Galileo Sensight.AI/Power is a solution for acquiring and analyzing multichannel measurements on three-phase systems, electric motors, generators, inverters and photovoltaic plants.
Its AI-based Anomaly Detection module automatically detects anomalous behavior in the monitored signals in real time, triggering safety procedures through the PLC when needed.
Artificial intelligence for industrial electrical monitoring
Three-phase electrical systems need continuous monitoring to prevent costly failures and ensure operating efficiency. Anomalies often appear as slow drifts or subtle variations that are hard to detect with fixed thresholds and take specialist skills to interpret. Sensight.AI/Power fully automates this process using proprietary AI algorithms that adapt dynamically to operating conditions.
Main features
The system combines high-frequency multichannel acquisition with intelligent real-time analysis.
AI-based anomaly detection
- Proprietary algorithms for automatic recognition of anomalous behavior
- Joint analysis of all channels for complex correlations
- Adaptive thresholds calculated automatically, with no manual intervention
Power Quality (PQ) analysis
- Real-time monitoring of imbalances, harmonics and distortion
- Precise calculation of active power P and reactive power Q
- Frequency and angle reference assessment
Direct PLC interface
- Digital outputs for immediate activation of safety procedures
- Real-time communication with existing control systems
- Automatic recording of raw data during anomalous events
Automatic configuration
- Immediate setup with no complex manual parameter setting
- Fast reconfiguration for new operating scenarios
- Dynamic adaptation to changes in process conditions
Advantages over the traditional approach
Conventional systems require thresholds and complex logic to be defined by hand, with significant limitations in dynamic scenarios.
| Traditional approach | With Sensight.AI/Power |
|---|---|
| Thresholds defined by hand for each measurement | Adaptive thresholds calculated automatically by AI |
| Separate analysis of each parameter | Joint multivariate analysis with correlations |
| Manual reconfiguration at every change | Automatic reconfiguration when the scenario changes |
| Difficulty detecting slow drifts | Optimized detection of progressive drifts and offsets |
| Limits on the number of monitored channels | Practically unlimited scalability |
Typical configuration
The system is based on a CompactRIO architecture to ensure real-time determinism and industrial reliability.
Hardware components
| Component | Specifications |
|---|---|
| cRIO NI-9064 | Dual-core ARM CPU, Xilinx Artix-7 FPGA, 4 C Series slots, Ethernet |
| NI-9239 | 4-channel analog acquisition, ±10V, 24 bit, 50 kS/s per channel |
| NI-9421 | 8-channel digital input, 24V, PLC interface |
| NI-9474 | 8-channel digital output, 24V sourcing, 500µs response time |
Software and platform
- Environment: LabVIEW RT/FPGA for real-time determinism
- Supported OS: LabVIEW Real-Time on CompactRIO
- Note: embedded architecture for autonomous operation with no Internet connection
Applications and fields of use
The AI technology is optimized for scenarios where anomalies cannot be defined in advance through fixed thresholds.
Energy and photovoltaics
- Monitoring of photovoltaic plant inverters to optimize production
- Real-time detection of voltage, current and power anomalies
- Power Quality analysis to prevent faults and maximize reliability
Automotive and electric mobility
- Testing of electric vehicle inverters on test benches
- Monitoring of charging systems during development and validation
- Characterizing electric motor performance under operating conditions
Generation and distribution
- Monitoring of industrial generators and micro-grids
- Analysis of storage and electrical distribution systems
- Detection of imbalances and distortion on complex three-phase networks
Technical specifications
| Feature | Details |
|---|---|
| Acquisition channels | Configurable through NI C Series modules |
| Analog resolution | 24 bit with NI-9239 modules |
| Sampling rate | Up to 50 kS/s per channel |
| Anomaly response time | < 500 µs to activate digital outputs |
| AI configuration | Automatic, in a single training phase |
| PLC interface | Isolated 24V digital I/O |
| Determinism | Real-time guaranteed by integrated FPGA |
| Operation | Fully autonomous, offline |
System requirements
| Requirement | Details |
|---|---|
| Power supply | 24VDC via CompactRIO |
| Connectivity | Ethernet for configuration and supervision |
| Operating environment | Industrial, per CompactRIO specifications |
| Required software | LabVIEW RT/FPGA for custom development |
Why choose Sensight.AI/Power
Sensight.AI/Power removes the complexity of manual parameter setting in electrical monitoring systems, offering built-in intelligence that is transparent to the user.
Our long experience in industrial measurements and data analysis ensures solutions that bring real improvements, designed to be immediate and intuitive in the field. The system stands out for its ability to adapt dynamically to changing operating scenarios, drastically reducing setup and maintenance time compared with traditional solutions. The combination of proprietary AI and the CompactRIO platform ensures industrial reliability and real-time performance for mission-critical applications.