Canary Edge ships with a powerful generic model that works out of the box. For production workloads, setting a baseline for each machine fine-tunes a dedicated predictor that learns the specific patterns of your equipment.
When to Set a Baseline
- Your time series has unique seasonal patterns
- The generic model produces too many false positives
- You need maximum sensitivity for critical equipment
- You want regime classification (HEALTHY/ACTIVE/TRANSITION/SHOCK)
How It Works
- Send normal operating data via
POST /v1/baseline with a machine_id
- Canary Edge computes energy statistics and trains a lightweight predictor (~462K params) in seconds
- Future detection calls with that
machine_id use the fine-tuned model automatically
- Detection accuracy typically improves from ~82% (generic) to 97%+ (fine-tuned)
Setting a Baseline
curl -X POST https://api.canaryedge.com/v1/baseline \
-H "Content-Type: application/json" \
-H "Ocp-Apim-Subscription-Key: YOUR_API_KEY" \
-d '{
"machine_id": "pump-assembly-1",
"energies": [0.12, 0.15, 0.11, 0.13, 0.14, 0.12, 0.16, 0.11, ...]
}'
Only send energy scores from normal operating data for baseline creation. Including anomalous data will degrade detection accuracy.
Checking a Baseline
curl "https://api.canaryedge.com/v1/baseline?machine_id=pump-assembly-1" \
-H "Ocp-Apim-Subscription-Key: YOUR_API_KEY"
Response:
{
"machine_id": "pump-assembly-1",
"mean": 0.132,
"std": 0.018,
"p99": 0.187,
"sample_count": 500,
"created_at": "2026-03-15T10:00:00Z"
}
Requirements
- Minimum 100 energy values for a reliable baseline
- Data should represent at least one full operational cycle
- All data should be from normal, healthy operation
Machine Status
Once a baseline is set, check machine status:
curl "https://api.canaryedge.com/v1/status/pump-assembly-1" \
-H "Ocp-Apim-Subscription-Key: YOUR_API_KEY"
Deleting a Machine
To remove a baseline and revert to the generic detector:
curl -X DELETE "https://api.canaryedge.com/v1/machines/pump-assembly-1" \
-H "Ocp-Apim-Subscription-Key: YOUR_API_KEY"