Motor Failure Detection with e-AI

This demonstration shows that one Renesas MCU realizes motor control and fault detection for an application simultaneously. e-AI discovers an application fault through the abnormal state of motor. Abnormal state of motor is detected by the acceleration sensor, also by current, torque and rotation speed which are the information stored in the motor control MCU. e-AI makes motor control more intelligent, predicts the maintenance schedule, identifies the location of the failure, and realizes the endpoint in real time.

 

Added on 10月 02, 2018

This demonstration shows motor control and fault detection with a Renesas MCU.


1:15
Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.
1:15
Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.
1:15
Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.

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Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.
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1:15
Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.
1:45
This demonstration shows an AI unit solution connected to actual equipment, where an abnormality judgment is made.
1:10
This video demonstrates predictive maintenance of equipment through the use of e-AI.
1:09
This video shows a demonstration of a biological monitoring solution for home healthcare applications.
2:17
This video provides a demonstration of the biomedical information monitor module.
1:51
This video shows a demonstration of a parking lot management system coordinating with peripheral devices.
1:21
Using a printer as an example, this video shows a device forecasting its own failure.
1:15
Embedded AI (e-AI) makes motor control more intelligent. This demonstration shows motor control and fault detection with a Renesas MCU.
1:45
This demonstration shows an AI unit solution connected to actual equipment, where an abnormality judgment is made.
1:10
This video demonstrates predictive maintenance of equipment through the use of e-AI.
1:09
This video shows a demonstration of a biological monitoring solution for home healthcare applications.
2:17
This video provides a demonstration of the biomedical information monitor module.
1:51
This video shows a demonstration of a parking lot management system coordinating with peripheral devices.
1:21
Using a printer as an example, this video shows a device forecasting its own failure.