Online Instantaneous Angular Speed Estimation from Vibration Data on Low-Power Embedded Systems Evaluated on a Gas Foil Bearing

This study presents an algorithm for estimating the instantaneous angular speed (IAS) from vibrations in low-power embedded systems, evaluated on the use-case of a gas foil bearing. While there are numerous methods for IAS estimation, they have thus far only been evaluated using industrial-grade sensors and data acquisition systems with high computational resources. To boost the application of IAS estimation methods in embedded applications, like sensor-integrating machine elements, this paper highlights and evaluates an algorithm for low-power embedded systems. Theoretical analysis and benchmarks on various low-power microcontrollers demonstrate its feasibility for real-time application. Furthermore, evaluation with lower sampling rates and ADC resolutions confirms compatibility with small-scale sensors typical in embedded systems. For good performance, a typical Cortex-M4-based MCU (e.g. 1.12 ms estimation time using 1024 data points) and a sensor with 8-bit resolution and 6400 Hz sampling rate would suffice. These findings establish the algorithm's readiness for diverse embedded applications.     «

This study presents an algorithm for estimating the instantaneous angular speed (IAS) from vibrations in low-power embedded systems, evaluated on the use-case of a gas foil bearing. While there are numerous methods for IAS estimation, they have thus far only been evaluated using industrial-grade sensors and data acquisition systems with high computational resources. To boost the application of IAS estimation methods in embedded applications, like sensor-integrating machine elements, this paper h...     »