An empirical re-sampling method on intrinsic mode function to deal with speed variation in machine fault diagnostics

To implement traditional order tracking in practice requires rotational speed information. However, it may be difficult in some cases to mount an appropriate monitoring device to obtain reliable speed information. In this paper, a novel empirical re-sampling of intrinsic mode functions obtained from empirical mode decomposition is explored, so that the approximation of order tracking effects without rotational speed is possible. The newly introduced intrinsic cycle concept in the intrinsic mode function simplifies linking of the resultant spectra to signal variations, and is therefore beneficial for condition monitoring of rotating machines. In the paper the rationale behind the technique is first explained. Secondly, the effectiveness of the technique is demonstrated on a dynamic gear simulation model. Lastly, the technique is applied to experimental data from a gearbox test rig. Both the simulation and experimental studies corroborate the usefulness of the proposed technique.

► We developed a novel empirical re-sampling method on intrinsic mode function, namely intrinsic cycle re-sampling (ICR), to exclude speed variation effects in the measured rotating machine vibration data.
► We used gear mesh simulation model as well as experimental gear box test rig to validate the proposed method.
► The ICR method approximates computed order tracking effects in spectra analysis and proves to be an effective condition monitoring tool for fault diagnosis with the absence of rotational speed.