What does complete predictive machine maintenance look like?

At Sensor Expo 2019, Edoardo Gallizio from product marketing for MEMS & Sensors in the Americas at STMicroelectronics demonstrates a complete predictive maintenance reference design. Multiple sensors are part of the monitoring where some sensors are mounted directly on a spinning wheel to continuously measure vibration. The sensors gather the data, a microprocessor accesses the situation and then the results are transmitted through a Predictive Maintenance Node to Cloud gateway. A cloud dashboard displays the real-time results including pressure, temperature, humidity, motor revolutions and system anomalies. Key aspects of the reference design include the STEVAL-BFA001V1B, STEVAL-IHM042V1 and STEVAL-IDP004V1 evaluation kits as well as Amazon Web Service (AWS) connectivity.

The STEVAL-BFA001V1B is an industrial reference design kit designed for condition monitoring (CM) and predictive maintenance (PdM). It includes an industrial sensor board (STEVAL-IDP005V1), an adapter for the ST-LINK/V2-1 programming and a debugging tool (STEVAL-UKI001V1). In addition, firmware package includes dedicated algorithms for advanced time and frequency domain signal processing and analysis of a 3D digital accelerometer with 3 kHz flat bandwidth. Drivers for pressure, relative humidity and temperature sensor monitoring as well as audio algorithms for acoustic emissions are also part of the package.

The STEVAL-IHM042V1 is a complete dual motor field-oriented control (FOC) demonstration platform that includes a 32-bit microcontroller (MCU) with floating point support and two fully integrated DMOS L6230 3-phase motor drivers.

The STEVAL-IDP004V1 evaluation kit has 4 L6360 IO-Link master devices that are managed by a 32-bit MCU.

AWS connectivity allows the data to be displayed at a remote and/or local location for monitoring and control.