Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/35431
Title: Stability-based system for bearing fault early detection
Authors: Diaz, Moises 
Henriquez, P. 
Ferrer Ballester, Miguel Ángel 
Pirlo, Giuseppe
Alonso Hernández, Jesús Bernardino 
Carmona Duarte, María Cristina 
Impedovo, Donato
UNESCO Clasification: 3325 Tecnología de las telecomunicaciones
Keywords: Bearing fault detection
Direct matching points
Dynamic time warping
Stability analysis
Issue Date: 2017
Journal: Expert Systems with Applications 
Abstract: This paper presents a new and straightforward system for bearing fault detection. The system computes the stability of two vibration signals by using the direct matching points (DMP) of an elastic and nonlinear align function. It is able to find discriminant properties in the stability of fault-free and faulty bearing vibration signals from the early and late stages of the fault in critical bearing parts. Because training data constitutes one of the critical challenges in most expert and intelligent systems, one of the novelties of the proposed stability-based system is that it requires neither training nor fine-tuning. A significant impact on the robustness of the system is demonstrated using two publicly available vibration signal databases under several load conditions, with real faults, during multiple machine working states. Experimental results validate the use of the proposed stability-based system for predictive maintenance in bearings.
URI: http://hdl.handle.net/10553/35431
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2017.02.030
Source: Expert Systems with Applications[ISSN 0957-4174],v. 79, p. 65-75
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