Detection of Adjacent and Non-Adjacent Bar Breakages in Induction Motors Based on Power Spectral Subtraction and Second Order Statistics of Sound Signals

Martínez, Miguel; Córdoba, Pedro Fernández de; Antonino-Daviu, José A.; Conejero, J. Alberto

doi:10.3390/app10196641

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…The range and applications of diagnostics, where magnetic effects are used today, are mostly in the area of energetics, where there are strong fields near the object of measurement. Some of the experiments show that there are possibilities to follow the energy flow with the help of acoustic noise [45,46], heat and mechanical oscillations [47][48][49][50]. The subjects of measurements are often stationary devices without rotating parts.…”

Section: Introductionmentioning

confidence: 99%

Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

et al. 2021

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The magnetic field created by technical devices is a source of information. This information could be used in contactless diagnostics and predictive maintenance or for resolving problems along with standard NDT (nondestructive testing) methods, especially if we consider large, slow-speed devices, such as electromotors, transmissions, or generators. Identification of causalities of device failure processes with near magnetic field is one of the suitable NDT methods improving sustainability of systems. The measurements presented in the article were performed with the VEMA 04 fluxgate vector magnetometer with the DC-250 Hz bandwidth and 2 nT sensitivity. Postprocessing of the results was performed in the means of standard methods of discrete Fourier Transform, spectrogram creation and Wavelet Transform. The article presents data gathered during the measurement of a pair of extraction fans with power of 140 kW each and maximum revolutions up to 740 rev/min controlled by frequency converters and a single semi-Kaplan water power plant with 400 kW peak power at 1005 rev/min maximum generator speed. The measurements were performed before and after repairs of one of the ventilators in the ventilation system at 60% and 100% of maximal output power. The rotating magnetic fields of the fan electromotor stator, fan rotor revolutions, rotor slip frequency and ball-bearing frequencies were identified in frequency spectrums in the distance of 700 mm from fan electromotor axis in both cases. During the measurements on the semi-Kaplan turbine, the changes in states of mechanical and electrical components of the machine were monitored in the magnetic fields with increase of the power in the range of 0–95%, before and after phasing to the electrical grid. Standard processing methods, Discrete Fourier Transform, spectrograms and Discrete Wavelet Transform were used. In the spectrograms of the measured magnetic fields, the 1st–4th harmonics of the turbine shaft, generator shaft and also their side frequencies were identified. Significant changes of magnetic fields in time were identified in the area of 60–95% power. With the help of the Wavelet, transform intervals were identified where it is desirable to operate the turbine. The analyses of magnetic fields measurements performed on the power plant were compared with vibro-diagnostic principles.

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Section: Introductionmentioning

confidence: 99%

Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

et al. 2021

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“…Furthermore, failure detection methods based on higher-order statistical analysis have been applied to vibration signals, by considering the information provided by cumulants and moments of orders greater than or equal to two, as well as the spatial information that extracted from the analysis of higher-order spectra such as the bispectrum [29,30,33,34,50,63,66]. In addition to statistical estimators such as variance, kurtosis and skewness, derived from the cumulants of second, third, and fourth orders respectively are performed.…”

Section: Introductionmentioning

confidence: 99%

Higher-Order Spectral Analysis of Stray Flux Signals for Faults Detection in Induction Motors

Martínez

Antonino-Daviu

Córdoba

et al. 2020

Applied Mathematics and Nonlinear Sciences

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AbstractThis work is a review of current trends in the stray flux signal processing techniques applied to the diagnosis of electrical machines. Initially, a review of the most commonly used standard methods is performed in the diagnosis of failures in induction machines and using stray flux; and then specifically it is treated and performed the algorithms based on statistical analysis using cumulants and polyspectra. In addition, the theoretical foundations of the analyzed algorithms and examples applications are shown from the practical point of view where the benefits that processing can have using HOSA and its relationship with stray flux signal analysis, are illustrated.

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Evaluation and Classification of Double Bar Breakages Through Three-Axes Vibration Sensor in Induction Motors

Göktaş

2022

IEEE Sensors J.

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Detection of Adjacent and Non-Adjacent Bar Breakages in Induction Motors Based on Power Spectral Subtraction and Second Order Statistics of Sound Signals

Cited by 4 publications

References 45 publications

Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

Low-Frequency Magnetic Fields in Diagnostics of Low-Speed Electrical and Mechanical Systems

Higher-Order Spectral Analysis of Stray Flux Signals for Faults Detection in Induction Motors

Evaluation and Classification of Double Bar Breakages Through Three-Axes Vibration Sensor in Induction Motors

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