular the factor k ¼ 26.8, for filters centered at 3.80 and 3.90 mm when 60 ms was chosen as integration time, while k ¼ 57 for filters centered at 3.80 and 3.97 mm when 130 ms was set as integration time. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

5.1. Model validation and experimental calibration Briefly further validation on the Mathcad model implemented to detect the appropiate pair of filters has been possible in MW f ) obtained through spectral range using the experimental data (DL i the FLIR SC5500 camera calibration. Through eqs. (7) or (8) multiplied, in this case, by a factor which takes into account the integration time and the camera electronics, one obtains the analytical expression (DLa ¼ k  Gn;i ðTÞ) of the experimental data (K was f ) and simply deduced by ratio between experimental ratio(DL i theoretical data Gn;i ðTÞ ). An example, obtained for the 3.80 mm filter is shown in Fig. 10. Also in this case, as for the LW range (Fig. 2 on the right), the model reproduces the experimental results with a maximum error of 3%, confirming its attendance. Going slightly more into the calibration details, the infrared radiative sensor produces an electric output proportional to the radiative power El ðεobj ; T obj Þ. The signal output coming from an object, obtained from the sensor, can be expressed and fitted by the semi empirical adaptation of Planck law [9], eq. (15):


f l; ε ; T DL obj obj ¼ εobj

R ! . exp B T F obj

(15)

where R, B and F are the characteristic parameters of the filter determined by calibrations. The experimental digital level data f ), furthermore, has been purged of a DL0, which represents the (DL i rate of signal generated by spurious electronic noise. It can be determined by framing with the camera a target at temperature below the threshold of the sensitivity of its detector (i.e. at environment temperature when camera integration time is set to obtain measurement at “high temperature”). The calibration was performed for two pairs of band pass filters 3.80e3.90 mm and 3.80e3.97 mm respectively with a MIKRON M305 black body device with known emissivity ε ¼ 0.995 [11]. Moreover in general after the calibration phase in the measuring phase when Tobj is known, by

L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341 Table 2 MW filters specification. Model

Central Wavelength

Spectral width

Spectrogon BP-3970-116 nm Spectrogon BP-3800-180 nm Spectrogon BP-3900-200 nm

3.977 mm 3.810 mm 3.900 mm

116 nm 180 nm 200 nm

reversing the relation (15), for any of the two filters, it could be possible to obtain εobj :


 εobj T obj ¼


. f l1; ε ; T exp B T DL obj obj obj R1

!

!  F1 (16)

In this study three SPECTROGON filters have been used: BP3970-116, BP-3900-200 and BP-3800-180 nm [7], Table 2. Spectral widths have been chosen in order to work in the temperature range 100e650
C. The possibility to use different integration times assures a good SNR in calibration phase. In particular an integration time of 130 ms was used for 3.80e3.97 mm couple and 60 ms for 3.80e3.90 mm. The integration time was chosen in order to obtain, at higher temperature in calibration phase, a value close to the detector saturation. Moreover for temperature determination by means of the dual color technique is necessary to calculate the SR obtained with the two filters, in such a way to elide the emissivity function of the surface material. The calibrations were performed in the range f value with a step of from 50
C to 500
C, by measuring the DL i


50 C up to 300 C and with a step of 25 C from 350 to 500
C, for both couple of filters. Third degree polynomial functions (eq. (17)) are chosen to model analytically trend of SR with temperature (i.e. calibration curve to be used in dual color technique), since they well fitted the experimental data (Fig. 11, right side).

T ij ¼ D þ C SR þ B SR2 þ A SR3

(17)

f experimental values and semi Comparison between DL i f empirical Planck fit DLðl; εbb ; Tbb Þ data for l ¼ 3.90 mm are shown on the left of Fig. 11, while comparison between SR experimental value for 3.80e3.90 mm couple and its polynomial fit, are showed on the right part of the figure. As can be deduced, right side of

335

Fig. 11, in the MW range case, a regular curve of the SR has been obtained differently from LW range, right side of Fig. 11 (compared with Figs. 6 and 7), proving that in the MW the technique can be implemented for a filter distance of about 0.1 mm (it is referred to the couple 3.90e3.80 mm filters). In the same way calibration curves and signal ratio curves for the 3.80e3.97 mm pair, have been determined. In the Table 3 calibration parameters of the filters corresponding to two calibration times (130 ms and 60 ms) have been reported, while coefficients of the signal ratio fitting curve (eq. (17)) are indicated in Table 4: By comparing Figs. 5 and 11, a significant offset between experimental data and theoretical ones can be observed for uncooled Flir A655 (working in LW range, Fig. 5), while this offset is completely absent in analysis made with Flir SC 5500 (Fig. 11, right). For LW uncooled camera an external wheel was necessary to support filters (Fig. 12, left). Consequently the environment radiation reflected by filter at the external range of its transmissivity range can not be neglected and has been deduced from comparison between experimental and numerical data (see Fig. 5). For MW cooled camera (Fig. 12, right) the amount of radiation reflected by filter is absolutely negligible, relative to the direct one, since the main source reflected by filter is given by the cooled detector (in this case with a stirling cooling system) negligible relative to the direct radiation. 5.2. Dual color experimental results In order to evaluate experimentally thermographic dual color measurements through the pairs of the specific filters chosen (3.80e3.90 mm and 3.80e3.97 mm), the authors have performed an experimental verification in which the temperature of aluminum plate, heated by means of ceramic heating device, was simultaneously measured both with a thermal camera and with K-type thermocouples. 5.2.1. Experimental set up A ceramic heating plate “Velp Scientifica” REC model [10] was used to realize the experimental validation. The heating plate was set at a temperature value equal to 500
C and the effects of reflected radiance were neglected. To test the dual color technique, a treated square plate with a side of 100 mm and 5 mm thick, made of

f Fig. 11. On the left the trend of purged digital level DL 3:90 in function of temperature during calibration made with filter centered at 3.90 mm (black square points) and semi f empirical Planck adaptation fit DLð3:90 mm; εbb ; Tbb Þ (red circle points). On the right SR experimental value for 3.90e3.80 mm couple (black square points) with its polynomial fit f (red circle points). Digital level DL (digital output deprived of offset value DL0 of Altair by Flir); range is 80e12500 counts. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 12. On the left a scheme representing the reflected radiation when an external wheel is used for uncooled camera, while on the right the scheme is relative to the reflected radiation for an internal wheel when cooled camera is used.

Table 3 Thermocamera calibration coefficients and DL0.

l (mm)

IT (ms)

R

B

F

DL0

3.97 3.80 3.90 3.80

130 130 60 60

1697090.00 3270110.00 1444450.00 1460100.00

3587.09 3757.59 3667.81 3732.06

2.26 0.55 1.16 0.26

1048.38 1023.98 810.37 773.88

rough aluminum alloy, was used as target surfaces, Fig. 13. To validate the results obtained during the experiments and to calculate the target emissivity, four K thermocouples (Chromel (NiCr) (þ)/Alumel (Ni-Al) ()) were used. The thermocouples were characterized by a wide temperature range, 200e1260
C, with a sensitivity of 41 mV/
C. The temperature regulation system of the ceramic heating plate, monitored using a Luma Sense Technologies dual-color pyrometer ISR 12-LO [11], causes a mean temperature oscillation over time of about 6% of the set temperature value (in this case 400
C). The thermocouples are characterized by an accuracy of 0.75% of the reading value [12]. The measured temperature values of the four thermocouples had a standard deviation of less than 1% of the average value, guaranteeing spatial uniformity for temperature distribution. The average values measured by thermocouples, considered in Table 5 (Tc) as reference, have been considered with an accuracy of ±2% that takes into account both the accuracy of the single thermocouple and the standard deviation of the different measurements. Data acquisition consisted of a Ceam VR 18 system [13]. The radiation coming from air near the plate heated through convection effect is completely negligible since this term is directly proportional to (1-t) where t, transmissivity of air in the spectral region of interest (3.8e3.9 mm), is near to 1 [3]. The FLIR SC5500 research camera [8], was used to acquire the dual color temperature on a 20  20 pixels square matrix (see Fig. 14). This thermal camera is provided of a drum that can accommodate up to 4 filters and it can switch from one filter to another in a tenth of a second. Two pairs of pass band filters, 3.80e3.97 mm and 3.80e3.90 mm wavelengths, were used. The Fig. 15 shows the filter transmittances and overlap zone.

To calculate the dual color temperature of the targets it was necessary to reproduce the same conditions set during the calibration of the thermocamera. The thermocamera was positioned orthogonally to the target at 60 cm away from it. The thermographic signal acquisition was started when a stationary regime was achieved, with a duration of 4 s and composed of 201 frames. During the acquisition, the drum switched from one of the two filters to the other one and, at the same time, the temperatures of the thermocouples were revealed through the VR18 data acquisition system, in order to calculate the average temperature.

5.2.2. Results and discussion In the first case study the 3.80e3.97 mm wavelengths were used, while in the second one 3.80e3.90 mm. In Table 5 the SR calculated from DLs, the dual color temperature (Tij) computed by eq. (17), the “true” reference temperature measured by thermocouples and the relative temperature (Tc) percentage deviation are reported. Since the surface objects temperature was measured by the thermocouples, it was possible to calculate the surface spectral emissivity as well, Table 6, for each wavelength by means eqs. (18) and (19) for the first test (1) and eqs (20) and (21) for the second test (2).

    . f exp B  F ε3:97ð1Þ ¼ DL 3:97 R 3:97 T 3:97 average 3:97

(18)

    . f exp B3:80 T  F 3:80 ε3:80ð1Þ ¼ DL 3:80 R average 3:80

(19)

    . f exp B3:80 T  F 3:80 ε3:80ð2Þ ¼ DL 3:80 R average 3:80

(20)

  . f ε3:90ð2Þ ¼ DL 3:90 R 3:90 exp B3:90 T

(21)

 average

  F 3:90

where Taverage (K) indicates the average between the temperatures measured by the four thermocouples. To derive the targets emissivity, the DL0 (digital level at room temperature) and the R, B and F of the thermocamera parameters depending on the filter were

Table 4 Polynomial function constant values. Constant values

3.80e3.90 mm 3.80e3.97 mm

A

B

C

D

R-Square

138962.99617 115201.52368

488724.0643 262532.8634

574960.2032 201460.44885

226650.4219 52479.58169

0.99925 0.99757

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337

Fig. 13. On the left, scheme of the Aluminium plate equipped with four k thermocouples used for dual color experimental measurement, and on the right, the aluminium plate heated by ceramic plate.

Table 5 Test results, see text. Test

l (mm)

SR

Tij (
C)

TC (
C)

% ¼ j(TijTC)/TCj

1 2

3.80e3.97 3.80e3.90

0.6704 1.0958

429 341

408.8 ± 8 414.33 ± 8

z4.9 z17.7

necessary (Table 3). A difference in emissivity value at the same wavelength (3.80 mm) has been revealed between the two tests. This is probably due to the change of aluminium surface features after the heating of the plate in the first test (this phenomenon helps to understand how difficult it can be, to set the right emissivity value in a “single

Fig. 14. Upside on left, image in term of DL of the square analyzed for filter 3.97 mm (20  20 pixels, IT ¼ 130 ms) and on the right, down histograms represent the frequency of pixels in terms of DL and Temperature.

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Fig. 15. Transmissivity curves for 3.80e3.97 mm filters (left) and 3.80e3.97 mm filters (right).

Table 6 Emissivity values, see text. Test

l (mm)

1 2

3.80e3.97 3.80e3.90

ε3.97 ¼ 0.3094 ε3.90 ¼ 0.2070

ε3.80 ¼ 0.3069 ε3.80 ¼ 0.2047

color” mode, that instead, represents the state of the art technique in temperature measurements when material emissivity is known and changes in its value are minimal). For the first test (3.80e3.97 mm) with Dl ¼ 0.17 mm, the experimental percentage error (evaluated as the ratio between the difference of the dual colour temperature and the thermocouples temperature measurement over the thermocouples temperature measurement) is about 5%. For the second test (3.80e3.90 mm) with Dl ¼ 0.10 mm, the experimental percentage error increases and it corresponds to about 18%. In this case the error is not due only to the local grey body hypothesis (ε3.90 ¼ 0.2070, ε3.80 ¼ 0.2047), but also to the two closer bandwidths having DL signals which are very similar. Therefore, the SR sensitivity decreases and, consequently, increases the measurement error. Hence this effect can be predominant respect to the grey body hypothesis validity. Once the dual color temperature has been determined, eqs (18)e(21) can be used to obtain surface emissivity estimation values. Of course the emissivity values at two wavelengths are similar since the wavelengths used for dual color technique are very close. Using a wheel capable to host different narrow filters centered at different wavelengths and collecting signals coming from the same target at the same temperature, it would be possible to obtain emissivity wavelength trends by eq. (16). Of course one pair of filters could be centered as close as possible to perform the dual color technique, while the others could be used to extract emissivity information at different wavelengths. Notice that non stationary phenomena are possible, so that a wheel rotating as fast as possible would be necessary in order to obtain measurement through different filters for which temperature could be considered constant at adjacent frames.

6. Error analysis for different materials The Mathcad numerical tool, validated experimentally, allows an estimation of dual color technique for different materials whose emissivity trend with wavelength was provided by literature and

compacted into three main areas: ε < 0.3, 0.3 < ε < 0.8 and ε > 0.8. In Tables 7 and 8 the results are determined simulating the FLIR SC5500 camera equipped with two filters: BP-3800-180, BP-3970200 nm, having observed for this pair of filters from the experimental analysis a good compromise between grey body hypothesis satisfaction and sensitive trend of SR. In this case the expression used to obtain the SR for the two filters, hence the “real” temperature, takes into account also the trend of emissivity with wavelength [14e16]:

Zb G1 ðTÞ ¼

εðlÞ*F1 ðlÞ*RðlÞ*

2phc2 h hc i dl 5 l ekTl  1

εðlÞ*F2 ðlÞ*RðlÞ*

2phc2 h hc i dl l5 ekTl  1

a

Zb G2 ðTÞ ¼ a

SRε ðTÞ ¼ G1 ðTÞ=G ðTÞ 2





W m2 sr

W m2 sr

 (22)

 (23)

(24)

SRε associated to a real temperature (Treal) is deduced from eq. (24) (Fig. 16, blue line), and is associated to the calibration curve (deduced from ratio between eqs. (7) and (8) implemented in Mathcad code) in order to obtain the two color measured temperature (Tdual in Fig. 16, red line). Analysis were conducted for two virtually measured dual color temperature values, 100
C and 500
C, in order to analyze the behavior, for seven types of material with emissivity that varies from low values (ε < 0.3) up to high values (ε > 0.8) and for pair of filters centered at 3.80e3.97 mm, in order to obtain information about the methodologies in the used range. For simplicity the trend of emissivity was obtained for each material at a reference temperature, but applied for different temperature in numerical model. Curves represented in Fig. 17 just give an indication of sensitivity of emissivity with wavelength for different materials. Results show how in MW range errors are limited relative to those obtained when emissivity is totally unknown; a maximum error of about 28% has been revealed while less than 5% for materials with high emissivity are obtained. In the dual color signal ratio SR(T) (Tables 7 and 8), the uncertainty DSRðTÞ due to the sensitivity of the camera is considered from eq. (13) and propagated on the real effective temperature. Treal is associated to Tdual color measured (i.e. when a dual color temperature measurement X is obtained, it is related to a signal ratio SR þ

L. Savino et al. / International Journal of Thermal Sciences 117 (2017) 328e341

339

Table 7 Numerical results for different materials in MW (couple 3.80e3.97 mm at 100
C). Type of material

Tdualcolor
C

Treal
C

DT K

abs[(TdualTreal)/Treal*100)] %

SRðTÞ ¼ Gn;3970 n;3800

POLISHED ALUMINIUM (ε < 0:3), Fig. 3 dotted line in Ref. [14] ROUGHENED ALUMINIUM (ε < 0:3), Fig. 4 dotted line in Ref. [14] ANODIZED ALUMINIUM (ε < 0:3), Fig. 5 solid line in Ref. [14] VO2/CaF2 (0.3 < ε < 0.8), Fig. 2 red dotted line in Ref. [15] C/SiC (0.3 < ε < 0.8), Fig. 1 square mark in Ref. [16] GRAPHITE (ε > 0:8), Fig. 2 square mark in Ref. [16] SiC (ε > 0:8) Fig. 3, square mark in Ref. [16]

100.0 100.0 100.0 100.0 100.0 100.0 100.0

78.1 ± 1,0 89.9 ± 1,0 121.4 ± 1,1 99.5 ± 1,1 73.2 ± 0,9 104.7 ± 1,2 98.5 ± 1,0

21.9 10.1 21.4 0.5 26.8 4.7 1.5

28 11,2 17,6 0,5 36,6 4,5 1,5

0.821 0.821 0.821 0.821 0.821 0.821 0.821

± ± ± ± ± ± ±

G

3970 SRðε; TÞ ¼ G G3800

0.001 0.001 0.001 0.001 0.001 0.001 0.001

0.799 0.811 0.840 0.820 0.793 0.825 0.819

Table 8 Numerical results for different materials in MW (couple 3.80e3.97 mm at 500
C). Type of material

Tdualcolor
C

Treal
C

POLISHED ALUMINIUM (ε < 0:3), Fig. 3 dotted line in Ref. [14] ROUGHENED ALUMINIUM (ε < 0:3), Fig. 4 dotted line in Ref. [14] ANODIZED ALUMINIUM (ε < 0:3), Fig. 5 solid line in Ref. [14] VO2/CaF2 (0.3 < ε < 0.8), Fig. 2 red dotted line in Ref. [15] C/SiC (0.3 < ε < 0.8), Fig. 1 square mark in Ref. [16] GRAPHITE (ε > 0:8), Fig. 2 square mark in Ref. [16] SiC (ε > 0:8), Fig. 3 square mark in Ref. [16]

500.0 500.0 500.0 500.0 500.0 500.0 500.0

409.4 455.8 598.3 497.9 390.0 520.5 492.9

± ± ± ± ± ± ±

3,8 4,4 6,2 5,0 3,6 5,3 4,8

DT K

abs[(TdualTreal)/Treal*100)] %

SRðTÞ ¼ Gn;3970 n;3800

90.6 44.2 98.3 2.1 110.0 20.5 7.1

22,1 9,7 16,4 0,4 28,2 3,9 1,4

0.656 0.656 0.656 0.656 0.656 0.656 0.656

± ± ± ± ± ± ±

G

3970 SRðε; TÞ ¼ G G3800

0.001 0.001 0.001 0.001 0.001 0.001 0.001

0.638 0.648 0.671 0.656 0.634 0.660 0.655

equation (22)). Setting an emissivity of 0.40, the same radiance would be instead obtained at about 650
C giving an absolute temperature difference of 150
C, while dual color technique gives, as indicated in Table 8, an absolute difference of about 7
C. In order to obtain the same difference (7
C, i.e. 493
C) as reported in Table 8 in standard mode an emissivity value of 0.92 should be set, and for a set value of 0.96 a difference of 15
C (i.e. 485
C) would be obtained. So the emissivity value should be known with high precision in order to obtain a lower error in the case described. 7. Summary and outlook

Fig. 16. A simple representation of the method used to extract the dual color temperature from an assigned real temperature, see text.

DSR that will correspond to a real temperature Y± DY, where in turn DY is due to the signal ratio uncertainty DSR due to the camera sensitivity and black body stability in calibration phase). For the low temperature values (100
C), the technique can be applicable only when background reflected radiation can be predicted and separated from direct radiation since, just in this condition, eq. (4) can be approximated to the first term of its second member and so ratio principle can be applied. From Tables 7 and 8, errors by using technique can be deduced. Notice that despite nor negligible errors for some applications, for innovative materials, for which emissive features are completely unknown, dual color technique provides better information in terms of temperature measurement than standard mode thermography with attempt emissivity value. Just in order to give a quantitative idea, if a Sic sample is considered (Fig. 17, right), at a temperature of 500
C with an emissivity of 0.87 (close to the real one, see Fig. 17 on the right), with a filter centered at 3.99 mm with width of 100 nm a radiative power of about 189 W/m2sr would be obtained (by using

In this paper, experimental investigation of the influence of wavelength distance on measurement temperature by means dual colour thermography technique was carried out both in LW range and in MW range. The first attempt performed by using two filters characterized by a distance between central wavelength of 0.01 mm applied in front of a Flir A655 camera (working in LW range) showed limitation due to external reflection (since camera was not provided of an internal wheel to support more than one filter). Mathcad validated numerical tool through comparison with experimental data collected during camera calibration, allowed to predict the amount of reflection and subtract it from the collected data. Anyway the ratio between signals working in this spectral range was too insensitive to be appreciated by the camera (both for a distance between central wavelengths of filters of 0.01 mm and 0.1 mm), for this reason the dual color technique can not be applied in this spectral window (7e13 mm). Investigation continued in MW spectral range. The numerical tool has been used to detect the best pair of filters to be considered in order to obtain an acceptable sensitivity in terms of signal ratio. The following experimental analysis showed that this measurement methodology allows measuring the surface temperature with error lower than 5%, when appropriate narrow wavelength filters with small bandwidths were adopted. The case study involved the use of dual wavelength thermometry by switching between two different band-pass filters, 3.80e3.97 mm and 3.80e3.90 mm. The crucial factor of this measurement methodology has been the choice of the two narrow filter wavelengths.

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Fig. 17. Left: Trend in function of wavelength in a medium-low range of emissivity, Right: Trend in function of wavelength in a medium-high range of emissivity, see text.

- For the first test (3.80e3.97 mm) Dl ¼ 0.17 mm, the percent error, evaluated as the ratio between the difference of the dual colour temperature and the thermocouples temperature measurement over the thermocouples temperature measurement, is equal to 4.9%. In this case the acceptable error is due to the local grey body hypothesis. - For the second test (3.80e3.90 mm) Dl ¼ 0.10 mm, the percent error is equal to 17.7%. In this case the greater error despite a lower distance between central wavelengths of filters is due both to the local grey body hypothesis and to the two closer bandwidths having a DL signals too similar between them and so a low SR sensitivity that increases the measurement error. Once experimentally validated the dual color technique in the range of temperature between 150 and 650
C and in the MW range, the last step was the analysis of dual color technique through the Mathcad numerical model for different materials whose emissivity spectral trends were obtained from literature. The difference between real and dual color temperature is lower than 10% for most of analysed materials (and 5% for high emissivity values). This technique can be useful in contexts where any possibility to use invasive techniques (such as thermocouples) to measure temperature over surface of materials is to be excluded and the emissivity material is unknown: a incorrect setting of emissivity can lead to unacceptable errors of the real temperature measurements. This technique, studied for simplicity for a uniform surface, monitored easily with instruments such as thermocouples which can give temperature measurement considered as reference, can be extended to different pixel of FPA (Focal Planar Array) for surfaces with no uniform temperature in order to obtain free emissivity temperature maps. For a broad spectrum of dual color method experimental verifications, the following steps are planned in the near future: - Verify experimentally the Dual Color method in a higher range of temperature (up to 1500
C) at a range of wavelength (centered at ~ 4 but also around ~ 2 mm) and monitoring a material that, starting from a low emissivity, gradually increases its value. This can be experimentally obtained by bombarding (implanting) 12C ions in a material with low emissivity. The CIRCE [17,18] facility of the University of Campania “Luigi Vanvitelli” would be a suitable laboratory to have this opportunity using the 3 MV tandem accelerator. The CIRCE accelerator

originally equipped for radiocarbon-AMS (12C ions and its isotopes), was upgraded to perform AMS with actinides (238U and its isotopes) ions [19e21] for environmental measurements [22], thus having the possibility of generating ions in the entire periodic table. - Temperature measurement of test article at the CIRA Plasma Wind Tunnel like SCIROCCO and/or GHIBLI through dual color technique implementation in a higher range of temperature (up to 2500
C) at lower wavelength (~2 mm). Acknowledgments This work was supported by PRogramma Nazionale di Ricerche Aerospaziali (PRORA) through the MEtodologie Fisiche Innovative per l’Aerospazio (MEFIA) project. References [1] De Filippis F, Toscano C, Gallo D, Caruso P, Savino L. Influence of mirrors utilization on the radiation emitted by models subjected to hypersonic flow for surface temperature determination. Proceedings of the 11th QIRT Quantitative InfraRed Thermography Conference, Naples (Italy). June 2012. [2] Purpura C, Trifoni E, Musto M, Rotondo G, Della Ragione R. Methodology for spectral emissivity measurement by means of single color pyrometer. Measurement 2016;82:403. €llmann KP, Pinno F, Vollmer M. Two-color or ratio thermal imaging e [3] Mo potentials and limits. Brandenburg University of Applied Sciences, Germany: InfraMation; 2010 [Proceedings]. [4] Hijazi1 A, Sachidanandan S, Singh R, Madhavan V. A calibrated dualwavelength infrared thermometry approach with non-greybody compensation for machining temperature measurements. Meas Sci Technol 2011;22(2): 025106. [5] McLean AG, Ahn J-W, Maingi R, Gray TK, Roquemore AL. A dual-band adaptor for infrared imaging. Rev Sci Instrum 2012;83:053706. [6] Musto M, Rotondo G, De Cesare M, Del Vecchio A, Savino L, De Filippis F. Error analysis on measurement temperature by means dual-color thermography technique. Measurement 2016;90:265. [7] Spectrogon web site, http://www.spectrogon.com/. [8] FLIR web site, http://www.flir.com/. [9] Ianiro A, Cardone G. Measurement of surface temperature and emissivity with stereo dual-wavelength IR thermography. J Mod Opt 2010;57(18):1708. [10] Velp Scientifica web site, http://www.velp.com. [11] LumaSenseTechnologies web site, www.lumasenseinc.com. [12] Omega web site, http://www.omega.com. [13] Dataloggerinc web site, http://www.dataloggerinc.com/. [14] Reynolds PM. Spectral emissivity of 99.70% aluminium between 200 and 540
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