Recognition of acoustic signals of induction motor using FFT, SMOFS-10 and LSVM

Abstract

Article citation info: (*) Tekst artykułu w polskiej wersji językowej dostępny w elektronicznym wydaniu kwartalnika na stronie www.ein.org.pl IntroductionThe induction motors are used in various industries such as: mining, fuel, metallurgical. These motors have low maintenance and low price. To reduce maintenance costs scientists analyze mechanical properties of materials [18,20,25,30].They also develop early fault detection methods [1,5,6,[10][11][12][13][14][15]. Especially non-invasive methods are developed such as : acoustic, vibrations, thermal, magnetic [3, 14, 19, 27, 28, 29, 35, 36, 38]. Noninvasive methods are capable to diagnose early faults without disassembly the induction motor. Many of them used patterns recognition and signal processing to identify type of fault.Incipient faults of motors may change into damages and may stop the production line. The stopped production line causes losses of resources and production time. It increases the cost of operation and maintenance.This article deals with a recognition method of early faults of induction motor. Proposed method uses Fast Fourier Transform (FFT), shortened method of radio frequencies selection (SMoFS-10) and Linear Support Vector Machine (LSVM). Proposed approach of recognition of acoustic signal of induction motorThe proposed approach of recognition of acoustic signal of induction motor contained two processes: a pattern creation process and an identification process. These processes were needed for proper recognition of acoustic signal (Fig. 1).The first of them recorded acoustic signal of motor with the help of a sound card and a microphone [22]. Acoustic signal was converted GLOWACZ A. Recognition of acoustic signals of induction motor using ffT, smOfs-10 and Lsvm. Eksploatacja i Niezawodnosc -maintenance and Reliability 2015; 17 (4)

Introduction to Special Issue on Symmetry in Mechanical Engineering

“…The presented solutions, methods, and approaches can be improved and used in the future. Moreover, mechanical engineering is essential for fault diagnosis of machines [10][11][12][13][14][15][16][17][18][19][20][21][22] and the analysis of temperature [23][24][25]. The mechanical properties of materials are also investigated in the literature [26][27][28].…”

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“…The proposed topics are essential for industry. Signal processing and analysis of diagnostic signals are used for fault diagnosis and monitoring systems [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. Signal processing and image processing methods are used for many applications, for example medical applications [27][28][29][30][31][32][33][34][35][36].…”

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