Optical Detection of Inhibitor in Transformer Oil at Silicon-Detectable Wavelength Using Variable Path Length Model

Thiviyanathan, Vimal Angela; Ker, Pin Jern; Leong, Yang Sing; Jamaludin, M. Z.; Hannan, M. A.; Mun, Looe Hui

doi:10.1109/jsen.2020.3041903

Cited by 4 publications

(2 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The spectral peaks at wavelengths 856 nm and 1098 nm belong to the C-H third overtone [35], and the spectral peak in wavelength 1586 nm is for the second overtone of N-H [36]. The peak at around wavelength 1320 nm is related to C-H combinations, and the peak at wavelength 980 nm is related to the second overtone of O-H bending [37,38].…”

Section: Vis-nir Reflectance Spectra Of Different Edible Oilsmentioning

confidence: 99%

Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods

Pan

Wang

et al. 2021

Biosensors

View full text Add to dashboard Cite

The composition and content of fatty acids are critical indicators to identify the quality of edible oils. This study was undertaken to establish a rapid determination method for quality detection of edible oils based on quantitative analysis of palmitic acid, stearic acid, arachidic acid, and behenic acid. Seven kinds of oils were measured to obtain Vis-NIR spectra. Multivariate methods combined with pretreatment methods were adopted to establish quantitative analysis models for the four fatty acids. The model of support vector machine (SVM) with standard normal variate (SNV) pretreatment showed the best predictive performance for the four fatty acids. For the palmitic acid, the determination coefficient of prediction (RP2) was 0.9504 and the root mean square error of prediction (RMSEP) was 0.8181. For the stearic acid, RP2 and RMSEP were 0.9636 and 0.2965. In the prediction of arachidic acid, RP2 and RMSEP were 0.9576 and 0.0577. In the prediction of behenic acid, the RP2 and RMSEP were 0.9521 and 0.1486. Furthermore, the effective wavelengths selected by successive projections algorithm (SPA) were useful for establishing simplified prediction models. The results demonstrate that Vis-NIR spectroscopy combined with multivariate methods can provide a rapid and accurate approach for fatty acids detection of edible oils.

show abstract

Section: Vis-nir Reflectance Spectra Of Different Edible Oilsmentioning

confidence: 99%

Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods

Pan

Wang

et al. 2021

Biosensors

View full text Add to dashboard Cite

show abstract

“…It plays the role of arc extinguishing, heat conduction and insulation [2]. Its performance and quality are crucial to the safe operation of transformers and even the entire power system [3]. Once a failure leads to insufficient power, it will cause irreparable losses to people's lives and industrial production [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

New Measurement Method of Viscosity, Density, and Dielectric Constant of Transformer Oil Based on Quartz Tuning Fork

Chen

Ding

et al. 2022

IEEE Sensors J.

View full text Add to dashboard Cite

Transformer oil is a liquid insulating material used in ultra-high voltage power equipment such as oil-immersed transformers and reactors. Online monitoring of its characteristics helps to maintain the status of power equipment. Aiming at the problem of single detection parameter in traditional methods, a new detection method for density, viscosity and dielectric constant based on quartz tuning fork is proposed in this paper. Firstly, by analyzing the working mechanism of the quartz tuning fork, the sensor detection model and parameter extraction method in air are constructed based on the equivalent circuit model of the Butterworth-Van Dyke model. Then, the working mechanism of the density, viscosity and dielectric constant of the transformer oil is analyzed, and the method of parameter extraction of sensor in standard oil sample and measurement model of sensor in oil sample to be measured are obtained. Finally, an experimental platform is built to verify the above conclusions. The results show that the quartz tuning fork detection model has good repeatability, the measurement errors of density, viscosity and dielectric constant are 2.52%, 6.53% and 3.36%, respectively, which meet the online monitoring accuracy requirements. The detection technology of transformer viscosity, density and dielectric constant based on quartz tuning fork realizes the simultaneous detection of three parameters in the same method, which meets the requirements of miniaturization, diversification and real-time detection of power parameters under the condition maintenance system, and also provides a new application scenario for tuning fork quartz crystal oscillators.

show abstract

Microalgae biomass and biomolecule quantification: Optical techniques, challenges and prospects

Thiviyanathan,

Ker,

Hoon Tang

et al. 2024

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

Optical Detection of Inhibitor in Transformer Oil at Silicon-Detectable Wavelength Using Variable Path Length Model

Cited by 4 publications

References 24 publications

Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods

Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods

New Measurement Method of Viscosity, Density, and Dielectric Constant of Transformer Oil Based on Quartz Tuning Fork

Microalgae biomass and biomolecule quantification: Optical techniques, challenges and prospects

Contact Info

Product

Resources

About