The embedded AI (e-AI) technology is used to predict failures based on motor abnormality. Data showing the motor’s current or rotation rate status is valuable for abnormality detection, meaning that motor control and abnormality detection can be accomplished by a single MCU. RX66T also eliminates the need for additional sensors, further reducing BoM cost.
e-AI-based motor control-based detection can trigger alarms when a fault occurs, and also be used for preventive maintenance - estimating when repairs and maintenance should be performed.
Renesas Failure Detection e-AI Solution can control up to four motors using the high-performance RX66T MCU. The solution comprises Renesas’ Motor Control Evaluation System and an RX66T CPU card, which is combined with a set of sample program files that run on the RX66T MCU, and a GUI tool for collecting and analyzing property data indicating motor states. To detect faults, it is necessary to learn the characteristics of the normal state. The GUI tool allows engineers to begin developing AI learning and optimized fault detection functionality. Once the AI models are developed, the e-AI development environment can be used to import the learned AI models into the RX66T.