Detecting abnormal vibration patterns in rotating machinery such as motors, pumps, fans, and compressors. Learns normal vibration signatures using autoencoders or statistical models and flags deviations indicating bearing wear, shaft imbalance, or misalignment. Runs on constrained MCUs attached directly to equipment housings. Extremely resource-efficient — the model processes accelerometer data windows and outputs a binary normal/anomaly classification.
| Minimum RAM | 32 KB |
| Minimum Flash | 256 KB |
| Sensor Inputs | accelerometer |
| Typical Model Size | 15 KB (quantized int8) |
| Minimum Clock | 48 MHz |
No hardware guides for vibration anomaly detection yet. Use the MCU Checker to find compatible hardware.
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