Prediction Model for Dissolved Gas in Transformer Oil Based on Non-Parametric Regression

Jin Qiang Chen

doi:10.4028/www.scientific.net/AMR.986-987.1410

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 986-987Prediction Model for Dissolved Gas in Transformer...

Prediction Model for Dissolved Gas in Transformer Oil Based on Non-Parametric Regression

Abstract:

The non-parametric regression prediction model for dissolved gases in power transformer and its application are studied. As the intervals between two analytic experiments of transformer dissolved gas are unfixed,the data sequence sampled with unequal intervals is converted into the data sequences with equal intervals,which is smoothed to form a new sequence. And then use the historical samples data to establish non-parametric regression model for prediction. Compared with the grey model,the non-parametric regression model has better prediction accuracy. The case verifies the correctness and feasibility of the method.

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Energy Research and Power Engineering 2014

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Periodical:

Advanced Materials Research (Volumes 986-987)

Pages:

1410-1413

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.986-987.1410

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Online since:

July 2014

Authors:

Jin Qiang Chen*

Keywords:

Dissolved Gas in Oil, Non-Parametric Regression, Prediction, Transformer

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References

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