Observations and Modeling for Source Characterization

2011 ◽  
Author(s):  
Mark A. Moline ◽  
Lyle F. Hibler
Keyword(s):  
Source Characterization

Source characterization of disinfection byproduct precursors in two Arkansas water-supply reservoirs

Fact Sheet ◽  
1997 ◽  
Author(s):  
Michael L. Pomes ◽  
W.R. Green ◽  
E.M. Thurman ◽  
W.H. Orem ◽  
H.T. Lerch
Keyword(s):  
Water Supply ◽  
Source Characterization ◽  
Disinfection Byproduct ◽  
Water Supply Reservoirs

scholarly journals An Efficient Method for LED Light Sources Characterization

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1089 ◽  
Author(s):  
Sara Raggiunto ◽  
Alberto Belli ◽  
Lorenzo Palma ◽  
Piergiovanni Ceregioli ◽  
Massimo Gattari ◽  
...  
Keyword(s):  
Efficient Method ◽  
Least Squares Method ◽  
Color Temperature ◽  
Experimental Setup ◽  
Light Sources ◽  
Careful Study ◽  
Source Characterization ◽  
Led Light ◽  
Lighting Systems ◽  
Led Drivers

Digital LED drivers capable of blending the spectrum of two LED fixtures with different Correlated Color Temperatures through the LEDs’ power supply control are widespread. However, the digital control of lighting systems is possible only after a careful study of the LED’s response, in terms of illuminance and Correlated Color Temperature. The proposed work takes advantage of the Tunable White technology for the realization of an efficient method for LED light source characterization. In order to evaluate how the light changes as a function of the electric power supplied by the LED drivers, an experimental setup to characterize LED light sources has been designed. Starting from the data acquired from the experimental setup, a model for dimming the LED driver and obtaining the desired values of quality of light has been developed. The proposed model is based on the least squares method and its accuracy is evaluated by comparing the obtained values of illuminance and Correlated Color Temperature with those measured by an illuminance spectrophotometer. Results achieved an error of 0.3% for Correlated Color Temperature and 1.5% for illuminance using the proposed approximation functions.

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