AI Anomaly &
Predictive Analytics.
Pre-empt unplanned shutdowns. Orbit AI correlates electrical, thermal, vibration and human maintenance history to identify mechanical wear precursors and schedule autonomous maintenance workflows 7–21 days in advance.
+12.4% vs industry baseline
-38.2% downtime optimization
100% nominal connection status
Critical downtime avoided YTD
One Model, Four Sources Of Truth
Orbit AI never relies on a single sensor. It continuously learns from electrical measurements, temperature, vibration — and from your own maintenance team's history and behavior — to tell a real failure precursor apart from normal operational noise.
Current, voltage, power, phase imbalance and harmonic distortion sampled continuously from every panel and feeder.
Infrared cameras and contact sensors track bearing, winding and enclosure temperatures in real time.
High-frequency accelerometers capture vibration harmonics up to 10kHz on every rotating asset.
Every past intervention, corrective-vs-preventive ratio and technician note feeds back into the model.
Cross-references every signal against equipment age, operating hours and the technician's own intervention history to isolate true degradation patterns.
A 7–21 day advance warning, automatically dispatched as a maintenance work order to the right technician.
DIAGNOSTIC STATUS
Asset Performance & Maintenance Intelligence
Combine asset condition, energy & power quality (APQ) and OEE insights to drive preventive maintenance, optimize maintenance management, and improve equipment reliability.
Electrical Meter Analytics
Tracks current, voltage, power factor, phase imbalance and harmonic distortion (THDV/THDI) on every panel. Electrical stress signatures often precede a mechanical failure by weeks, giving the model an early lead indicator before vibration or heat even change.
FFT Vibration Spectrograms
Samples physical sound and vibration harmonics up to 10kHz. Fast Fourier Transform mathematical matrices isolate sub-millimeter motor misalignments or bearing pitting before physical defects damage rotors.
Infrared Temperature Anomaly
Integrates with infrared imaging cameras, monitoring turbine thermal boundaries. Multi-layer AI models spot thermal anomalies, differentiating standard motor workloads from cooling line fluid blockages.
Technician History & Behavior
Every corrective and preventive intervention, every note and every part replacement is logged and learned from — so the model weighs a machine's real maintenance record, not just its sensor feed, before it raises an alert.
Ready to Predict Failures Before They Happen?
Connect your electrical meters, sensors and maintenance history into one model and turn every signal into days of early warning.