Normalization of vibration signals generated under highly varying speed and load with application to signal separation

Jacek Urbanek, Tomasz Barszcz, Marcin Strączkiewicz, Adam Jablonski

Research output: Contribution to journalArticle

Abstract

The paper presents a normalization dedicated to transform non-stationary vibration signals into signals characterized by purely stationary properties. For this purpose, a novel class of generalized periodic signals is defined followed by a proposition of a normalization technique, which takes advantage of available, instantaneous values of operational parameters. Within the paper, a well-known discrete-random separation (DRS) technique is recalled as an exemplary technique, which has been restricted to stationary signals so far. The authors present a step-by-step adoption of the DRS to non-stationary signals. The method is applied to simulated signal, test rig signal, and a vibration signal from industrial object. Additionally, for the purpose of synthesis of simulated signal, a new model of multi-component vibrations generated under varying regime is proposed. The presented method aims to expand existing solutions dealing with varying frequency to a more general solution dealing with independent, simultaneous varying frequency and amplitude of signal components.

Original languageEnglish (US)
Pages (from-to)13-31
Number of pages19
JournalMechanical Systems and Signal Processing
Volume82
DOIs
StatePublished - Jan 1 2017

Keywords

  • Non-stationary signals analysis
  • Signal separation
  • Varying operational conditions
  • Vibration signal modeling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Normalization of vibration signals generated under highly varying speed and load with application to signal separation. / Urbanek, Jacek; Barszcz, Tomasz; Strączkiewicz, Marcin; Jablonski, Adam.

In: Mechanical Systems and Signal Processing, Vol. 82, 01.01.2017, p. 13-31.

Research output: Contribution to journalArticle

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