Measuring electron density, electric field and temperature of a micro-discharge air plasma jet using optical emission spectroscopy

Abbasi, Hamed; Nazeri, Majid; Mirpour, Shahriar; Farahani, Neda Jalali

doi:10.1109/kbei.2015.7436207

Cited by 4 publications

(1 citation statement)

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“…In addition, they could work with a large variety of light sources in ultraviolet, visible and near-infrared regimes. Similar to normal spectrometers, hyperspectral imaging systems could be used for studying the emission profile of the plasma sources related with different elements or to determine plasma temperature/electron density/electric filed profile [23,24]. A post-processing data analysis is required (either unsupervised or supervised) to bring more power to the initial output of the systems, both qualitatively and quantitatively, they range from simple statistical classification/discrimination methods to advanced neural network-based image processing techniques for multivariate image analysis [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Implementation of webcam-based hyperspectral imaging system

Balooch

Nazeri

Abbasi

2018

Photonic Instrumentation Engineering V

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In the present work, a hyperspectral imaging system (imaging spectrometer) using a commercial webcam has been designed and developed. This system was able to capture two-dimensional spectra (in emission, transmission and reflection modes) directly from the scene in the desired wavelengths. Imaging of the object is done directly by linear sweep (pushbroom method). To do so, the spectrometer is equipped with a suitable collecting lens and a linear travel stage. A 1920 x 1080 pixel CMOS webcam was used as a detector. The spectrometer has been calibrated by the reference spectral lines of standard lamps. The spectral resolution of this system was about 2nm and its spatial resolution was about 1 mm for a 10 cm long object. The hardware solution is based on data acquisition working on the USB platform and controlled by a LabVIEW program. In this system, the initial output was a three-dimensional matrix in which two dimensions of the matrix were related to the spatial information of the object and the third dimension was the spectrum of any point of the object. Finally, the images in different wavelengths were created by reforming the data of the matrix. The free spectral range (FSR) of the system was 400 to 1100 nm. The system was successfully tested for some applications, such as plasma diagnosis as well as applications in food and agriculture sciences.

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