Details Details PDF BIBTEX RIS Title Local Fault Assessment in a Helical Geared System via Sound and Vibration Parameters Using Multiclass SVM Classifiers Journal title Archives of Acoustics Yearbook 2016 Volume vol. 41 Issue No 3 Authors Amarnath, Muniyappa Keywords gear ; ANN ; SVM ; vibration ; sound Divisions of PAS Nauki Techniczne Coverage 559-571 Publisher Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics Date 2016 Type Artykuły / Articles Identifier DOI: 10.1515/aoa-2016-0054 Source Archives of Acoustics; 2016; vol. 41; No 3; 559-571 References Chen (2002), Classification of wavelet patterns using multilayer neural networks and, Mech Syst Signal Process, 16, 695, doi.org/10.1006/mssp.2002.1488 ; Cormick (1997), Classification of the rotating machine condition using artificial neural networks Part, Proc Instn Mech Engrs, 211. ; Banerjee (2012), Multi - sensor data fusion using support vector machine for motor fault detection, Information Sciences, 96, 217. ; Sugumaran (2007), Feature selection using decision tree and classification through proximal support vector machine for fault diagnostics of roller bearing, Mech Syst Signal Process, 21, 930, doi.org/10.1016/j.ymssp.2006.05.004 ; Aditya (2016), Feature Extraction and Fault Severity Classification in Ball Bearings of Vibration and Control, Journal, 22, 176. ; Amarnath (2014), Local fault detection in helical gears via vibration and acoustic signals using EMD based statistical parameter analysis, Measurement, 58, 154, doi.org/10.1016/j.measurement.2014.08.015 ; Samanta (2004), Gear fault diagnosis using artificial neural networks and support vector mechanics with genetic algorithms and, Mech Syst Signal Process, 18, 625, doi.org/10.1016/S0888-3270(03)00020-7 ; Collobert (2001), Suport vector machines for large scale regression problems of machine learning research, Journal, 1, 143. ; Hu (2007), Fault diagnosis of rotating machinery based on improved Wavelet packet transform and SVMs ensemble, Mech Syst Signal Process, 21, 688, doi.org/10.1016/j.ymssp.2006.01.007 ; Wang (1995), Application of orthogonal wavelets to early gear damage detection, Mech Syst Signal Process, 5, 497, doi.org/10.1006/mssp.1995.0038 ; Staszewski (1997), Time - frequency analysis in gearbox fault detection using the Wigner - ville distribution and pattern recognition, Mech Syst Signal Process, 11, 673692, doi.org/10.1006/mssp.1997.0102 ; Murray (1997), Extraction of useful higher order features for condition monitoring using artificial neural networks on signal, IEEE Trans process, 45, 2821, doi.org/10.1109/78.650108 ; Amarnath (2013), Exploiting sound signals for fault diagnosis of bearings using decision tree, Measurement, 46, 12501256, doi.org/10.1016/j.measurement.2012.11.011 ; Yang (2005), Condition classification of small reciprocating compressor for refrigerators using artificial neural networks and support vector machines, Mech Syst Signal Process, 19, 371, doi.org/10.1016/j.ymssp.2004.06.002 ; Yang (2002), Third order spectral technique for the diagnosis of motor bearing conditions using artificial neural network, Mech Syst Signal Process, 16, 391, doi.org/10.1006/mssp.2001.1469 ; Paya (1999), Artificial neural network based fault diagnostics of rotating machinery using wavelet transform as a preprocessor, East Mech Syst Signal Process, 11, 751, doi.org/10.1006/mssp.1997.0090 ; Wuxing (2004), Classification of gear faults using cumulants and the radial basis function, Mech Syst Signal Process, 18, 381, doi.org/10.1016/S0888-3270(03)00080-3 ; Yuan (2006), Support vector machines - based fault diagnosis for turbo - pump rotor, Mech Syst Signal Process, 20, 939, doi.org/10.1016/j.ymssp.2005.09.006 ; Demuth (1998), User s guide for neural network toolbox for use with MATLAB The Mathworks Inc, Natick, 3. ; Shin (2005), One class support vector machines - an application in fault detection and classification Computer and, Industrial Engineering, 48, 395, doi.org/10.1016/j.cie.2005.01.009