Recognition of rotor damages in a DC motor using acoustic signals

Journal title

Bulletin of the Polish Academy of Sciences Technical Sciences






No 2


Divisions of PAS

Nauki Techniczne






DOI: 10.1515/bpasts-2017-0023 ; ISSN 2300-1917


Bulletin of the Polish Academy of Sciences: Technical Sciences; 2017; 65; No 2; 187-194


Wang (2016), Multi - scale morphology analysis of acoustic emission signal and quantitative diagnosis for bearing fault, Acta Mechanica Sinica, 44, 265. ; Perun (2015), Evaluation of state of rolling bearings mounted in vehicles with use of vibration signals of Metallurgy and, Archives Materials, 60, 1679. ; Van Hecke (2016), Low speed bearing fault diagnosis using acoustic emission sensors, Applied Acoustics, 35, 35, ; Hachaj (2016), Application of neural network for human actions recognition Computational Intelligence and Intelligent Systems ISICA in Computer and Information, Communications Science, 54, 575. ; Koprowski (2016), Some selected quantitative methods of thermal image analysis in Matlab of, Journal Biophotonics, 9, 510, ; Hemmati (2016), Roller bearing acoustic signature extraction by wavelet packet transform applications in fault detection and size estimation, Applied Acoustics, 42, 101, ; Głowacz (2016), Diagnostics of stator faults of the single - phase induction motor using thermal images MoASoS and selected classifiers, Measurement, 11, 86, ; Gorny (2015), Methodology for the construction of a rule - based knowledge base enabling the selection of appropriate bronze heat treatment parameters using rough sets of Metallurgy and, Archives Materials, 61, 309. ; Jedlinski (2015), Application of vibration signal in the diagnosis of IC engine valve clearance of, Journal Vibroengineering, 17, 175. ; Augustyniak (2014), Seamless tracing of human behavior using complementary wearable and house - embedded sensors, Sensors, 49, 7831, ; Patan (2008), Artificial neural networks for the modelling and fault diagnosis of technical processes Notes in Control and Information, Lecture Sciences, 1, 377. ; Michalak (2016), Diagnostic model for longwall conveyor engines Man - Machine Interactions, ICMMI, 391. ; Mika (2016), Normative measurements of noise at CNC machines work stations in Science and Technology Research, Advances Journal, 10, 138. ; Głowacz (2015), Recognition of acoustic signals of synchronous motors with the use of MoFS and selected classifiers, Measurement Science Review, 36, 167. ; Kunicki (2016), Study on descriptors of acoustic emission signals generated by partial discharges under laboratory conditions and in on - site electrical power transformer of, Archives Acoustics, 33, 265. ; Li (2016), Fault diagnosis for rotating machinery using vibration measurement deep statistical feature learning, Sensors, 19. ; Głowacz (2007), Simulation language for analysis of discrete - continuous electrical systems SESL Proceedings of the th IASTED International Conference on Modelling Identification and Control Innsbruck, Austria, 94. ; Yadav (2015), A novel transmission line relaying scheme for fault detection and classification using wavelet transform and linear discriminant analysis Ain Shams, Engineering Journal, 57, 199. ; Singh (2016), Induction motor inter turn fault detection using infrared thermographic analysis &, Infrared Physics Technology, 77. ; Jena (2015), Automatic gear and bearing fault localization using vibration and acoustic signals, Applied Acoustics, 34, 20, ; Palacios (2015), da A comprehensive evaluation of intelligent classifiers for fault identification in three - phase induction motors, Electric Power Systems Research, 56, 127. ; Duan (2016), Segmented infrared image analysis for rotating machinery fault diagnosis &, Infrared Physics Technology, 77. ; Sebok (2011), Diagnostics of electric equipments by means of thermovision Elektrotechniczny, Przegląd, 87, 313. ; Skrickij (2016), Diagnostic features for the condition monitoring of hypoid gear utilizing the wavelet transform, Applied Acoustics, 41, 51, ; Dudek (2009), Neural network adaptation process effectiveness dependent of constant training data availability, Neurocomputing, 50, 13. ; Jamroz (2015), Application of multidimensional data visualization by means of self - organizing Kohonen maps to evaluate classification possibilities of various coal types of, Archives Mining Sciences, 53, 39. ; Panek (2015), Acoustic analysis assessment in speech pathology detection and, International Journal of Applied Mathematics Computer Science, 52, 631. ; Wilk (2016), Comparative analysis of the properties of the nodular cast iron with carbides and the austempered ductile iron with use of the machine learning and the support vector machine, International Journal of Advanced Manufacturing Technology, 60, 1. ; Jiang (2016), On the bi - dimensional variational decomposition applied to nonstationary vibration signals for rolling bearing crack detection in coal cutters and Technology, Measurement Science, 27, ; Valis (2016), System condition estimation based on selected tribodiagnostic data Quality and Reliability, Engineering International, 47, 635. ; Li (2016), Detection of gear cracks in a complex gearbox of wind turbines using supervised bounded component analysis of vibration signals collected from multi - channel sensors of and, Journal Sound Vibration, 26, 371. ; Deptuła (2016), Acoustic diagnostics applications in the study of technical condition of combustion engine of, Archives Acoustics, 29, 345. ; Frigieri (2016), A mel - frequency cepstral coefficient - based approach for surface roughness diagnosis in hard turning using acoustic signals and Gaussian mixture models, Applied Acoustics, 62, 113. ; Deptuła (2016), Decision support system for identifying technical condition of combustion engine of, Archives Acoustics, 41, 449, ; Li (2016), Recent progress on decoupling diagnosis of hybrid failures in gear transmission systems using vibration sensor signal : A review, Measurement, 90, 4, ; Roj (2015), Method of measurement of capacitance and dielectric loss factor using artificial neural networks, Measurement Science Review, 51, 127. ; Głowacz (2016), Recognition of acoustic signals of induction motors with the use of MSAF and Bayes classifier of Metallurgy and, Archives Materials, 40, 153. ; Ciszewski (2016), Current - based higher - order spectral covariance as a bearing diagnostic feature for induction motors, Insight, 5, 431. ; Bowen (2016), Systemic health evaluation of RF generators using Gaussian mixture models &, Computers Electrical Engineering, 63, 13, ; He (2016), A new signal processing and feature extraction approach for bearing fault diagnosis using AE sensors of Failure Analysis and Prevention, Journal, 43, 821. ; Islam (2016), Discriminant feature distribution analysis - based hybrid feature selection for online bearing fault diagnosis in induction motors of Article No, Journal Sensors, 48, 2016. ; Stanik (2015), Effective methods for the diagnosis of vehicles rolling bearings wear and damages of Metallurgy and, Archives Materials, 60, 1717. ; Caesarendra (2016), Acoustic emission - based condition monitoring methods : Review and application for low speed slew bearing Mechanical Systems and, Signal Processing, 28, 73. ; Carletti (2016), Vibroacoustic measurements and simulations applied to external gear pumps An integrated simplified approach of, Archives Acoustics, 41, 285, ; Józwik (2016), Identification and monitoring of noise sources of CNC machine tools by acoustic holography methods in Science and Technology Research, Advances Journal, 32, 127. ; Lara (2015), Influence of constructive parameters and power signals on sound quality and airborne noise radiated by inverter - fed induction motors, Measurement, 27, 73. ; Delgado (2017), Methodology for fault detection in induction motors via sound and vibration signals Mechanical Systems and, Signal Processing, 37, 83. ; Henao (2014), et Trends in fault diagnosis for electrical machines a review of diagnostic techniques Industrial, IEEE Electronics Magazine, 8, 31, ; Jun (2014), Investigations of thermocouple drift irregularity impact on error of their inhomogeneity correction, Measurement Science Review, 55, 29. ; Hwang (2015), Support vector machine based bearing fault diagnosis for induction motors using vibration signals of & Technology, Journal Electrical Engineering, 18, 1558. ; Hameyer (2016), o Fault diagnosis of bearing damage by means of the linear discriminant analysis of stator current features from the frequency selection Transactions on Industry Applications, IEEE, 58, 3861. ; Głowacz (2015), Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier of, Archives Electrical Engineering, 64, 29,