An Online Monitoring System for Oil Immersed Power Transformer Based on SnO<sub>2</sub> GC Detector With a New Quantification Approach

Fan, Jingmin; Feng, Wei; Sun, Qiuqin; Ye, Huisheng; Liu, Yuhan

doi:10.1109/jsen.2017.2734072

Cited by 38 publications

(17 citation statements)

References 32 publications

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“…In addition, most physical/chemical techniques rely on the external carrier gases. In recent years, with the development of related technologies, solid oxide fuel cell sensors [11], carbon nanotube sensors [12], and nano metal-oxide semiconductor sensors [13] have been proposed and researched. Part of the detector performance has been improved.…”

Section: Introductionmentioning

confidence: 99%

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Jiang

Wang

Han

et al. 2019

IEEE Trans. Dielect. Electr. Insul.

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Online dissolved gas analysis (DGA) is an effective technique to obtain the health status information of insulation oil in power transformers. The typical hydrocarbon gases (methane, ethyne, ethene, ethane) decomposed from insulation oil, are the key indicators to diagnose the fault type and severity. To realize contactless and field measurement, a multi-gas detection system based on tunable diode laser absorption spectrum (TDLAS) is proposed in this paper. Critical technique problems on the light source, long path gas cell, and the topology for multi-gas detection are investigated. Individual central wavelengths of hydrocarbon gases are set at as 1653.72 nm for methane, 1530.37 nm for ethyne, 1620.04 nm for ethene and 1679.06 nm for ethane in the near infrared band. A 10.13 m long multi-pass gas cell is developed with the advantage of anti-vibration design. To share the optical absorption path, an optical switch is adopted to merge the multi-gas detection system. The high sensitivity of the TDLAS multi-gas detection system was demonstrated in the laboratory calibrations, with ethyne detection reaching sub-parts per million level, and the other hydrocarbon gases achieving ppm level. Furthermore, the comparison detection in the real 220 kV power transformer gave evidence to the effective monitoring of DGA, proving it an alternative approach to online detection of multiple gases in power transformer oil.

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Section: Introductionmentioning

confidence: 99%

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Jiang

Wang

Han

et al. 2019

IEEE Trans. Dielect. Electr. Insul.

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“…These monitoring systems most often work on the basis of one of the three relatively well-known and developed diagnostic methods, i.e. : (i) dissolved gas analysis in oil (DGA), (ii) detection of the acoustic emission signals (AE), and (iii) detection of electromagnetic waves in different frequency bands (HF/VHF/UHF) [8,12,17,21,23,25,28,30]. Electromagnetic PD detection methods are already widely applied in diagnostics of gas insulated lines and substations (GIL/GIS), rotating machines, cables and medium voltage substations [1,13].…”

Section: Wojciech Sikorski Cyprian Szymczak Krzysztof Siodła Filip Polakmentioning

confidence: 99%

Hilbert curve fractal antenna for detection and on-line monitoring of partial discharges in power transformers

Sikorski¹,

Szymczak²,

Siodła³

et al. 2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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Science and Technology article citation info: IntroductionLarge power transformers are the most critical component in electric power systems, as they are essential in maintaining a reliable supply of electric energy. There are many factors which cause a transformer malfunction, but those, which can potentially lead to catastrophic failure are winding damages (due to short-circuit, lightning, and other over-voltages) and insulation system failure (moisture, thermal aging, partial discharges). The damage from a catastrophic transformer failure may run into tens of millions of dollars [16]. To avoid such a scenario, power utilities are moving towards continuous transformer condition monitoring, based on dissolved gas analysis and acoustic emission (AE) or electromagnetic (HF/VHF/UHF) partial discharge detection.According to the newest research results and analyses presented by the experts of the CIGRE Working Group A2.37, in the technical brochure 642: Transformer Reliability Survey, the main reason of breakdowns of high voltage power transformers is damage to the windings and the main insulation system [3]. Mechanical defects in the form of winding deformations (axial displacements and radial deformations) and deterioration of insulation properties associated with thermal aging processes [6], can lead to the initiation of the partial discharge (PD) phenomena occurrence.In recent years, in the electric power industry and research centres, a trend consisting in developing and implementing advanced

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“…C 2 H 4 is the main content of hydrocarbon while at high temperature thermal faults ( T > 300°C) (Fan et al, 2017). For detecting these hydrocarbons, an online monitoring system based on a SnO 2 -based gas chromatographic detector for assessing the running condition of a power transformer was developed (Fan et al, 2017). Qi et al fabricated a C 2 H 2 sensor based on 6 wt% Sm 2 O 3 -doped SnO 2 , whose gas response to 1,000 ppm C 2 H 2 could reach 63.8, 16.8 times larger than that of pure SnO 2 (Qi et al, 2008).…”

Section: Sensing Performances Of Sno2-based Sensors To Fault Charactementioning

confidence: 99%

Recent Advances of SnO2-Based Sensors for Detecting Fault Characteristic Gases Extracted From Power Transformer Oil

Zhang

Zhou

et al. 2018

Front. Chem.

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Tin oxide SnO2-based gas sensors have been widely used for detecting typical fault characteristic gases extracted from power transformer oil, namely, H2, CO, CO2, CH4, C2H2, C2H4, and C2H6, due to the remarkable advantages of high sensitivity, fast response, long-term stability, and so on. Herein, we present an overview of the recent significant improvement in fabrication and application of high performance SnO2-based sensors for detecting these fault characteristic gases. Promising materials for the sensitive and selective detection of each kind of fault characteristic gas have been identified. Meanwhile, the corresponding sensing mechanisms of SnO2-based gas sensors of these fault characteristic gases are comprehensively discussed. In the final section of this review, the major challenges and promising developments in this domain are also given.

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An Online Monitoring System for Oil Immersed Power Transformer Based on SnO₂ GC Detector With a New Quantification Approach

Cited by 38 publications

References 32 publications

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Hilbert curve fractal antenna for detection and on-line monitoring of partial discharges in power transformers

Recent Advances of SnO2-Based Sensors for Detecting Fault Characteristic Gases Extracted From Power Transformer Oil

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An Online Monitoring System for Oil Immersed Power Transformer Based on SnO2 GC Detector With a New Quantification Approach

Cited by 38 publications

References 32 publications

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Multi-gas detection in power transformer oil based on tunable diode laser absorption spectrum

Hilbert curve fractal antenna for detection and on-line monitoring of partial discharges in power transformers

Recent Advances of SnO2-Based Sensors for Detecting Fault Characteristic Gases Extracted From Power Transformer Oil

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An Online Monitoring System for Oil Immersed Power Transformer Based on SnO₂ GC Detector With a New Quantification Approach