A Graphitic Carbon Nitride Film Capacitive Sensor for Selective Trace Moisture Detection in Transformer Oil

Transformers play a vital role in the power system. Moisture, 2-furfuraldehyde (2-FAL), and dissolved gases in transformer oil are used to assess the condition of the insulation in transformers. Reliable transformer insulation health monitoring in real time is still a challenge. Sensorbased monitoring is one of the solutions. The moisture concentration in oil is an important indicator of the health of oil and article insulation as well as an in-service transformer. Although it is possible to measure moisture concentrations in transformer oil using a capacitive sensor as its dielectric constant is very high in comparison to the oil, at the same time, the capacitive sensor will be sensitive to another high dielectric constant contamination, 2-FAL. Therefore, sensitive and selective measurement of the concentration of moisture in oil is a challenge. In this work, a novel material with an optimized comb structure is presented for selective trace moisture detection. A graphitic carbon nitride (g- C3N4) film capacitive sensor for moisture detection in transformer oil has been presented. This work aims to develop a robust and precise sensor for on-site condition monitoring, with an emphasis on material selection, design, and accurate characterization. The proposed sensor is tested for mineral and palm oil samples that contain different moisture concentrations from 0 to 40 ppm. The cross-sensitivity of the sensor is determined with 2-FAL and it is found that it is highly selective for moisture. The proposed sensor is found to be highly sensitive and selective for moisture detection in oil.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-11-07
DOI
https://doi.org/10.1109/jsen.2024.3486614
Citations
2
Primary Topic
Analytical Chemistry and Sensors
Type
article
Field-Weighted Citation Impact
0.58
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article

A Graphitic Carbon Nitride Film Capacitive Sensor for Selective Trace Moisture Detection in Transformer Oil

Shakeb A. Khan, Asfar Ali Khan, Arif Ali, Abdul Suboor et al.
2 citations
IEEE Sensors Journal
Analytical Chemistry and Sensors
0.58
article

A Graphitic Carbon Nitride Film Capacitive Sensor for Selective Trace Moisture Detection in Transformer Oil

Shakeb A. Khan, Asfar Ali Khan, Arif Ali, Abdul Suboor, Obaidur Rahman, Mohd Saquib Tanweer
article en
2 citations

Abstract

Transformers play a vital role in the power system. Moisture, 2-furfuraldehyde (2-FAL), and dissolved gases in transformer oil are used to assess the condition of the insulation in transformers. Reliable transformer insulation health monitoring in real time is still a challenge. Sensorbased monitoring is one of the solutions. The moisture concentration in oil is an important indicator of the health of oil and article insulation as well as an in-service transformer. Although it is possible to measure moisture concentrations in transformer oil using a capacitive sensor as its dielectric constant is very high in comparison to the oil, at the same time, the capacitive sensor will be sensitive to another high dielectric constant contamination, 2-FAL. Therefore, sensitive and selective measurement of the concentration of moisture in oil is a challenge. In this work, a novel material with an optimized comb structure is presented for selective trace moisture detection. A graphitic carbon nitride (g- C3N4) film capacitive sensor for moisture detection in transformer oil has been presented. This work aims to develop a robust and precise sensor for on-site condition monitoring, with an emphasis on material selection, design, and accurate characterization. The proposed sensor is tested for mineral and palm oil samples that contain different moisture concentrations from 0 to 40 ppm. The cross-sensitivity of the sensor is determined with 2-FAL and it is found that it is highly selective for moisture. The proposed sensor is found to be highly sensitive and selective for moisture detection in oil.

IEEE Sensors JournalVol. 25(3)
Aligarh Muslim University (IN), Jamia Millia Islamia (IN)
Openalex Percentile: Top 36%
Analytical Chemistry and Sensors
0.58
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