An intelligent system for faulty-bearing detection based on vibration spectra

Abstract

In this paper, a new detection and classification system of faulty bearings is presented. This system is based on artificial intelligent techniques and vibration signals in the frequency domain produced by the faulty bearings. The system consists of several neuro-fuzzy systems in cascade, along with measurement equipment for the vibration spectral data. These neuro-fuzzy systems have been used as bi-classifiers. That is, each neuro-fuzzy system is specialized in the classification between two different types of rolling bearing status. A careful selection process for rules has been included in the learning algorithm. Moreover, the demodulated vibration signal has been used as input to the neuro-fuzzy systems based on the Sugeno approach. Several trials were carried out, taking into account the vibration spectral data collected by the measurement equipment for each bearing. Different results with three types of faulty bearings using the proposed approach are shown, where satisfactory results have been achieved.

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“…There has been increasing interest in computer‐aided ergonomics and its applications in recent years, in a variety of fields such as intelligent algorithms, computation techniques, and so on (Cegarra & Hoc, 2008; Chen, 2009a, 2009b, 2010a, 2010b, 2011a, 2011b, 2011c, 2011d, 2011e, 2011f, 2011g, 2011h, 2011i, 2011j; Chen & Chen, 2010; Chen, Chen & Chiang, 2010, Chen, Chen, Yang, & Chen, 2007; Chen, Lin & Tsai, 2007; Chen, Shen, Chen, & Jeng, 2010; Chen, Wang, & Lin, 2009; Chen, Wang, Liu, & Chen, 2010; Chen, Yeh, Chiang, Chen, & Wu, 2007; Chen, Yeh, & Liu, 2009; Leung, Yucel, & Duffy, 2010; Shih, 2010a, 2010b, 2010c, 2011a, 2011b, 2011c, 2011d, 2011e, 2011f, 2011g; McPherson & White, 2006; Tung, Yuan, & Tsai, 2009, Jayaswal et al, 2011; Marichal et al, 2011; Metin and Guclu, 2011). These computer‐aided techniques are a good way to connect with ergonomics applications.…”

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“…Step 2: Through the FFT algorithm, [15][16][17] computing the main frequency regions of the vibration signal for every operating status of the motor at low and high rotating speeds, respectively.…”

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“…Eventually, (Marichal g. et al, 2010) used the hybrid method to detect the vibration fault of ingoing and over the bearing. They seem to reduce the complexity of a vibration signal by dividing the frequency with the equilateral category.…”

“…Thereafter, these signals were applied to a neural fuzzy system to locate vibrations in the bearing. Finally, they applied these signal to the many stages of the neuro-fuzzy technique, where the results of first network was inputted into the second stage for finding the other kind of vibration that might be generated duration operations [13].…”