August 1, 2025Open Access

Condition Monitoring in Power Transformers Using IoT: A Model for Predictive Maintenance

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Authors

ATAleem Al Razee Tonoy

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Implication

This model demonstrates enhanced fault detection and maintenance efficiency in power transformers, indicating improved reliability with IoT applications.

Key Points

The model significantly enhances condition monitoring for power transformers using IoT technologies for predictive maintenance.
It integrates data from multiple sensors, including oil temperature and moisture content, for real-time analysis.
Validation through simulated and real-world case studies shows improved fault detection accuracy and maintenance scheduling efficiency.
This approach reduces unplanned outages and operational costs by enabling timely interventions based on predictive insights.

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Aleem Al Razee Tonoy (2025) studied this question.

synapsesocial.com/papers/689a0c65e6551bb0af8cfaf1 https://doi.org/10.20944/preprints202507.2379.v1

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Implication

This model demonstrates enhanced fault detection and maintenance efficiency in power transformers, indicating improved reliability with IoT applications.

Condition Monitoring in Power Transformers Using IoT: A Model for Predictive Maintenance

Discussion

Member takes

Implication

Key Points

Cite This Study

Condition Monitoring in Power Transformers Using IoT: A Model for Predictive Maintenance

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider