𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Morphological undecimated wavelet decomposition for fault diagnostics of rolling element bearings

✍ Scribed by Rujiang Hao; Fulei Chu

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
838 KB
Volume
320
Category
Article
ISSN
0022-460X

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

ARTIFICIAL NEURAL NETWORK BASED FAULT DI
ARTIFICIAL NEURAL NETWORK BASED FAULT DIAGNOSTICS OF ROLLING ELEMENT BEARINGS USING TIME-DOMAIN FEATURES
✍ B. SAMANTA; K.R. AL-BALUSHI πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 455 KB

A procedure is presented for fault diagnosis of rolling element bearings through artificial neural network (ANN). The characteristic features of time-domain vibration signals of the rotating machinery with normal and defective bearings have been used as inputs to the ANN consisting of input, hidden

A COMPARISON OF AUTOREGRESSIVE MODELING
A COMPARISON OF AUTOREGRESSIVE MODELING TECHNIQUES FOR FAULT DIAGNOSIS OF ROLLING ELEMENT BEARINGS
✍ D.C. Baillie; J. Mathew πŸ“‚ Article πŸ“… 1996 πŸ› Elsevier Science 🌐 English βš– 543 KB

The paper introduces the concept of fault diagnosis using an observer bank of autoregressive time series models. The concept was applied experimentally to diagnose a number of induced faults in a rolling element bearing using the measured time series vibration signal. Three distinct techniques of au

USING THE CORRELATION DIMENSION FOR VIBR
USING THE CORRELATION DIMENSION FOR VIBRATION FAULT DIAGNOSIS OF ROLLING ELEMENT BEARINGSβ€”I. BASIC CONCEPTS
✍ David Logan; Joseph Mathew πŸ“‚ Article πŸ“… 1996 πŸ› Elsevier Science 🌐 English βš– 427 KB

There is a wide variety of condition monitoring techniques currently in use for the diagnosis and prediction of machinery faults, but little attention has been paid to the occurrence and detection of chaotic behaviour in time series vibration signals. This paper introduces some of the basic concepts