Overview
Description
RealityCheck™ Motor is an add-on software toolbox that enables conditional monitoring and predictive maintenance functionality without relying on additional sensors. Rather, it uses electrical information from the motor control process as a proxy for vibration and other sensors. With its advanced signal processing and Machine Learning (ML) models, RealityCheck Motor is an add-on to Reality AI Tools® software engineered to create algorithms that detect and classify small fluctuations and anomalies of various conditions like load, vibration and others. It then relates them to known conditions or failure modes and unknown anomalies.
With no external sensors required, RealityCheck Motor enables the detection of minute changes in system parameters that are indicative of anomalies and maintenance issues. This toolbox can be deployed on the endpoint for early detection of faults in a motor system, allowing for timely maintenance, reducing downtime and intensive repair costs.
RealityCheck Motor is designed to work seamlessly with Renesas MCUS, MPUs, and motor-driven applications, enabling hardware optimization and the creation of software models. This software toolbox along with Reality AI Tools software, provides a low-code automated machine learning platform for creating, validating, and deploying sensor classification or prediction models at scale in the targeted Renesas embedded devices of your choice.
By combining advanced signal processing and ML models with internal data, RealityCheck Motor allows for proactive maintenance, reducing the risk of cost-intensive failures and improving overall system reliability. With its ease of use and powerful capabilities, RealityCheck Motor is the perfect toolbox and add-on functionality for those looking to optimize their motor systems and ensure maximum efficiency and uptime.
Features
- Performance optimized, real-time capable and extended data collection engine
- Enables sensorless ML models, reducing product BoM
- Embedded conditional monitoring, predictive maintenance, anomaly detection, and control feedback
Benefits:
- Eliminates unexpected downtime for equipment owners and operators
- Extend equipment lifespan
- Reduces maintenance costs
- Optimizes energy efficiency
Target Devices
Documentation
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Type | Title | Date |
Flyer | PDF 282 KB | |
White Paper | PDF 628 KB 日本語 , 简体中文 | |
2 items
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Design & Development
Related Kits & Tools
Videos & Training
This demonstration shows how the Reality AI Load Detection solution allows a sensorless three-phase brushless DC motor (BLDC) or permanent magnet synchronous motor (PMSM) system to detect its load during startup stress without adding components to the BOM. For more details, visit the Reality AI Tools or RealityCheck Motor pages.
News & Blog Posts
Increase Motor Performance and Reduce Stress with Sensorless Load Detection on Three-Phase BLDC/PMSM Motors | Blog Post | Oct 16, 2024 |
The Future of Digital Motor Control: Multiple Motors, Embedded AI, and Advanced Algorithms on One MCU | Blog Post | Sep 19, 2024 |
Is Your Vacuum Smart Enough to Clean for Real? | Blog Post | Sep 12, 2024 |
How to Maximize the Lifespan of Electric Motors | Blog Post | Jun 29, 2023 |
Problems We Solve
This unique product allows you to detect anomalies in all motor-driven applications, even when the anomalies are not easily detectable by traditional sensors like vibration sensors or temperature sensors. It helps address:
- Load balancing and alignment
- Bearing wear
- Any load monitoring or predictive maintenance application where vibration sensors or accelerometers might traditionally be deployed
Target Applications:
- Consumer appliances
- Industrial machinery and automation
- HVAC systems
- Automotive applications
- Renewable energy systems
- Building automation
- Home appliances
- Adding smart monitoring or predictive maintenance functionality to any motor-driven system