TY - JOUR
T1 - Analysis of liquid viscosity by image processing techniques
AU - Santhosh, K. V.
AU - Shenoy, Vighnesh
PY - 2016
Y1 - 2016
N2 - Objective: In this paper, a technique is proposed for measurement of viscosity using the principle of dispersion of incident light with variation of liquid viscosity. The objective of the proposed technique is to design a non contact technique to analyze the characteristics of dispersed image using image processing for the light incident on liquid whose viscosity is to be measured. Methods: A camera is used to capture the background image of the refracted image. This captured image is processed by techniques like thresholding, filtering, and histogram to arrive at a quantified relation between viscosity and histogram values. To establish the relation an artificial neural network model is designed. Proposed neural network is trained by levenburg Marquardt Algorithm, once trained it is tested with the real time system conditions. Findings: Once the neural network is designed, tests are conducted. Several samples of liquid are used with varying viscosity. From the obtained results it is clear that the proposed technique is able to measure viscosity accurately with a root mean percentage of error 2.01%. Application: From the obtained results it is clear that the proposed viscosity measurement technique can be used for measurement of liquid viscosity, even in dynamic flow conditions.
AB - Objective: In this paper, a technique is proposed for measurement of viscosity using the principle of dispersion of incident light with variation of liquid viscosity. The objective of the proposed technique is to design a non contact technique to analyze the characteristics of dispersed image using image processing for the light incident on liquid whose viscosity is to be measured. Methods: A camera is used to capture the background image of the refracted image. This captured image is processed by techniques like thresholding, filtering, and histogram to arrive at a quantified relation between viscosity and histogram values. To establish the relation an artificial neural network model is designed. Proposed neural network is trained by levenburg Marquardt Algorithm, once trained it is tested with the real time system conditions. Findings: Once the neural network is designed, tests are conducted. Several samples of liquid are used with varying viscosity. From the obtained results it is clear that the proposed technique is able to measure viscosity accurately with a root mean percentage of error 2.01%. Application: From the obtained results it is clear that the proposed viscosity measurement technique can be used for measurement of liquid viscosity, even in dynamic flow conditions.
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U2 - 10.17485/ijst/2016/v9i30/98693
DO - 10.17485/ijst/2016/v9i30/98693
M3 - Article
AN - SCOPUS:84984660040
SN - 0974-6846
VL - 9
JO - Indian Journal of Science and Technology
JF - Indian Journal of Science and Technology
IS - 30
M1 - 98693
ER -