Influence of Standoff Distance and Sunlight on Detection of Pollution Deposits on Silicone Rubber Insulators Adopting Remote LIBS Analysis

IEEE Transactions on Industry Applications(2022)

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Abstract
Silicone rubber (SR) insulators have been coated with different concentrations of NaCl to study the contamination level adopting laser-induced breakdown spectroscopy (LIBS) analysis. An elemental study of LIBS spectral data has identified the sodium peaks, thereby indicating the presence of salt deposits. A regression coefficient is used for a better understanding of the direct correlation between the salt deposit density (SDD) and the normalized intensity ratio, at various standoff distances. A marginal decrement in the normalized intensity ratio of the sodium peaks has been noticed in the case of readings taken at morning and midday, compared to those taken at night at different SDD values and different energies of the laser pulse. With increase in SDD, the intensity distribution characteristics have a right shift on the intensity scale. The polluted SR specimens are successfully classified by employing artificial neural network technique. Overall, the LIBS method is successful in identifying the variations in the salt deposition on the surface of the insulator, even at far distances of 15 m and at any time of the day.
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Key words
Artificial neural network (ANN),laser-induced breakdown spectroscopy (LIBS),normalized intensity ratio,salt deposit density (SDD),silicone rubber,standoff distance
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