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Shock and Vibration
Volume 2017, Article ID 3698370, 11 pages
https://doi.org/10.1155/2017/3698370
Research Article

Data-Driven Iterative Vibration Signal Enhancement Strategy Using Alpha Stable Distribution

1Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Science and Technology, Na Grobli 15, 50-421 Wrocław, Poland
2KGHM Cuprum Research & Development Center, Ul. Sikorskiego 2-8, 53-659 Wrocław, Poland

Correspondence should be addressed to Grzegorz Żak; lp.ude.rwp@kaz.zrogezrg

Received 12 June 2017; Accepted 26 July 2017; Published 12 September 2017

Academic Editor: Andrzej Katunin

Copyright © 2017 Grzegorz Żak et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The authors propose a novel procedure for enhancement of the signal to noise ratio in vibration data acquired from machines working in mining industry environment. Proposed method allows performing data-driven reduction of the deterministic, high energy, and low frequency components. Furthermore, it provides a way to enhance signal of interest. Procedure incorporates application of the time-frequency decomposition, -stable distribution based signal modeling, and stability parameter in the time domain as a stoppage criterion for iterative part of the procedure. An advantage of the proposed algorithm is data-driven, automative detection of the informative frequency band as well as band with high energy due to the properties of the used distribution. Furthermore, there is no need to have knowledge regarding kinematics, speed, and so on. The proposed algorithm is applied towards real data acquired from the belt conveyor pulley drive’s gearbox.