Sensor solution with integrated machine learning core (MLC) to recognize activity, or to categorize audio signals into predetermined classes with Acoustic Scene Classification (ASC)
Features
- Multi-sensing wireless platform implementing vibration monitoring and ultrasound detection
- Development platform and reference design that simplifies prototyping and testing of advanced industrial IoT applications such as condition monitoring and predictive maintenance
- Built around STMicroelectronics STWIN core system board with processing, sensing, connectivity and expansion capabilities
Applications / Use Cases
Industrial IoT applications with condition monitoring and predictive maintenance, including:
- Motor control with condition monitoring
- Ball bearing crack detection
- Gas leak detection
Motor control with condition monitoring
Measure the condition of a motor with multiple sensors to measure temperature, vibration, sound, and analyze all the sensor data to define the condition of a motor and to predict when the motor can fail
Measure the condition of a motor with multiple sensors to measure temperature, vibration, sound, and analyze all the sensor data to define the condition of a motor and to predict when the motor can fail
Ball bearings crack detection
Analyze vibration on ball bearings to predict if the ball bear will break. Ball bearings faults are one of the main causes of breakdown of rotating machines. Detection and diagnosis of mechanical faults in ball bearings are crucial for the reliable operation
Analyze vibration on ball bearings to predict if the ball bear will break. Ball bearings faults are one of the main causes of breakdown of rotating machines. Detection and diagnosis of mechanical faults in ball bearings are crucial for the reliable operation
Gas leak detection
Detect gas leakage with ultrasound inspection and condition monitoring
Detect gas leakage with ultrasound inspection and condition monitoring
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