Machine learning and multiresolution decomposition for embedded applications to detect short-circuit in induction motors

[1]  Vijander Singh,et al.  RELATIVE WAVELET ENERGY AS A NEW FEATURE EXTRACTOR FOR SLEEP CLASSIFICATION USING EEG SIGNALS , 2012 .

[2]  Yu Zhang,et al.  Experimental Investigation of Machine Learning Based Fault Diagnosis for Induction Motors , 2018, 2018 IEEE Industry Applications Society Annual Meeting (IAS).

[3]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[4]  Lorand Szabo,et al.  Induction Machine Bearing Fault Detection by Means of Statistical Processing of the Stray Flux Measurement , 2015, IEEE Transactions on Industrial Electronics.

[5]  Atila Girao De Oliveira,et al.  Neural Network Used to Stator Winding Interturn Short-Circuit Fault Detection in an Induction Motor Driven by Frequency Converter , 2013, 2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence.

[6]  Nicholas D. Lane,et al.  Squeezing Deep Learning into Mobile and Embedded Devices , 2017, IEEE Pervasive Computing.

[7]  Alexander E Prosvirin,et al.  Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers , 2020, Sensors.

[8]  Hagit Messer,et al.  Suboptimal detection of non-Gaussian signals by third-order spectral analysis , 1990, IEEE Trans. Acoust. Speech Signal Process..

[9]  Abdelhamid Benakcha,et al.  Early detection and localization of stator inter-turn faults based on discrete wavelet energy ratio and neural networks in induction motor , 2020 .

[10]  A.H. Bonnett,et al.  Increased Efficiency Versus Increased Reliability , 2008, IEEE Industry Applications Magazine.

[11]  Gil Alterovitz,et al.  Accelerating wrapper-based feature selection with K-nearest-neighbor , 2015, Knowl. Based Syst..

[12]  Robert X. Gao,et al.  A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing , 2017, Chinese Journal of Mechanical Engineering.

[13]  Gérard-André Capolino,et al.  Advances in Diagnostic Techniques for Induction Machines , 2008, IEEE Transactions on Industrial Electronics.

[14]  Jorge Luis Victória Barbosa,et al.  Machine learning and reasoning for predictive maintenance in Industry 4.0: Current status and challenges , 2020, Comput. Ind..

[15]  Gérard-André Capolino,et al.  Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art , 2015, IEEE Transactions on Industrial Electronics.

[16]  Vladimir Vapnik,et al.  Support-vector networks , 2004, Machine Learning.

[17]  Carlo Concari,et al.  Differential Diagnosis Based on Multivariable Monitoring to Assess Induction Machine Rotor Conditions , 2008, IEEE Transactions on Industrial Electronics.

[18]  Ivo Paixao de Medeiros,et al.  Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling , 2018, Comput. Ind. Eng..

[19]  Carlo Vercellis,et al.  Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms , 2021, Comput. Ind..

[20]  Jeevanand Seshadrinath,et al.  Incipient Inter-turn Fault Diagnosis in Induction motors using CNN and LSTM based Methods , 2018, 2018 IEEE Industry Applications Society Annual Meeting (IAS).

[21]  Cláudio Marques de Sá Medeiros,et al.  Detection and classification of faults in induction generator applied into wind turbines through a machine learning approach , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

[22]  F. Harris.  On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[23]  Ukashatu Abubakar,et al.  Induction motor fault detection based on multi-sensory control and wavelet analysis , 2020 .

[24]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Marcin Wolkiewicz,et al.  Electrical Fault Diagnostic System Based on the Kohonen Neural Network Classifier , 2018, 2018 International Symposium on Electrical Machines (SME).

[26]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[27]  D. A. Asfani,et al.  Three-Phase Induction Motor Short Circuit Stator Detection Using an External Flux Sensor , 2020, 2020 International Seminar on Intelligent Technology and Its Applications (ISITIA).

[28]  Pascal Maussion,et al.  Electrical Aging of the Insulation of Low-Voltage Machines: Model Definition and Test With the Design of Experiments , 2013, IEEE Transactions on Industrial Electronics.

[29]  João Paulo Papa,et al.  Design of robust pattern classifiers based on optimum-path forests , 2007, ISMM.

[30]  H. Henao,et al.  Detection of stator short-circuit in induction machines using an external leakage flux sensor , 2004, 2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT '04..

[31]  Thyago P. Carvalho,et al.  A systematic literature review of machine learning methods applied to predictive maintenance , 2019, Comput. Ind. Eng..

[32]  Victor Hugo C. de Albuquerque,et al.  A reliable approach for detection of incipient faults of short-circuits in induction generators using machine learning , 2018, Comput. Electr. Eng..

[33]  Elias Teodoro da Silva Júnior,et al.  Toward an Embedded Application to Identify Degradation in Energized Polymeric Insulators using Discrete Wavelet Transform , 2018, 2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP).