Open AccessBook
The vibration analysis handbook
TLDR
The transducer output is proportionate to how fast the machine is moving (frequency) and how much the machine was moving (amplitude), the frequency describes what is wrong with the machine and the amplitude describes relative severity of the problem as discussed by the authors.Abstract:
The physical movement or motion of a rotating machine is normally referred to as vibration. Since the vibration frequency and amplitude cannot be measured by sight or touch, a means must be employed to convert the vibration into a usable product that can be measured and analyzed. Electronics, mechanics, and chemical physics are closely related. Therefore, it would logically follow that the conversion of the mechanical vibration into an electronic signal is the best solution. The means of converting the mechanical vibration into an electronic signal is called a transducer. The transducer output is proportionate to how fast the machine is moving (frequency) and how much the machine is moving (amplitude). The frequency describes what is wrong with the machine and the amplitude describes relative severity of the problem. The motion can be harmonic, periodic, and/or random. All harmonic motion is periodic. However, all periodic motion is not harmonic. Random motion means the machine is moving in an unpredictable manner.read more
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Journal ArticleDOI
Neural-network-based motor rolling bearing fault diagnosis
TL;DR: Simulation and real-world testing results obtained indicate that neural networks can be effective agents in the diagnosis of various motor bearing faults through the measurement and interpretation of motor bearing vibration signatures.
Journal ArticleDOI
Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine
TL;DR: In this article, the authors used wavelet analysis and support vector machine (SVM) for multi-fault detection in an electric motor with two rolling bearings, one of them was next to the output shaft and the other one was near the fan and for each of them there is one normal form and three false forms, which make 8 forms for study.
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Basic vibration signal processing for bearing fault detection
S.A. McInerny,Y. Dai +1 more
TL;DR: This module is one of two laboratory modules focusing on machine condition monitoring applications that were developed for this course, and constitutes an instructional module on bearing fault detection that can be used as a stand-alone tutorial or incorporated into a course.
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Dynamic model of a deep-groove ball bearing including localized and distributed defects. Part 1: Theory:
Jussi Sopanen,Aki Mikkola +1 more
TL;DR: In this article, the authors proposed a dynamic model of a deep-groove ball bearing with six degrees of freedom, which includes descriptions of non-linear Hertzian contact deformation and elastohydrodynamic (EHD) fluid film.
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Automatic bearing fault diagnosis based on one-class ν -SVM
TL;DR: The results showed that the method was able not only to detect the failure in an incipient stage but also to identify the location of the defect and qualitatively assess its evolution over time.