A Harmonic Wavelets Approach for Extracting Transient Patterns From Measured Rotor Vibration Data

2002 ◽  
Vol 125 (1) ◽  
pp. 81-89 ◽  
Author(s):  
V. C. Chancey ◽  
G. T. Flowers ◽  
C. L. Howard
Keyword(s):  
Fourier Transform ◽  
Vibration Analysis ◽  
Transient Effects ◽  
Harmonic Wavelets ◽  
Vibration Data ◽  
Harmonic Wavelet ◽  
Vibration Signature ◽  
The Fourier Transform ◽  
Traditional Approaches

Vibration analysis is a powerful diagnostic tool for rotating machinery problems. Traditional approaches to vibration signature analysis have focused on the Fourier transform, which tends to average out transient effects. Recent work in the area of wavelets has allowed for the characterization of signals in frequency and in time, which, if properly interpreted, can provide substantial insight, particularly with regard to transient behaviors. There are many different types of wavelets, but the harmonic wavelet was developed specifically for vibration analysis. It uses an algorithm based upon the fast Fourier transform (FFT), which makes it particularly attractive to many in the vibration analysis community. This paper considers the harmonic wavelet as a tool for extracting transient patterns from measured vibration data. A method for characterizing transient behaviors using the harmonic wavelet is described and illustrated with simulation and experimental results.

A Harmonic Wavelets Approach for Extracting Transient Patterns From Measured Rotor Vibration Data

2001 ◽  
Author(s):  
Valeta Carol Chancey ◽  
George T. Flowers ◽  
Candice L. Howard
Keyword(s):  
Vibration Analysis ◽  
Transient Effects ◽  
Rotor Vibration ◽  
Harmonic Wavelets ◽  
Vibration Data ◽  
Harmonic Wavelet ◽  
Vibration Signature ◽  
The Fourier Transform ◽  
Traditional Approaches

Vibration analysis is a powerful diagnostic tool for rotating machinery problems. Traditional approaches to vibration signature analysis have focused on the Fourier transform, which tends to average out transient effects. Recent work in the area of wavelets has allowed for the characterization of signals in frequency and in time, which, if properly interpreted, can provide substantial insight, particularly with regard to transient behaviors. There are many different wavelets, but the harmonic wavelet was developed specifically for vibration analysis. It uses an algorithm based upon the FFT, which makes it particularly attractive to many in the vibration analysis community. This paper considers the harmonic wavelet as a tool for extracting transient patterns from measured vibration data. A method for characterizing transient behaviors using the harmonic wavelet is described and illustrated using simulation and experimental results.

Characterization of Transient Effects in Rotordynamic Vibrations Using Harmonic Wavelets

1999 ◽  
Author(s):  
Valeta Carol Chancey ◽  
George T. Flowers
Keyword(s):  
Steady State ◽  
Journal Bearing ◽  
Wavelet Coefficients ◽  
Transient Effects ◽  
State Behavior ◽  
Absolute Value ◽  
Harmonic Wavelets ◽  
Oil Whirl ◽  
Harmonic Wavelet

Abstract Traditional vibration analysis methods for rotating machinery consider steady state or near steady state behavior. Perhaps a key to identifying the source of some complex behaviors may be the transients associated with such phenomena. In an effort to develop a means of identifying transients, the application of harmonic wavelets is explored. Simple vibratory models were studied using harmonic wavelet analysis. Several general observations were made with characteristics found in the harmonic wavelet coefficients associated with particular behavior. Specifically, a relationship with transient growth and the absolute value of the harmonic wavelet coefficients was identified. Example experimental data was collected and analyzed from a bench top test rig with a journal bearing exhibiting oil whirl to illustrate the proposed methods.

Pego everywhere

2016 ◽  
Vol 15 (04) ◽  
pp. 1650074 ◽  
Author(s):  
Przemysław Górka ◽  
Tomasz Kostrzewa
Keyword(s):  
Fourier Transform ◽  
Abelian Groups ◽  
General Version ◽  
Pontryagin Duality ◽  
Locally Compact ◽  
Locally Compact Abelian Groups ◽  
Compact Abelian Groups ◽  
The Fourier Transform ◽  
Compact Subsets

In this note we show the general version of Pego’s theorem on locally compact abelian groups. The proof relies on the Pontryagin duality as well as on the Arzela–Ascoli theorem. As a byproduct, we get the characterization of relatively compact subsets of [Formula: see text] in terms of the Fourier transform.

scholarly journals Classification of Hydroacoustic Signals Based on Harmonic Wavelets and a Deep Learning Artificial Intelligence System

2020 ◽  
Vol 10 (9) ◽  
pp. 3097
Author(s):  
Dmitry Kaplun ◽  
Alexander Voznesensky ◽  
Sergei Romanov ◽  
Valery Andreev ◽  
Denis Butusov
Keyword(s):  
Fourier Transform ◽  
Deep Learning ◽  
Feature Space ◽  
Roc Curves ◽  
Harmonic Wavelets ◽  
Intelligence System ◽  
Stationary Signals ◽  
Harmonic Wavelet ◽  
Short Time

This paper considers two approaches to hydroacoustic signal classification, taking the sounds made by whales as an example: a method based on harmonic wavelets and a technique involving deep learning neural networks. The study deals with the classification of hydroacoustic signals using coefficients of the harmonic wavelet transform (fast computation), short-time Fourier transform (spectrogram) and Fourier transform using a kNN-algorithm. Classification quality metrics (precision, recall and accuracy) are given for different signal-to-noise ratios. ROC curves were also obtained. The use of the deep neural network for classification of whales’ sounds is considered. The effectiveness of using harmonic wavelets for the classification of complex non-stationary signals is proved. A technique to reduce the feature space dimension using a ‘modulo N reduction’ method is proposed. A classification of 26 individual whales from the Whale FM Project dataset is presented. It is shown that the deep-learning-based approach provides the best result for the Whale FM Project dataset both for whale types and individuals.

Preparation and Characterization of Heparin-Immobilized Poly(Ether Urethanes)

2011 ◽  
Vol 393-395 ◽  
pp. 236-239
Author(s):  
Li Ming Lian ◽  
Bing Leng ◽  
Xiao Hua Ma
Keyword(s):  
Contact Angle ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Aqueous Solutions ◽  
Fourier Transform Infrared Spectroscopy ◽  
Toluidine Blue ◽  
Water Contact ◽  
The Fourier Transform ◽  
Hydrolysis Of

Heparin (Hep)-immobilized poly(ether urethanes) (PU) was prepared by a unique preparation procedure. Firstly, the poly(ether urethanes)(PU) containing diester groups in the side chains were synthesized. Then, PU was dispersed in aqueous solutions and immobilized with heparin after the hydrolysis of diester groups and carboxylation. The Fourier transform infrared spectroscopy (FTIR) and water contact angle (WCA) were used to characterize the heparin-bonded PU. The amount of heparin grafted on the PU was determined to be 0.57wt.% by the toluidine blue method. The heparin-immobilized PU could release just 12% of the immobilized heparin in the early 10 hours of the 70 hours immobilized heparin stability test.

PREPARATION AND STRUCTURAL CHARACTERIZATION OF NANOCRYSTALLINE Zn–Cu–Cr FERRITES WITH Gd SUBSTITUTION

2010 ◽  
Vol 24 (27) ◽  
pp. 5409-5416 ◽  
Author(s):  
JING JIANG ◽  
CHAOCHAO CHEN ◽  
LUNHONG AI
Keyword(s):  
Fourier Transform ◽  
Spinel Structure ◽  
Remanent Magnetization ◽  
Phase Reaction ◽  
X Ray Diffraction ◽  
Reaction Method ◽  
X Ray ◽  
Magnetic Parameters ◽  
The Fourier Transform

Nanocrystalline spinel Zn – Cu – Cr ferrites with Gd substitution were prepared by a rheological phase reaction method. By means of the Fourier transform infrared (FTIR) spectra, Raman spectra, and X-ray diffraction (XRD), the cubic spinel structure of samples had been confirmed. The magnetic parameters such as saturation magnetization, remanent magnetization and coercivity can be tailored by controlling the content of substituting Gd ions.

Fabrication and Characterization of Nano-Sized Starch Particles

2015 ◽  
Vol 1120-1121 ◽  
pp. 275-280
Author(s):  
Hua Lin ◽  
Qing Li ◽  
Mu Feng ◽  
Li Zhao Qin
Keyword(s):  
Fourier Transform ◽  
Electron Microscope ◽  
Experimental Conditions ◽  
Transmission Electron ◽  
Infrared Spectrometer ◽  
Ft Ir ◽  
Plausible Mechanism ◽  
Fabrication And Characterization ◽  
The Fourier Transform

An efficient method of preparing nanostarch using high-intensity ultrasonic irradiation and acid hydrolysis was discussed. The transmission electron microscope (TEM) showed that the nanosized starch particles were in shape of sphere with the size of 80-120 nm, and their surfaces were rough with many flocci. The Fourier transform infrared spectrometer (FT-IR) revealed that the products maintained the original biological characteristics, and the molecules did not undergo any chemical changes. In addition, the effects of experimental conditions were analyzed and a plausible mechanism was proposed to explain the formation of the nanostarch.

Sign in / Sign up

Export Citation Format

Share Document