Anomaly Detection
Catch Faults Before They Become Failures
OpSys Anomaly Detection uses multivariate time-series analysis and unsupervised deep learning to identify abnormal behaviour in energy assets and processes — milliseconds after it begins. From partial discharge in MV cables to inverter clipping in solar plants, it surfaces the signal in the noise before equipment damage or revenue loss occurs.
Key Capabilities
Multivariate Anomaly Detection
Autoencoder and LSTM-based models learn normal operating envelopes across hundreds of correlated signals simultaneously.
Real-Time Streaming Analysis
Sub-100ms anomaly scoring on live SCADA and meter data streams using edge-deployed inference engines.
Root Cause Attribution
SHAP and attention-map explanations identify which signals contributed most to each anomaly score.
Adaptive Baselines
Models automatically retrain on rolling windows to adapt to seasonal load changes and equipment aging.
Alarm Rationalisation
Intelligent alarm grouping suppresses nuisance alarms and surfaces only actionable, high-confidence anomalies.
Cross-Asset Correlation
Detects cascading anomalies across interconnected assets (e.g., transformer → cable → switchgear) before they propagate.
Why Choose OpSys Anomaly Detection?
- Detect incipient faults 30–90 days before catastrophic failure
- Reduce false alarm rate by 80% compared to threshold-based alarm systems
- Recover 0.5–2% of annual generation through early inverter and transformer fault detection
- Integrate with OpSys Asset Management for automatic work order creation on anomaly detection
- Comply with NERC PRC reliability standards with automated anomaly event logging
- Deploy at the edge for air-gapped substations with no cloud dependency
Technical Specifications
- Detection Latency
- < 100ms (edge) / < 500ms (cloud)
- Model Architecture
- Autoencoder, LSTM-AE, Isolation Forest, One-Class SVM
- Signal Capacity
- Up to 50,000 tags per deployment
- False Positive Rate
- < 2% with adaptive threshold tuning
- Integration
- OPC-UA, MQTT, REST, IEC 61850 MMS, Historian
- Deployment
- Edge (NVIDIA Jetson), on-premise, or OpSys cloud