caa a22 4500 605470081 CHVBK 20210128100326.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00500-014-1326-5 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1326-5 Anfis model for vibration signals based on aging process in electric motors [Elektronische Daten] [Duygu Bayram, Serhat Şeker] In this study, the aging process of an electric motor is accomplished by adaptive neuro-fuzzy inference system (ANFIS) using vibration signals. Different ANFIS models are compared for representing the aging process in the best possible way. An artificial aging experiment is performed and vibration data taken from the initial (healthy) and final (faulty) cases are used to identify the aging process. Four different ANFIS models are presented. Moving average (MA) filters are applied to the input and output pairs for different lagging factors to change the smoothness degree of the data and thus the performance of system identification. The success of the models is evaluated on three conditions; the performance of the ANFIS and the linear correlation between expected output (faulty case data) and aging model output, in time and frequency domains.The study also evaluates the influence of preprocessing using MA filtering on the ANFIS performance for vibration data which have stochastic characteristics. Springer-Verlag Berlin Heidelberg, 2014 ANFIS nationallicence Electric motor nationallicence Aging nationallicence Correlation coefficient nationallicence Moving average nationallicence Spectral analysis nationallicence Bayram Duygu Electrical Engineering Department, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey aut Şeker Serhat Electrical Engineering Department, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey aut Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 1107-1114 1432-7643 19:4<1107 2015 19 500 https://doi.org/10.1007/s00500-014-1326-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1326-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bayram Duygu Electrical Engineering Department, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey aut NATIONALLICENCE 700 1- Şeker Serhat Electrical Engineering Department, Istanbul Technical University, Maslak, 34469, Istanbul, Turkey aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/4(2015-04-01), 1107-1114 1432-7643 19:4<1107 2015 19 500