Transformers are critical assets in power distribution. Unexpected failures can lead to prolonged downtime, safety hazards, and significant financial losses.
Our AI-powered Predictive Maintenance solution monitors key parameters to detect anomalies early, ensuring reliability and preventing catastrophic failures.
Our system monitors multiple critical parameters including oil level, oil temperature, power factor, current, vibration, and voltage to predict transformer health.
Detect insulation breakdown, overheating, and oil degradation before they lead to transformer explosions or fires.
Move from time-based to condition-based maintenance, reducing unnecessary interventions and costs.
Proactive monitoring helps extend transformer lifespan by 20-30% through timely interventions.
AI models trained on oil level, temperature, power factor, current, vibration, and voltage data.
Continuous monitoring of oil temperature, dissolved gases, moisture levels, and electrical parameters provides immediate alerts for abnormal conditions. Real-time dashboards show health status across your transformer fleet with millisecond latency.
Machine learning models analyze historical and real-time data to identify patterns indicative of developing faults. The system learns normal operating conditions and alerts when parameters deviate from expected ranges, enabling early intervention.
Join industry leaders who trust Pradjna for predictive maintenance solutions that deliver measurable ROI.
CEO, Pradjna Intellisys™
"Our transformer monitoring solution represents the convergence of IoT and AI. We're not just collecting data - we're creating intelligence that prevents failures before they happen, ensuring grid reliability and safety. The results speak for themselves: our clients have reduced maintenance costs by 40% while increasing asset uptime to 99.7%."