Uncertainty evaluation of low-cost vibration sensors in precision manufacturing applications

Vibration monitoring is one of the key areas of interest in precision manufacturing setups to ensure high level of engineering confidence in manufactured products and associated machinery. Traditionally, high-cost vibration sensors have been employed in industrial manufacturing scenarios. The recent development of industrial grade MEMS based vibration sensors has shown promise in viability offered by such low-cost sensors in metrological applications enabling Industry 4.0. Previous work was conducted to characterize the performance and background noise of measurements from low cost triaxial accelerometers in terms of identifying the parameters that induce uncertainties and baseline errors in measured data. This work expands the study by evaluating uncertainty in measured data of such low-cost vibration sensors according to stochastic (JCGM 100:2008) and Monte Carlo methods (JCGM 101:2008). The recorded data was captured after conducting static and dynamic tests on a calibration test bench using a range of frequencies while establishing traceability according to the ISO 16063-11:1999, ISO 16063-21:2003 and the IEEE 1293-2018 standards. The work investigates uncertainty in measurement by installing the sensors on machine tools and conducting traceability tests. The work also identifies the main aspects which contribute to measurement uncertainty and proposes an improved setup to mitigate effects of uncertainty of such low-cost vibration sensors offering a viable implementation for smart condition monitoring and smart machining purposes.