Simulation analysis of uncertainty of infrared camera measurement and processing path

Minkina, W.; Dudzik, Sebastian

doi:10.1016/j.measurement.2006.03.001

Cited by 34 publications

(38 citation statements)

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“…An infrared camera can be also used for acquisition of input data for evaluations of the model parameters in the straight and inverse heat transfer problems [6][7][8]. The value of the measured object temperature can be expressed as a function of five parameters [1,9,10] …”

Section: Passive Thermographymentioning

confidence: 99%

A simple method for defect area detection using active thermography

Dudzik

2009

Opto-Electronics Review

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In this paper a simple method for defect area detection in the subsurface layer of materials was presented. The method uses active infrared thermography. A statistical detectivity ratio was introduced for a quantitative characterization of areas containing defects. The described algorithm of defect area detection was tested for a material with a low thermal diffusivity. The results of experimental and simulation investigations are presented. It was stated that the statistical detectivity ratio can be used to detect regions of defect presence, even for the non-uniformly heated surfaces.

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Section: Passive Thermographymentioning

confidence: 99%

A simple method for defect area detection using active thermography

Dudzik

2009

Opto-Electronics Review

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“…Additional advantage of thermo visual camera is safety of the operator because it is not in direct contact with the hot object. Procedure of taking thermo vision measurements is described in literature [11].…”

Section: Introductionmentioning

confidence: 99%

Thermovision and spectrophotometric analysis of ink volume and material characteristics influence on colour changes of heat treated printed substrates

et al. 2015

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Original scientific paper This paper presents experimental usage of updated control methods such as thermovision and spectrophotometric analysis in graphic industry. These methods were applied to research the influence of ink volume and material characteristics on colour and heat treated printed substrates. Samples used in these experiments were printed by digital ink jet printing technique using Mimaki JV22 printing machine and J-Eco Subly Nano inks. As printing substrates, three different types of materials were used. Materials were different in respect of fabric weight and thread count, while material composition was the same for all three materials. The appropriate test card consisting of fields of CMYK colours was printed, varying the number of ink layers applied. Samples were exposed to heat treatment after printing. The heat applied was measured by thermovision camera. Spectrophotometric measurements were conducted before and after heat treatment. Based on data gathered by spectrophotometric measurements colour difference ΔE76 was calculated. Results showed that increasing number of layers, as well as right choice of substrates, can improve behaviour of printed product during exploitation. Keywords: digital textile printing; heat treatment; ink layers; material characteristics Termovizijska i spektrofotometrijska analiza diferenciranog nanosa boja na specifične podloge izložene toplinskim opterećenjimaIzvorni znanstveni članak U radu su predstavljene primjene suvremenih metoda kontrole, kao što su termovizijska i spektrofotometrijska analiza, u grafičkoj industriji. Suvremene metode kontrole primijenjene su pri istraživanju parametara diferenciranog nanosa boje na specifične podloge izložene toplotnim opterećenjima. Uzorci koji su rabljeni za istraživanje odštampani su Ink jet postupkom na digitalnom tiskarskom stroju Mimaki JV 22 koja koristi J-Eco Subly nano boje. U procesu tiska, rabljene su tri vrste podloga, pri čemu je za sve njih sastav materijala bio isti, ali su se razlikovale prema parametrima površinske mase i gustoće pletenja. Odgovarajuća test karta koja se sastojala od polja CMYK otiskana je s pet različitih nanosa boje. Ti uzorci su izloženi toplinskom djelovanju, pri čemu je polje toplinskog djelovanja mjereno termovizijskom kamerom. Uzorci su analizirani spektrofotometrijskim mjerenjima prije i poslije toplinskog djelovanja te je na osnovu tih podataka određena vrijednost razlike boje (ΔE76). Dobiveni rezultati su pokazali da povećanje broja nanosa boje, kao i odabir odgovarajuće podloge za štampu, može povećati eksploatacijske karakteristike otisaka.

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“…The problem of determination of uncertainty components in thermovision measurement was described in [3][4][5][6]. In this paper the analysis of the measurement method accuracy, based on the coverage interval idea was presented.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper the analysis of the measurement method accuracy, based on the coverage interval idea was presented. In the simulation research, the model described in [4,5,7] was assumed. It can be formulated as a function of five input variables:…”

Section: Introductionmentioning

confidence: 99%

“…This theory allows for the analysis of random interactions, even if the measurement model is strongly nonlinear. According to the theory of uncertainty, the standard uncertainty plays the main role in the accuracy determination.The problem of determination of uncertainty components in thermovision measurement was described in [3][4][5][6]. In this paper the analysis of the measurement method accuracy, based on the coverage interval idea was presented.…”

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confidence: 99%

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Application of the numerical method for the propagation of distributions to the calculation of coverage intervals in the thermovision measurements

Dudzik¹,

Minkina²

2008

Proceedings of the 2008 International Conference on Quantitative InfraRed Thermography

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IntroductionIn the contemporary measurement theory, the new methods of accuracy determination are still investigated. It is possible, that the theory of uncertainty is a universal tool for the estimation of accuracy [1,2]. This theory allows for the analysis of random interactions, even if the measurement model is strongly nonlinear. According to the theory of uncertainty, the standard uncertainty plays the main role in the accuracy determination.The problem of determination of uncertainty components in thermovision measurement was described in [3][4][5][6]. In this paper the analysis of the measurement method accuracy, based on the coverage interval idea was presented. In the simulation research, the model described in [4,5,7] was assumed. It can be formulated as a function of five input variables:where: εob -object emissivity, Tatm -the temperature of atmosphere, K, T0 -ambient temperature, K ω -relative humidity, d -distance between infrared camera and the object, m.In the research of components of combined standard uncertainty, by means model (1), Monte Carlo simulations were used. The expanded uncertainty, with the assumed level of confidence was calculated using the method for the propagation of distributions. The method for the propagation of distributions and Monte Carlo simulationsThe goal of the use the propagation of distributions is the determination of uncertainty, using Monte Carlo simulations. The fundamental purpose of computational procedure is to obtain a statistical coverage interval of the measurement model output variable. It is necessary to emphasize, that the results of calculations are correct, even if the model is strongly nonlinear and the probability density functions of output are asymmetric. This situation takes place in the thermovision measurements.The Common Commitee for Basic Issues In Metrology took this into consideration and worked out "Supplement No.1" entitled "Numerical methods of propagation of distributions" [8]. "Supplement..." deals with evaluation of precision in indirect measurements, with particular emphasis on strongly nonlinear and/or complicated measurement models, like e.g. the processing algorithm of measurement path of an infrared camera. The method of propagation of distributions makes it possible to give a correct estimation of a measurement precision, in particular in the following cases [9]:• the partial derivatives are unavailable, • the distribution of the output variable is not Gaussian, The method for the propagation of distributions evaluates the uncertainties using Monte Carlo method. The principal aim of the computational procedure is to evaluate the statistical coverage interval at a specified confidence level. It is worth to emphasize that the procedure gives correct results even for strongly nonlinear functional relationships of measurement models as well as for assymetric probability dennsity functions of input random variables. The following steps can be distinguished in the evaluation of uncertainty: The method for the propagation of distributi...

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Simulation analysis of uncertainty of infrared camera measurement and processing path

Cited by 34 publications

References 1 publication

A simple method for defect area detection using active thermography

A simple method for defect area detection using active thermography

Thermovision and spectrophotometric analysis of ink volume and material characteristics influence on colour changes of heat treated printed substrates

Application of the numerical method for the propagation of distributions to the calculation of coverage intervals in the thermovision measurements

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