Fault diagnosis of rotating machinery using compression sensing and order analysis

Abstract

Sound and vibration are widely used in the diagnosis of rotating machinery failures. However, one of the challenges is the increasing amount of measured data. Therefore, we are building a method to identify spectra at measurement frequencies other then the Nyquist frequency using compressed sensing. By improving the conventional method and combining order analysis using rotation measurement, we have succeeded in reducing the number of measurement points and improving performance of compressed sensing, and this paper will report on the evaluation results.