Jerk monitoring, defined as the first derivative of acceleration, has become a major issue in computerized numeric controlled (CNC) machines. Several works highlight the necessity of measuring jerk in a reliable way for improving production processes. Nowadays, the computation of jerk is done by finite differences of the acceleration signal, computed at the Nyquist rate, which leads to low signal-to-quantization noise ratio (SQNR) during the estimation. The novelty of this work is the development of a smart sensor for jerk monitoring from a standard accelerometer, which has improved SQNR. The proposal is based on oversampling techniques that give a better estimation of jerk than that produced by a Nyquist-rate differentiator. Simulations and experimental results are presented to show the overall methodology performance. © 2009 by the authors.
Rangel-Magdaleno, J. J., Romero-Troncoso, R. J., Osornio-Rios, R. A., & Cabal-Yepez, E. (2009). Novel oversampling technique for improving signal-to-quantization noise ratio on accelerometer-based smart Jerk sensors in CNC applications. Sensors, 9(5), 3767–3789. https://doi.org/10.3390/s90503767