Study on Influences and Elimination of Test Temperature on PDC Characteristic Spectroscopy of Oil-Paper Insulation System

Liu, Xiao; Liao, Ruijin; Lv, Yandong; Liu, Jiefeng; Gao, Jun; Hao, Jian

doi:10.5370/jeet.2015.10.3.1107

Cited by 7 publications

(3 citation statements)

References 17 publications

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“…The insulation system of oil-immersed power transformer is mainly composed of insulating oil and insulating paper [4]. In the process of long-term operation, the oil paper insulation material decomposes under the action of electric and thermal factors, producing a series of substances reflecting operational faults and insulation aging characteristics [5,6]. The content of acetone, as one of the aging characteristics of oil-paper insulation, can be used as a parameter to assess the aging condition of the insulation system [7].…”

Section: Introductionmentioning

confidence: 99%

Surface enhanced substrate simulation optimized coupled PLS model for quantitative detection of acetone in transformer oil

Qian,

Wang,

Pan

et al. 2024

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Acetone is a reliable index to evaluate the aging state of oil paper insulation. It is of great significance to study a fast, highly sensitive and accurate method of detecting acetone in oil to ensure the safe and stable operation of oil-immersed transformers. In this paper, a method based on surface enhanced Raman spectroscopy for the detection of acetone in oil is investigated. Based on the mechanism of surface-enhanced Raman spectroscopy (SERS), a simulation model of surface-enhanced substrate was constructed using COMSOL software, and it was determined that the enhancement effect was better when silver nanowires/zinc oxide nanorods (Ag/ZnO) composite structure was selected. Ag/ZnO substrates were prepared by solvothermal method and experimentally tuned and characterized to obtain SERS substrates with high enhancement properties. The substrate coupled partial least square (PLS) model was used to establish a method for the detection of acetone in insulating oils, and its limit of quantification for acetone was 0.003 mg/g, which meets the requirements for engineering testing.

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Section: Introductionmentioning

confidence: 99%

Surface enhanced substrate simulation optimized coupled PLS model for quantitative detection of acetone in transformer oil

Qian,

Wang,

Pan

et al. 2024

Opt Rev

View full text Add to dashboard Cite

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“…Saha and Purkait [14] investigated the PDC curves at different temperatures to indicate that the polarization time will be shortened as the temperature increase. In response to the above research results, the master curve technique based on the time-temperature superposition theory is used as an available model to correct the temperature effect of the transformer polymer insulation materials, which provides a novel idea for related research [15][16][17][18][19][20]. However, the temperature effect is considered as the single factor affecting the PDC test results in the existing research, which ignores the fact that moisture content is also an important factor affecting the polarization data of polymer material.…”

Section: Introductionmentioning

confidence: 99%

Correction for Polarization Current Curve of Polymer Insulation Materials in Transformers Considering the Temperature and Moisture Effects

et al. 2020

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Depending on the study of the master curve technique, a temperature correction model for the polarization current of transformer polymer (cellulose) insulation, considering the effects of both moisture content (mc%) and temperature is proposed. In the current work, the shift factors of polarization current curves of samples with various moisture contents are extracted at different temperatures. Then, the variation law among the shift factor, test temperature, and moisture content are studied so as to establish the corresponding functional relationship. The findings reveal that the modified model derived from the above functional relationship could be employed to perform the temperature correction of oil-immersed polymer samples with various insulation states. Therefore, the proposed temperature correction model in this paper will promote the state assessment of the field transformer polymer insulation.

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“…A fault in a transformer may result in not only substantial repair cost but also power interruptions to thousands of customers, therefore it is essential to assess its working condition online and detect the potential fault as soon as possible [1].…”

Section: Introductionmentioning

confidence: 99%

A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

Zhang¹,

Wang²,

Liao³

et al. 2017

Journal of Electrical Engineering and Technology

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-Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

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Study on Influences and Elimination of Test Temperature on PDC Characteristic Spectroscopy of Oil-Paper Insulation System

Cited by 7 publications

References 17 publications

Surface enhanced substrate simulation optimized coupled PLS model for quantitative detection of acetone in transformer oil

Surface enhanced substrate simulation optimized coupled PLS model for quantitative detection of acetone in transformer oil

Correction for Polarization Current Curve of Polymer Insulation Materials in Transformers Considering the Temperature and Moisture Effects

A New Support Vector Machine Model Based on Improved Imperialist Competitive Algorithm for Fault Diagnosis of Oil-immersed Transformers

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