I am working in a project where it's necessary to do a LED board to replace UVA 340/UVA 351 fluorescent tubes (represented in the graphic by the blue line).
I have to use LEDs with wavelengths from 280 to 420 nm and achieve a maximum point of 1 W/m² at 340 nm.
How can I normalize and distribute my LEDs in order to achieve the goal?
Good morning Raquel
In order to normalize your data set you first need to quantify the residual measurement value of the full dark situation and then subtract it from each set member value. You can then redistribute the set member values by reference to this zero point. Clearly, you can also apply all the standard methods of statistical analysis.
David Oulton the thing is, I have some leads with different peaks and I have to fit them in order to get one gaussian with peak 1 W/m² at 340 nm. Is normalization the rigth choice for this?
You can buy LEDs in this band, 340nm UV LED http://www.microphotons.cn/?a=cp3&id=303
Are you trying to physically or computationally match the power outputs? If you are trying to match the measured power, you need to find an LED that provides at least 1 W/m² at 340 nm, and dim it till you get there. If you are computationally match the power, you can normalize the spectral power distribution of the LED to 1 W/m² at 340 nm and rescale the rest of the spectra. Does this answer your question?
Raquel Andrade, there are two possible solutions of your task. Simplest is to put your LEDs close to focal point of a lens, which image them onto your plane of illumination. More homogeneous distribution can be obtained with two lens system: first lens image of LEDs on the the plane of the second lens, which image surface of this lens into plane of illumination. Due to UV light your lenses have to be silica made.
Good luck!
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