Preprint Article Version 1 This version is not peer-reviewed

Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines

Version 1 : Received: 31 July 2019 / Approved: 5 August 2019 / Online: 5 August 2019 (03:56:26 CEST)

A peer-reviewed article of this Preprint also exists.

Burriel-Valencia, J.; Puche-Panadero, R.; Martinez-Roman, J.; Sapena-Baño, A.; Riera-Guasp, M.; Pineda-Sánchez, M. Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines. Energies 2019, 12, 3361. Burriel-Valencia, J.; Puche-Panadero, R.; Martinez-Roman, J.; Sapena-Baño, A.; Riera-Guasp, M.; Pineda-Sánchez, M. Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines. Energies 2019, 12, 3361.

Journal reference: Energies 2019, 12, 3361
DOI: 10.3390/en12173361

Abstract

Induction machines drive many industrial processes, and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not the case for wind generators, motors driving varying loads, etc. In these cases an analysis in the time-frequency domain -such as a spectrogram- is required for detecting faults signatures. The spectrogram is built using the short frequency Fourier transform, but its resolution depends critically on the time window used to generate it: short windows provide good time resolution, but poor frequency resolution, just the opposite than long windows. Therefore, the window must be adapted at each time to the shape of the expected fault harmonics, by highly skilled maintenance personnel. In this paper, this problem is solved with the design of a new multi-band window, which generates simultaneously many different narrow-band current spectrograms, and combines them into a single, high resolution one, without the need of manual adjustments. The proposed method is validated with the diagnosis of bar breakages during the start-up of a commercial induction motor.

Subject Areas

fault diagnosis; induction motors; wind energy generation; fourier transforms; spectral 16 analysis; spectrogram; transient regime

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