7.7.8. Blower Imbalance
Detect blade imbalance in HVAC blowers using 3-phase motor current analysis.
7.7.8.1. Overview
Blade imbalance in HVAC blowers causes increased vibration, noise, and premature bearing wear. This example uses motor current signature analysis to detect imbalance conditions before they cause equipment failure.
Application: HVAC systems, industrial fans, predictive maintenance
Task Type: Time Series Classification
Data Type: Multivariate (3-phase motor currents)
7.7.8.2. Configuration
common:
target_module: 'timeseries'
task_type: 'generic_timeseries_classification'
target_device: 'F28P55'
dataset:
dataset_name: 'blower_imbalance'
training:
model_name: 'FanImbalance_model_1_t'
training_epochs: 50
batch_size: 32
testing: {}
compilation: {}
7.7.8.3. Running the Example
cd tinyml-modelzoo
./run_tinyml_modelzoo.sh examples/blower_imbalance/config.yaml
cd tinyml-modelzoo
run_tinyml_modelzoo.bat examples\blower_imbalance\config.yaml
7.7.8.4. Dataset Details
Input Variables:
Phase A current
Phase B current
Phase C current
Classes:
Normal operation
Blade imbalance detected
7.7.8.5. Recommended Models
Model |
Parameters |
Use Case |
|---|---|---|
|
Varies |
Baseline detection |
|
Varies |
Improved accuracy |
|
Varies |
Maximum accuracy |
7.7.8.6. See Also
Fan Blade Fault Classification - Accelerometer-based fan fault detection