Ruben Puche-Panadero

TL;DR: This paper shows how the evolution of other non-fault-related components such as the principal slot harmonic (PSH) can be extracted with the proposed technique.

TL;DR: Advanced signal-and-data-processing algorithms consist of a proper sample selection algorithm, a Hilbert transformation of the stator-sampled current, and spectral analysis via FFT of the modulus of the resultant time-dependent vector modulus for achieving MCSA efficiently.

TL;DR: It is shown that, in the case of machines with one or several broken bars, the IF of the LSHst exhibits a very characteristic and easy to identify pattern, which is physically justified, and a universal fault indicator can be defined.

TL;DR: The use of the fractional FT (FrFT) instead of the FT to perform TMCSA and the optimization of the FrFT to generate a spectrum where the frequency-varying fault harmonics appear as single spectral lines and, therefore, facilitate the diagnostic process.

TL;DR: In this article, a new method for demodulating the stator current prior to its spectral analysis is proposed, using the Teager-Kaiser energy operator, which is able to remove the mains component of the current with an extremely low usage of computer resources.