Octonion I-CUBE-OCTMI expansion package

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Octonion, a deep tech software company specialising in artificial intelligence (AI) at the edge for industrial-equipment diagnosis, has announced an STM32Cube expansion package optimised for STM32L4+ microcontroller-based industrial-application development boards from semiconductor company STMicroelectronics.

The software package supports ST’s efforts to develop AI-based applications running on STM32 microcontrollers and microprocessors in the condition-based-monitoring and predictive maintenance segments. The package delivers a self-care system running on STM32 ultralow-power MCUs and powered by Octonion’s Edge AI engine that automatically learns, inspects and monitors the health of industrial equipment throughout its operating life.

The expansion pack is optimised for the STM32L4+ development boards which include a range of ST’s industrial-grade sensors and connectivity features, starting from the STWIN SensorTile Wireless Industrial Node. It embeds Octonion’s AI engine operating in an unsupervised mode, continuously analysing data from an accelerometer to handle vibration analysis for condition monitoring and predictive maintenance. The engine does not require any prior knowledge of the equipment or existing dataset. It learns operational modes locally on the microcontroller to fine-tune the embedded Octonion Machine Intelligence algorithm. With all the computation done at the edge, there are no data sent outside, eliminating possible privacy issues.

The expansion pack gives developers access to two ready-to-use algorithms: Instant Analyser for fast-response equipment-health analysis and Wize Analyzer designed for equipment with frequent operational-mode changes. The expansion pack covers a wide range of industrial machines’ behaviours, allowing it to detect spike anomalies and extended dynamic state anomalies on motors of various power classes, including small BLDC, PMSM motors or huge turbines.

The Octonion Edge AI engine coupled with ST’s STM32 MCUs allows industrial organisations to reduce maintenance costs and downtime by easing and accelerating implementation of predictive maintenance solutions with real-time machine health monitoring on all STM32 build-in systems or on ultralow-power STM32 MCUs. Developers can customise different parameters to adapt the embedded AI engine for their specific use case, balancing the quality of equipment-state recognition, its computational complexity and the response speed.

For more information: https://intelligence.octonion.com/st-expansion.