RT-ICM
AI Conditional Monitoring
Motor Current Signature Analysis (MCSA) is an advanced, non-intrusive condition monitoring technique that uses sophisticated algorithms to detect faults in electric motors by analyzing current waveforms while the motors remain in operation. By identifying unique current patterns associated with specific faults, MCSA enables predictive maintenance, minimizes downtime, prevents costly failures, and enhances overall operational efficiency.
AI-based conditional monitoring for motors and pumps
Overview
AI-based condition monitoring system that uses Motor Current Signature Analysis (MCSA) to detect early-stage motor and pump faults — winding, bearing, and shaft issues — purely from the motor's current waveform, without needing intrusive vibration or temperature sensors on the machine itself. The condition monitoring device streams current data to an AI-software layer that scores motor health and flags degradation before it causes downtime, visualized on a live dashboard. Used for predictive maintenance on motors and pumps where unplanned failure is costly to production.