Gabor and the Wigner-Ville transforms for broken rotor bars detection in induction motors

Martinez-Herrera, Ana L.; Ledesma-Carrillo, Luis M.; Lopez–Ramirez, Misael; Salazar-Colores, Sebastián; Cabal-Yépez, Eduardo; García-Pérez, Arturo

doi:10.1109/conielecomp.2014.6808572

Cited by 17 publications

(16 citation statements)

References 12 publications

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“…The WT capabilities are significantly degraded in noisy signals, and the mother wavelet has to be appropriately chosen to obtain reliable results [4]. On the other hand, the WVD introduces cross-term interference in the estimated signal components, which inhibits the efficient estimation of the instantaneous frequencies, besides suffering aliasing problem [18]. The HHT suffers from the mode mixing effect, which means that waves with the same frequency are assigned to different intrinsic mode functions, affecting the accurate estimation of the instantaneous frequencies.…”

Section: Introductionmentioning

confidence: 99%

Shannon Entropy andK-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals

Camarena-Martinez

Valtierra-Rodríguez

Amezquita-Sanchez

et al. 2016

Shock and Vibration

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For industry, the induction motors are essential elements in production chains. Despite the robustness of induction motors, they are susceptible to failures. The broken rotor bar (BRB) fault in induction motors has received special attention since one of its characteristics is that the motor can continue operating with apparent normality; however, at certain point the fault may cause severe damage to the motor. In this work, a methodology to detect BRBs using vibration signals is proposed. The methodology uses the Shannon entropy to quantify the amount of information provided by the vibration signals, which changes due to the presence of new frequency components associated with the fault. For automatic diagnosis, theK-means cluster algorithm and a decision-making unit that looks for the nearest cluster through the Euclidian distance are applied. Unlike other reported works, the proposal can diagnose the BRB condition during startup transient and steady state regimes of operation. Additionally, the proposal is also implemented into a field programmable gate array in order to offer a low-cost and low-complex online monitoring system. The obtained results demonstrate the proposal effectiveness to diagnose half, one, and two BRBs.

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Section: Introductionmentioning

confidence: 99%

Shannon Entropy andK-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals

Camarena-Martinez

Valtierra-Rodríguez

Amezquita-Sanchez

et al. 2016

Shock and Vibration

Self Cite

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“…This was proposed by Gabor who had developed the STFT, the extended version of FT [86].

\begin{matrix} T1 \\ {STFT}_{x} (t, w) = {false\int}_{- \infty}^{\infty} x (τ) w (τ - t) e^{- 2 π f τ} d τ, \end{matrix}

where x ( τ ) is the EMG signal, w ( τ − t ) is the observation window, and t is the variable that slides the window over the signal, x ( τ ).…”

Section: Electromyography Processingmentioning

confidence: 99%

EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

Shair

Ahmad

Marhaban

et al. 2017

BioMed Research International

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Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications.

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“…Among the different faults occurred into the induction motor, BRB are a silent failure, since it allows This project was partially supported by the Mexican Council on Science and Technology (CONACyT) by the scholarship 289377, and the Council on Science and Technology of Queretaro (CONCYTEQ) + Corresponding author: jamezquita@uaq.mx operating to the motor with apparent normality; however, this fault produces a progressive fracture of the other bars, causing excessive vibrations, higher thermal stress, and current overconsumption [2]. For these reasons, an early detection of this failure is an imperative task because it will allow scheduling maintenance operations in order to minimize its impact During the last decade, different vibration and current analysis-based approaches for broken bars detection have been proposed, being the most popular: the fast Fourier transform (FFT) [3], [4], multiple signal classification (MUSIC) algorithm [5], [6], wavelet transform (WT) [7]- [10], HilbertHuang transform (HHT) [11], [12], and Wigner-Ville distribution (WVD) [13], [14]. Despite providing useful results, the aforementioned methods present some unresolved difficulties.…”

Section: Introductionmentioning

confidence: 99%

Compact kernel distribution-based approach for broken bars detection on induction motors

Perez-Ramirez

Amezquita-Sanchez

Domínguez-González

et al. 2015

2015 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)

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Induction motors, important elements into the industry, are susceptible to faults during its lifetime service; yet, they can keep working without affecting the process, but increasing the production costs as they consume more electrical current. Broken rotor bars (BRB) detection is an important topic due to the fact that this failure is silent and produces a power consumption increasing, vibration, or introduction of spurious frequencies in the electric line, among others. In this regard, a monitoring system that can efficiently diagnose the induction motor condition is highly required. In this work, a new methodology for one and two broken bars detection is presented. First, the compact kernel distribution (CKD) algorithm, a new high resolution time-frequency algorithm, is introduced for the detection of anomalies produced by the BRB failure in the startup current signal by considering that these signals describe changes on its dynamic characteristics due to the fault; then, the variance, a statistical feature, of the signal processed by CKD determines in automatic way the induction motor condition. The obtained results show a high overall efficiency for detecting broken rotor bars as well as healthy condition

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Gabor and the Wigner-Ville transforms for broken rotor bars detection in induction motors

Cited by 17 publications

References 12 publications

Shannon Entropy andK-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals

Shannon Entropy andK-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals

EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

Compact kernel distribution-based approach for broken bars detection on induction motors

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