Diagnosis of transformers based on vibration data

Publications - Paper

Diagnosis of transformers based on vibration data

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#Electricity Network #Technologies and Components

Publications - Paper

Diagnosis of transformers based on vibration data

A Support Vector Machine (SVM) algorithm-based approach for vibration data analysis to identify winding slack in a typical distribution transformer.

Transformers with loose or deformed windings can fail in the event of an external short circuit with loss of service and high maintenance costs. The transformer tank vibration technique potentially offers a decisive solution for continuous online assessment of the integrity of transformer structural elements. In this paper, the influence of sensor position on tank vibration measurements is addressed by means of Support Vector Machine (SVM) algorithms. Laboratory tests were performed at different points in the tank on a typical oil transformer under two extreme conditions, with tight and slack windings. The preliminary results of SVM analysis of the tank vibration spectra showed that winding slack can be identified correctly during repetitive installation of the sensor.

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Management, monitoring and control of the transmission grid (Mon4Grid2018)

Related tags

#Electricity Network #Technologies and Components

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Publications - Paper

Diagnosis of transformers based on vibration data

Publications - Paper

Diagnosis of transformers based on vibration data

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