STMicroelectronics Releases STM32 Condition-Monitoring Function Pack Leveraging Tools from Cartesiam for Simplified Machine Learning

STMicroelectronics has released a free STM32 software function pack that lets users quickly build, train, and deploy intelligent edge devices for industrial condition monitoring using a microcontroller Discovery kit.

Developed in conjunction with machine-learning expert and ST Authorized Partner Cartesiam, the FP-AI-NANOEDG1 software pack contains all the necessary drivers, middleware, documentation, and sample code to capture sensor data, integrate, and run Cartesiam’s NanoEdge libraries. Users without specialist AI skills can quickly create and export custom machine-learning libraries for their applications using Cartesiam’s NanoEdge AI Studio tool running on a Windows^® 10 or Ubuntu PC. The function pack simplifies complete prototyping and validation free of charge on STM32 development boards, before deploying on customer hardware where standard Cartesiam fees apply.

The straightforward methodology established with Cartesiam uses industrial-grade sensors on-board a Discovery kit such as the STM32L562E-DK to capture vibration data from the monitored equipment both in normal operating modes and under induced abnormal conditions. Software to configure and acquire sensor data is included in the function pack.

NanoEdge AI Studio analyzes the benchmark data and selects pre-compiled algorithms from over 500 million possible combinations to create optimized libraries for training and inference. The function-pack software provides stubs for the libraries that can be easily replaced for simple embedding in the application. Once deployed, the device can learn the normal pattern of the operating mode locally during the initial installation phase as well as during the lifetime of the equipment, as the function pack permits switching between learning and monitoring modes.

Using the Discovery kit to acquire data, generate, train, and monitor the solution, leveraging free tools and software, and the support of the STM32 ecosystem, developers can quickly create a proof-of-concept model at low cost and easily port the application to other STM32 microcontrollers. As an intelligent edge device, unlike alternatives that rely on AI in the cloud, the solution allows equipment owners greater control over potentially sensitive information by processing machine data on the local device.

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