Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil

Monitoring of moisture content in oil by utility companies is a routine exercise to keep the oil performance in check. Currently, Karl Fischer titration is being used for water determination in oil with sensitivity of 10 ppm and below however, it involves various expensive solvents and its time-cons...

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Main Author: Amelia Laccy, Jeffrey Kimura
Format: Thesis
Language:English
Published: Universiti Malaysia Sarawak (UNIMAS) 2021
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Online Access:http://ir.unimas.my/id/eprint/36436/1/Amelia%20Laccy%20Anak%20Jeffrey%20Kimura%20ft.pdf
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spelling my.unimas.ir.364362023-03-03T09:15:53Z http://ir.unimas.my/id/eprint/36436/ Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil Amelia Laccy, Jeffrey Kimura QD Chemistry Monitoring of moisture content in oil by utility companies is a routine exercise to keep the oil performance in check. Currently, Karl Fischer titration is being used for water determination in oil with sensitivity of 10 ppm and below however, it involves various expensive solvents and its time-consuming. Similarly, the Kittiwake analyzer also requires expensive solvents for analysis. In this study, Fourier Transform Infrared (FTIR) incorporated with Partial Least Squares was studied for prediction of moisture in the locally available transformer oil and lubricating oil. The standards were prepared by direct spiking of moisture in oil, direct spiking of moisture with addition of surfactant to reduce scattering of infrared light and extraction of moisture using acetonitrile. Among the three strategies, the most effective way to prepare standards for FTIR is the solvent extraction method. The spectral regions corresponding to moisture were found at 1600-1700 cm-1 and 3400-3750 cm-1. The former region at the lower frequency was found to produce better prediction accuracy with a lower % Root Mean Squares Error (RMSE). The FTIR method incorporated with PLS regression predicts samples with higher moisture concentrations with better accuracy. The method is not sensitive for detection of moisture at concentrations less than 1000 ppm. The limit of detection (LOD) established for quantification of moisture in transformer oil and lubricating oil was 1000 ppm and 700 ppm, respectively. The low sensitivity of FTIR is attributable to the short path length cell. The Karl Fischer (KF) method and Kittiwake analyser were used to compare with the FTIR method. However, both methods were not directly comparable with the FTIR method because both KF and Kittiwake demonstrated a better sensitivity for detection of moisture at low concentrations. Universiti Malaysia Sarawak (UNIMAS) 2021-01-14 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/36436/1/Amelia%20Laccy%20Anak%20Jeffrey%20Kimura%20ft.pdf Amelia Laccy, Jeffrey Kimura (2021) Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil. Masters thesis, Universiti Malaysia Sarawak.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QD Chemistry
spellingShingle QD Chemistry
Amelia Laccy, Jeffrey Kimura
Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
description Monitoring of moisture content in oil by utility companies is a routine exercise to keep the oil performance in check. Currently, Karl Fischer titration is being used for water determination in oil with sensitivity of 10 ppm and below however, it involves various expensive solvents and its time-consuming. Similarly, the Kittiwake analyzer also requires expensive solvents for analysis. In this study, Fourier Transform Infrared (FTIR) incorporated with Partial Least Squares was studied for prediction of moisture in the locally available transformer oil and lubricating oil. The standards were prepared by direct spiking of moisture in oil, direct spiking of moisture with addition of surfactant to reduce scattering of infrared light and extraction of moisture using acetonitrile. Among the three strategies, the most effective way to prepare standards for FTIR is the solvent extraction method. The spectral regions corresponding to moisture were found at 1600-1700 cm-1 and 3400-3750 cm-1. The former region at the lower frequency was found to produce better prediction accuracy with a lower % Root Mean Squares Error (RMSE). The FTIR method incorporated with PLS regression predicts samples with higher moisture concentrations with better accuracy. The method is not sensitive for detection of moisture at concentrations less than 1000 ppm. The limit of detection (LOD) established for quantification of moisture in transformer oil and lubricating oil was 1000 ppm and 700 ppm, respectively. The low sensitivity of FTIR is attributable to the short path length cell. The Karl Fischer (KF) method and Kittiwake analyser were used to compare with the FTIR method. However, both methods were not directly comparable with the FTIR method because both KF and Kittiwake demonstrated a better sensitivity for detection of moisture at low concentrations.
format Thesis
author Amelia Laccy, Jeffrey Kimura
author_facet Amelia Laccy, Jeffrey Kimura
author_sort Amelia Laccy, Jeffrey Kimura
title Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
title_short Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
title_full Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
title_fullStr Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
title_full_unstemmed Development of Partial Least Squares Integrated Fourier Transform Infrared Approach for Prediction of Moisture Content in Transformer Oil and Lubricating Oil
title_sort development of partial least squares integrated fourier transform infrared approach for prediction of moisture content in transformer oil and lubricating oil
publisher Universiti Malaysia Sarawak (UNIMAS)
publishDate 2021
url http://ir.unimas.my/id/eprint/36436/1/Amelia%20Laccy%20Anak%20Jeffrey%20Kimura%20ft.pdf
http://ir.unimas.my/id/eprint/36436/
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score 13.15806