IoT-Based Transformer Health Monitoring System using ESP32

Distribution transformers fail for preventable reasons. Sustained overloading cooks the winding insulation; overheating degrades the insulating oil; low oil level exposes windings; prolonged over-voltage stresses insulation until it gives way. Each of these failure modes is slow — measurable days or weeks before the burnout — yet utilities still lose transformers every year because the failure arrives as a surprise: nobody was watching the parameters. Manual inspection rounds cannot catch a gradual temperature creep between visits, and a transformer that fails takes the feeder down with it, leaving customers without power until a replacement is installed. Continuous monitoring changes the economics: four cheap sensors — oil temperature, load current, voltage, oil level — streamed to a dashboard with alert thresholds turn surprise burnouts into scheduled maintenance. The engineering lies in sensing AC quantities safely, computing true RMS values on a small microcontroller, and delivering alerts over WiFi or GSM.

1. The sensors continuously sample oil temperature, load current, input/output voltage and oil level.
2. The ESP32 processes the readings, computes RMS current and voltage, and compares each parameter against its configured alarm threshold.
3. Live readings appear on the onboard OLED display and are pushed over WiFi (MQTT/HTTP) to the cloud dashboard.
4. When a threshold is crossed — oil temperature rising past the set limit, or load current exceeding the rated value — the GSM module fires an SMS alert instantly.
5. On a severe fault, the relay output can trip the load automatically. The logged trend data demonstrates predictive maintenance: gradual temperature rise or creeping load imbalance visible days before a failure.

• Oil temperature monitoring with DS18B20 digital probe (±0.5°C per the sensor datasheet)
• Load current sensing with non-invasive SCT-013 split-core current transformer
• Input and output voltage monitoring with ZMPT101B AC voltage sensor modules
• Oil-level detection with float switch — alerts on low oil before damage occurs
• Live cloud dashboard with trend graphs for every parameter
• SMS alerts via GSM on overload, overheating, low oil or voltage anomalies
• Fully configurable alarm thresholds for temperature, current and voltage
• Relay trip output for automatic load disconnection on severe faults
• On-device OLED display showing live readings during demos
• Data logging for trend analysis and report graphs

• Assembled transformer-monitoring prototype with demo model
• Complete source code (Arduino IDE, well-commented)
• Circuit diagram and wiring schematic
• Project report PDF (synopsis, design, results, conclusion)
• PPT presentation for final review
• Viva Q&A preparation document
• Cloud dashboard and GSM setup guide

FAQs

1. Is it safe to demo a transformer project in college? Yes — the build uses a scaled low-voltage model transformer and load bank, so no high-voltage handling is needed. The sensing and alert logic mirrors real substation practice.
2. What temperature and current thresholds should be set? Utility practice typically alarms top-oil temperature around 90°C and trips near 105°C, with overload flagged above the rated current. For the demo model these are scaled down; every threshold is configurable in firmware and the report documents the chosen values with justification.
3. How does the SCT-013 current transformer work? It is a split-core CT with a 100 A : 50 mA ratio — it clamps around the load wire without breaking the circuit, and the ESP32 converts the small secondary current into an RMS load-current reading. The report walks through the CT-ratio calculation.
4. Does the project predict failures or just display readings? Both. Alerting handles the present; the logged trend data is the predictive part — a slowly rising oil temperature or a growing input-output voltage difference signals developing trouble before a burnout. That predictive-maintenance angle is the strongest review talking point.
5. WiFi or GSM — which does it use? Both. WiFi feeds the cloud dashboard for campus demos; GSM sends SMS alerts independently, which mirrors how remote substations report where internet is unreliable.
6. Can it disconnect the load on a fault? Yes — a relay trip output is included for severe faults such as extreme over-temperature. It demonstrates the step from monitoring to protection.