&lt;title&gt;Radiometric calibration of infrared detectors and thermal imaging systems&lt;/title&gt;

Fox, Nigel; Prior, T R; Theocharous, E

doi:10.1117/12.210558

Cited by 3 publications

(1 citation statement)

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“…It was shown earlier that gold-black coated domain engineered LiNbO 3 pyroelectric detectors can be applied for responsivity measurements with about 0.1 % (k=1) responsivity uncertainty in the near infrared range [5]. As increased reflectance in the longer wavelength infrared results in increased nonuniformity of the spatial responsivity [1], reflecting domes are mounted at the inputs to minimize reflection losses [6], [7]. The commercial pyroelectric detectors are used as working standard radiometers to propagate the NIST infrared responsivity scale to different applications.…”

Section: Introductionmentioning

confidence: 98%

Development and calibration of pyroelectric radiometer standards at NIST

Eppeldauer

Zeng

Hanssen

2006

Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense V

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The reference spectral power responsivity scale of NIST is being extended from the silicon range to the infrared (IR) using pyroelectric radiometers. Two transfer standard pyroelectric radiometers have been developed at NIST. The main design consideration was to obtain only a minimal increase in the measurement uncertainty during the responsivity scale extension. Domain engineered LiNbO 3 and regular LiTaO 3 pyroelectric detectors were used in the two radiometers. Both detectors are gold-black coated and temperature controlled. Reflecting domes are attached to the radiometer inputs to decrease the reflectance loss and to improve the spatial uniformity of responsivity in the infrared. Four commercial pyroelectric detectors have been added to the group and used as working standards. The relative spectral responsivity of all pyroelectric detectors was determined from spectral reflectance measurements. The radiant power responsivity tie points were derived from Si trap and single element detectors traceable to the NIST reference responsivity scale. The pyroelectric radiometers have been characterized for frequency and temperature dependent responsivity, noise, spatial non-uniformity of responsivity, angular responsivity, and linearity. The expanded (relative) uncertainty of the spectral power responsivity calibrations ranged between 0.5 % and 1.2 % (k=2) within the 1 µm to 19 µm range.

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Section: Introductionmentioning

confidence: 98%

Development and calibration of pyroelectric radiometer standards at NIST

Eppeldauer

Zeng

Hanssen

2006

Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense V

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Imaging-based thermal modelling and reverse engineering of as-built automotive components: A case study

Sukumar

Govindasamy

Koschan

et al. 2010

Virtual and Physical Prototyping

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Virtual prototyping of objects with thermal characteristic requirements depends on several aspects such as the geometry of the component, material properties, ambient environmental conditions and most importantly temperature curves/heat patterns of the component when functional. In this case study, we present the data acquisition methodology towards thermal modeling of as-built automotive parts into their virtual prototypes. We explain the imaging-based reverse engineering pipeline suitable for our application towards recovering 3D geometry and identify tools for measuring temperature curves in the data collection process. Further, we show results of immersing the reverseengineered mesh in the thermal simulation environment and verify the finite-element based simulation results to agree with the thermal image sequences. Our experimental results based on automobiles are able to address the issue of thermal modeling and verification of virtual vehicle components even when the computer aided design (CAD) models are not available. Finally, we conclude our investigation with the experimental achievability and limitations of imaging-based thermal modeling of vehicle components.

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