Anomaly Detection

Overview

Anomaly detection is synonym of machine condition monitoring. Early detection of anomalies allows preventive maintenance and avoids production losses. Ideally, an Industry 4.0 factory will be built from scratch with new production machinery and capital investments, but in reality this equipment is usually used for decades. A small and lightweight sensing tag based on the NTAG SmartSensor and a MCU with machine learning capabilities provides a way to add sensory and logging capabilities to existing machinery without disturbing or interfering during normal operations.

Anomaly Detection

Anomaly Detection

RAIN RFID Industry 4.0

RAIN RFID Industry 4.0

Upgrade Existing Industrial Machinery with NTAG<sup>®</sup> SmartSensor

Upgrade Existing Industrial Machinery with NTAG^® SmartSensor

Anomaly Detection Overview

Anomaly Detection Overview

Specifications

Anomaly detection

Anomaly detection

MPU/MCU

NFC

NHS3100 : NTAG^® SmartSensor with Temperature Sensor and Digital IOs

MEMS

MEMS Accelerometer : ±2g/±4g/±8g, Low g, 14-Bit Digital Accelerometer

PMIC

PF4210 : 14-channel power management IC optimized for i.MX 8M

Wi-Fi + Bluetooth

Design Resources

Documents ( 2 )

Users Guide ( 2 )

Documents

Users Guide ( 2 )

Anomaly Detection^{(REV
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This application shows how to use a neural network to search for anomalies in sensors that are in a stationary position.
- PDF
- 541.4 kB
- 14 Jan 2020
- IMXRTADUG
- [ English ]
eIQ Anomaly Detection Custom Case Step-by- Step^{(REV
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This user's guide provides information to replicate setup for AN12766; it includes steps for training the model and converting it to TensorFlow Lite and finally to header file which is exported to application project for i.MX RT1050 board. This guide also describes minimum package requirements for running python scripts. NXP Semiconductors eIQ
- PDF
- 959.0 kB
- 17 Jun 2020
- AN12851
- [ English ]

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