New near-infrared absorbance peak for inhibitor content detection in transformer insulating oil

Leong, Yang Sing; Ker, Pin Jern; Jamaludin, M. Z.; Nomanbhay, Saifuddin; Ismail, Amiruddin; Abdullah, Fairuz; Looe, Hui Mun; Shukri, C. Nuru Saniyyati M.

doi:10.1016/j.snb.2018.03.064

Cited by 22 publications

(5 citation statements)

References 15 publications

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“…UV-VIS is one of the most-used techniques to characterize Ag NPs. A Specord 210 Plus UV-VIS double-beam spectrophotometer [83] from Analytik Jena company (Analytik Jena GmbH+Co. KG., 07745 Jena, Germany) with a spectral resolution of 2.5 nm was used to read the absorbance between 250 and 700 nm for both synthesis procedures performed in this paper, as well as for Ag-77.…”

Section: Uv-vismentioning

confidence: 99%

Comparative Synthesis of Silver Nanoparticles: Evaluation of Chemical Reduction Procedures, AFM and DLS Size Analysis

et al. 2023

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The size of silver nanoparticles plays a crucial role in their ultimate application in the medical and industrial fields, as their efficacy is enhanced by decreasing dimensions. This study presents two chemical synthesis procedures for obtaining silver particles and compares the results to a commercially available Ag-based product. The first procedure involves laboratory-based chemical reduction using D-glucose (C6H12O6) and NaOH as reducing agents, while the second approach utilizes trisodium citrate dehydrate (C6H5Na3O7·2H2O, TSC). The Ag nanoparticle suspensions were examined using FT-IR and UV-VIS spectroscopy, which indicated the formation of Ag particles. The dimensional properties were investigated using Atomic Force Microscopy (AFM) and confirmed by Dynamic Light Scattering (DLS). The results showed particle size from microparticles to nanoparticles, with a particle size of approximately 60 nm observed for the laboratory-based TSC synthesis approach.

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Section: Uv-vismentioning

confidence: 99%

Comparative Synthesis of Silver Nanoparticles: Evaluation of Chemical Reduction Procedures, AFM and DLS Size Analysis

et al. 2023

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“…Figure 2a shows a simplified block diagram of a conventional wired monitoring system for large-scale power transformers. In the monitoring system of a power transformer, various physical quantities can be converted into electrical signals using sensors, such as PD, vibration, and ultrasound [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. When an electrical signal is fed to a signal conditioner through a wire, the signal conditioner manipulates the input to prepare it for the next stage, a high-speed DAQ.…”

Section: Types Of Conventional Monitoring Systemsmentioning

confidence: 99%

“…For pole-mounted transformers, however, a high-speed DAQ system can be a bulky and very expensive solution [14]. Remote methods using infrared thermographs or ultrasonic fault detection have been introduced for monitoring polemounted transformers with limited accessibility or safety hazards [15,16]. Even though the equipment for remote monitoring can be expensive, multiple transformers at different locations can be monitored using a single remote monitoring unit.…”

Section: Introductionmentioning

confidence: 99%

Long-Lifetime Event-Driven Wireless Monitoring System for Pole-Mounted Transformers

Kwak

Kim

2021

Applied Sciences

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As smart grids develop rapidly, low-cost monitoring systems for pole-mounted transformers increase in demand. Even though battery-powered wireless monitoring systems appear to provide optimal solutions, they consume large amounts of energy for continuous sampling and data transmission. Operation and maintenance costs then increase owing to reduced battery lifetime and battery replacement. To overcome this problem, this paper presents an event-driven battery-powered wireless monitoring system that monitors abnormalities of a transformer and transmits data only if an abnormality occurs. When the proposed event controller detects an abnormality, it enables a root mean square (RMS) converter and a peak detector for sampling and transmitting the maximum RMS value of the abnormal signal and then falls into sleep mode until the next event to save energy. Simulation and experimental results show that the proposed system enhances battery lifetime by up to two orders of magnitude compared to a conventional battery-powered wireless monitoring system.

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“…insulating oil, which has excellent electrical insulating properties. Apart from acting as an insulating and cooling agent, transformer oil also can be used to determine the condition of the power transformer [11], [12]. This is due to the breaking of carbon-hydrogen (C-H) and carbon-carbon (C-C) bonds in the molecules of the oil when it is continuously subjected to electrical and thermal stresses during operation.…”

Section: Most Power Transformers Are Filled With Petroleum-basedmentioning

confidence: 99%

Fault Prediction for Power Transformer Using Optical Spectrum of Transformer Oil and Data Mining Analysis

et al. 2020

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Periodic preventive maintenance of power transformer should be conducted for its health monitoring and early fault detection. Transformer oil is a vital element where its contents and properties need to be monitored during the service life of a power transformer. This paper presents an optical spectroscopy measurement from 200 nm to 3300 nm to characterize the transformer oil, which were sampled from the main tanks and 'on-load tap changer' of power transformers. The correlation of the optical characteristics in the range of 2120 nm to 2220 nm to the Dissolved Gas Analysis results and Duval Triangle interpretation demonstrates that the low energy electrical discharges, high energy electrical discharges as well as the thermal faults rated at temperatures above 700 • C in power transformers can be accurately predicted. For faster and accurate analysis of fault prediction, a data mining analytics tool was constructed using Rapid Miner server to analyze and verify the predictions for a total of 108 oil samples. For the optimization, continuous iterations were performed to determine the best absorbance-wavelength combination that can improve the accuracy of the prediction. The performance of the optical spectroscopy technique integrated with data analytic tool was analyzed and it was found that the technique contributes to a high accuracy of 98.1% in fault prediction. It is a cost-effective and quicker complementing approach to carry out pre-screening of the transformer oil in order to know the condition of the power transformers based on the transformer oil's optical characteristics.INDEX TERMS Data mining, fault prediction, optical spectroscopy, power transformers, transformer oil.

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New near-infrared absorbance peak for inhibitor content detection in transformer insulating oil

Cited by 22 publications

References 15 publications

Comparative Synthesis of Silver Nanoparticles: Evaluation of Chemical Reduction Procedures, AFM and DLS Size Analysis

Comparative Synthesis of Silver Nanoparticles: Evaluation of Chemical Reduction Procedures, AFM and DLS Size Analysis

Long-Lifetime Event-Driven Wireless Monitoring System for Pole-Mounted Transformers

Fault Prediction for Power Transformer Using Optical Spectrum of Transformer Oil and Data Mining Analysis

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