Real‐time condition monitoring on VSD‐fed induction motors through statistical analysis and synchronous speed observation

Cabal-Yépez, Eduardo; Fernandez‐Jaramillo, Arturo A.; García-Pérez, Arturo; Romero‐Troncoso, Rene J.; García, José Merced Lozano

doi:10.1002/etep.1938

Cited by 28 publications

(11 citation statements)

References 48 publications

(97 reference statements)

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“…According to information entropy theory in Saffet and Zhao et al, the atomic singular entropy is defined, the calculation equation can be described as

S_{j} = - true {true\sum}_{q = 1}^{b} u_{italicjq} ln u_{italicjq}

…”

Section: Basic Selection Theoriesmentioning

confidence: 99%

An adaptive fault line selection method based on atomic comprehensive measure values for distribution network

Wei

Yang

Wen

et al. 2016

Int. Trans. Electr. Energ. Syst.

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Summary In this article, an adaptive fault line selection method based on atomic comprehensive measures for a distribution network is proposed. Firstly, wavelet denoising is introduced to remove the noise contained in the transient zero‐sequence current; then, the matching pursuit algorithm is utilized to decompose the denoising transient zero‐sequence current. Moreover, based on singular value decomposition and information entropy, the atomic singular entropy values are computed, and the actual energy of feature atoms are obtained. Furthermore, according to the fuzzy mathematics, the fault comprehensive measurement function is built. Finally, the line that has the maximum of the fault comprehensive measure value is chosen as the fault line. A large number of simulation experiments and comparing results proved that the proposed method has high selection accuracy and reliability, as well as a powerful ability to resist noise.

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“…According to information entropy theory in Saffet and Zhao et al, the atomic singular entropy is defined, the calculation equation can be described as

S_{j} = - true {true\sum}_{q = 1}^{b} u_{italicjq} ln u_{italicjq}

…”

Section: Basic Selection Theoriesmentioning

confidence: 99%

An adaptive fault line selection method based on atomic comprehensive measure values for distribution network

Wei

Yang

Wen

et al. 2016

Int. Trans. Electr. Energ. Syst.

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show abstract

“…The burgeoning use of IMs in the industries is standing upon the pillars of efficient, continual, and cost‐effective operation of bearings. So, to have the incessant production, flawless operation of bearings is imperative . Here, condition monitoring, commonly known as predictive maintenance, steps in.…”

Section: Introductionmentioning

confidence: 99%

Detection and diagnosis of induction motor bearing faults using multiwavelet transform and naive Bayes classifier

Saini

Aggarwal

2018

Int Trans Electr Energ Syst

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Summary A novel framework is proposed for the classification of motor bearing faults by using multiwavelet transform and naive Bayes classifier. This work has explored the application of multiwavelet transform to the vibration signatures for extracting the effective fault features. Geronimo‐Hardin‐Massopust multiwavelet filter bank has been employed in this work for multiresolution analysis up to fourth decomposition level. This work has relied upon multiwavelets as the multiwavelets are enriched with the properties which wavelets do not offer simultaneously like compact support and orthogonality without compromising with symmetricity and higher order of vanishing moments. After that, fault features have been extracted from the decomposed vibration signals to utilize the fault information present at different resolution levels. The fault classification has been accomplished with high success rate by using the extracted fault features with the naive Bayes classifier due to its inherent features like robustness to noise, simplicity, and quick convergence even with less training data. The efficacy of the proposed classifier has been verified with both the offline signals and the real‐time signals having different fault severity levels. The outperformance of the proposed classifier has been shown by comparing the classification results with other established supervised classification techniques like probabilistic neural network, Gaussian‐support vector machine, polynomial‐support vector machine, and linear‐support vector machine.

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“…The improvement was challenged by the problems of controlling a DC motor during fault conditions [8]. Any unscheduled shutdown due to the faults in the induction motor can be disruptive to the high levels of production process at industrial plants.…”

Section: Introductionmentioning

confidence: 99%

“…The prevailing situation in industry is to connect induction motors to the power supply though Variable Speed Drives (VSD's), which introduce harmonics into the current supply signal that makes the fault identification highly difficult [12].The Discrete Wavelet Transform was used to drive the different harmonics component of stator currents. The various advanced signal processing techniques such as Fast Fourier Transform, Short Time Fourier Transform, Gabor Transform, and Wavelet Transform are used to diagnose the faults of induction motor.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Fault Analysis and Speed Control of an Induction Motor using Motor Solver

Sengamalai¹,

Subramani²

2017

Journal of Electrical Engineering and Technology

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-This paper deals with the performance analysis of three phase induction motor considering its stator side faults and operating thermal limits. The speed control of induction motor using three phase boost converter operated by a MOSFET switch and a PI controller is demonstrated and presented in this article. IGBTs switches are used for inverter drive mechanism .The experimental result of speed control of induction motor using voltage control technique clearly shows better accuracy than conventional methods of speed control. A three phase 1HP 415V 0.78 kW 4 Pole induction motor is designed using motor solver software. Based on the parameters used in the software thermal analysis of induction motor is done and torque variation with conductor area, efficiency, output curve, losses in different parts of motor has been obtained. Also different types of faults namely under voltage, over voltage, stator imbalanced voltage, turn to turn, locked rotor bar, wrong alignment of rotor bar with respect to stator are studied and fault analysis is performed. Hence comparison is made based upon the results obtained before and after faults.

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Real‐time condition monitoring on VSD‐fed induction motors through statistical analysis and synchronous speed observation

Cited by 28 publications

References 48 publications

An adaptive fault line selection method based on atomic comprehensive measure values for distribution network

An adaptive fault line selection method based on atomic comprehensive measure values for distribution network

Detection and diagnosis of induction motor bearing faults using multiwavelet transform and naive Bayes classifier

An Experimental Fault Analysis and Speed Control of an Induction Motor using Motor Solver

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