Application of ARMA modelling and alpha-stable distribution for local damage detection in bearings

• Autorzy: Żak G. , Obuchowski J. , Wyłomańska A. , Zimroz R.

Warianty tytułu

PL

Zastosowanie modelu ARMA i rozkładu alfa-stabilnego do detekcji uszkodzeń lokalnych w łożyskach

• Języki publikacji: EN

Abstrakty

EN

In this paper a novel method for informative frequency band selection is presented. It is suitable for a vibration signal from a damaged rotating machine which is consisted of a pulse train, but it might be contaminated by other vibrations, often with higher energy. We first decompose the signal into simpler sub-signals and analyze those sub-signals using statistical tools, i.e. autoregressive moving average modelling and fitting of the α -stable distribution. The choice of this distribution is motivated by its excellent ability of modeling heavy-tailed data, i.e impulsive data. We illustrate the proposed methodology by analysis of real vibration signals from heavy-duty rotating machinery. The results prove that this statistical analysis is very efficient in informative frequency band selection in presence of high-energy contamination.

PL

W artykule zaprezentowano nową metodę selekcji informacyjnego pasma częstotliwościowego. Jest ona odpowiednia dla sygnałów drganiowych z maszyny uszkodzonej zawierających impulsy, nawet kiedy są one niewidoczne w dziedzinie czasu, tzn. kiedy wysokoenergetyczne drgania innych elementów zakłócają sygnał informacyjny. Pierwszym krokiem zaproponowanej metody jest dekompozycja sygnału na składowe o prostszej strukturze i ich analiza za pomocą narzędzi statystycznych, tj. modelu ARMA i rozkładu alfa-stabilnego. Wybór tego rozkładu jest umotywowany zdolnością modelowania danych ciężko ogonowych, tzn. sygnałów, w których występują impulsy. Metodę zilustrowano analizą rzeczywistych sygnałów z drganiowych maszyn górniczych. Potwierdzono efektywność zaproponowanej metody statystycznej w kontekście selekcji informacyjnego pasma częstotliwościowego w obecności wysokoenergetycznych zakłóceń.

Słowa kluczowe

EN

local damage detection; informative frequency band selection; time series modeling; heavy-tailed distributions

PL

wykrywanie uszkodzeń lokalnych; wybór pasma informacyjnego; modelowanie szeregów czasowych; rozkłady ciężko-ogonowe

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2014
• Tom: Vol. 15, No. 3
• Strony: 3--10
• Opis fizyczny: Bibliogr. 28 poz., rys., wykr.

Twórcy

autor

Żak G.

• Diagnostics and Vibro-Acoustics Science Laboratory, Wroclaw University of Technology, Na Grobli 15, 50-421 Wroclaw, Poland

autor

Obuchowski J.

• Diagnostics and Vibro-Acoustics Science Laboratory, Wroclaw University of Technology, Na Grobli 15, 50-421 Wroclaw, Poland

autor

Wyłomańska A.

• Hugo Steinhaus Center, Institute of Mathematics and Computer Science, Wroclaw University of Technology, Janiszewskiego 14a, 50-370 Wroclaw, Poland

autor

Zimroz R.

• Diagnostics and Vibro-Acoustics Science Laboratory, Wroclaw University of Technology, Na Grobli 15, 50-421 Wroclaw, Poland

Bibliografia

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