Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals

Abstract In this paper, a non-invasive method of early fault diagnostics of electric motors was proposed. This method uses acoustic signals generated by electric motors. Essential features were extracted from acoustic signals of motors. A plan of study of acoustic signals of electric motors was proposed. Researches were carried out for faultless induction motor, induction motor with one faulty rotor bar, induction motor with two faulty rotor bars and flawless Direct Current, and Direct Current motor with shorted rotor coils. Researches were carried out for methods of signal processing: log area ratio coefficients, Multiple signal classification, Nearest Neighbor classifier and the Bayes classifier. A pattern creation process was carried out using 40 samples of sound. In the identification process 130 five-second test samples were used. The proposed approach will also reduce the costs of maintenance and the number of faulty motors in the industry.

[1]  Piotr Augustyniak,et al.  Seamless Tracing of Human Behavior Using Complementary Wearable and House-Embedded Sensors , 2014, Sensors.

[2]  Marek R. Ogiela,et al.  CAD system for automatic analysis of CT perfusion maps , 2011 .

[3]  K. Czopek,et al.  Cardiac Activity Based on Acoustic Signal Properties , 2012 .

[4]  Andrzej Mamala,et al.  Evaluation of the Effect of Selected Alloying Elements on the Mechanical and Electrical Aluminium Properties , 2014 .

[5]  Adam Glowacz,et al.  Recognition of monochrome thermal images of synchronous motor with the application of quadtree decomposition and backpropagation neural network , 2014 .

[6]  Adam Glowacz,et al.  Recognition of Monochrome Thermal Images of Synchronous Motor with the Application of Binarization and Nearest Mean Classifier , 2014 .

[7]  P. Korohoda,et al.  Wavelet-like decomposition stage with windowed filters defined for the Discrete Trigonometric Transforms (DTTs) , 2012 .

[8]  W. Głowacz,et al.  Diagnostics of Induction Motor Based on Spectral Analysis of Stator Current with Application of Backpropagation Neural Network , 2013 .

[9]  Ewa Skrodzka,et al.  Effect of Bass Bar Tension on Modal Parameters of a Violin's Top Plate , 2015 .

[10]  Piotr Augustyniak,et al.  A cardiac telerehabilitation application for mobile devices , 2011, 2011 Computing in Cardiology.

[11]  Ryszard Tadeusiewicz,et al.  Neural network adaptation process effectiveness dependent of constant training data availability , 2009, Neurocomputing.

[12]  Marek R. Ogiela,et al.  Application of neural networks in detection of abnormal brain perfusion regions , 2013, Neurocomputing.

[13]  Una Sofilić,et al.  Natural Radioactivity in Steel Slag Aggregate , 2011 .

[14]  Dariusz MAzurkiewicz.  Computer-aided maintenance and reliability management systems for conveyor belts , 2014 .

[15]  Marek R. Ogiela,et al.  Graph-Based Semantic Description in Medical Knowledge Representation and 3D Coronary Vessels Recognition , 2007, UIC.

[16]  Adam Glowacz,et al.  Diagnostics of Synchronous Motor Based on Analysis of Acoustic Signals with the use of Line Spectral Frequencies and K-nearest Neighbor Classifier , 2015 .

[17]  Tomasz Tokarski,et al.  Microstructure and Plasticity of Hot Deformed 5083 Aluminum Alloy Produced by Rapid Solidification and Hot Extrusion , 2012 .

[18]  Chengwei Huang,et al.  Speech Emotion Recognition under White Noise , 2013 .

[19]  A. Smalcerz,et al.  Aspects of application of industrial robots in metallurgical processes , 2013 .

[20]  Dariusz Pleban.  Definition and Measure of the Sound Quality of the Machine , 2015 .

[21]  Andrzej Nowicki,et al.  Mathematical and Ultrasonographic Model of the Left Ventricle : in Vitro Studies , 2012 .

[22]  Bartosz Przysucha,et al.  Statistical Analysis of the Equivalent Noise Level , 2015 .

[23]  M. Dytczak,et al.  Is explicit processing of fuzzy direct influence evaluations in DEMATEL indispensable? , 2013, Expert Syst. Appl..

[24]  David VAlis.  Utilization of diffUsion processes and fUzzy logic for vUlnerability assessment Wykorzystanie procesó W dyfUzyjnych i logiki rozmytej do oceny podatności na zagrożenie , 2014 .

[25]  Andrzej Glowacz,et al.  Towards Robust Visual Knife Detection in Images: Active Appearance Models Initialised with Shape-Specific Interest Points , 2012, MCSS.

[26]  C. Su,et al.  Reliability assessment for wind turbines considering the influence of wind speed using bayesian network , 2014 .

[27]  Ninoslav Zuber,et al.  Gearbox faults identification using vibration signal analysis and artificial intelligence methods , 2014 .

[28]  J. Falkus,et al.  The Prediction of Hardenability using Neural Networks , 2014 .

[29]  Piotr Walendowski,et al.  Zastosowanie sieci neuronowych typu SVM do rozpoznawania mowy , 2008 .

[30]  R. Tadeusiewicz,et al.  Processing of pathological changes in speech caused by dysarthria , 2005, 2005 International Symposium on Intelligent Signal Processing and Communication Systems.

[31]  David Valis,et al.  Engine residual technical life estimation based on tribo data , 2014 .

[32]  Piotr Augustyniak,et al.  Wireless body area network system based on ECG and accelerometer pattern , 2011, 2011 Computing in Cardiology.

[33]  Z. Głowacz,et al.  Detection of synchronous motor inter-turn faults based on spectral analysis of park's vector , 2013 .

[34]  Wojciech Batko,et al.  Verification of the Calculation Assumptions Applied to Solutions of the Acoustic Measurements Uncertainty , 2015 .

[35]  P. Andris,et al.  Magnetic Field Variations Near Weak Magnetic Materials Studied by Magnetic Resonance Imaging Techniques , 2012, IEEE Transactions on Magnetics.

[36]  Piotr Panek,et al.  Silicon solar cells efficiency improvement by the wet chemical texturization in the HF/HNO3/diluent solution , 2013 .

[37]  Waleed H. Abdulla,et al.  Speaker Identification Based on Log Area Ratio and Gaussian Mixture Models in Narrow-Band Speech: Speech Understanding / Interaction , 2004, PRICAI.

[38]  I. Frollo,et al.  Magnetic Resonance Imaging of Surgical Implants Made from Weak Magnetic Materials , 2013 .

[39]  Ninoslav Zuber,et al.  Relations between pulverizing process parameters and beater wheel mill vibration for predictive maintenance program setup , 2014 .