Comparison of wavelet-functions for induction-motor rotor fault detection based on the hybrid “Time Synchronous Averaging - Discrete Wavelet Transform” approach

2015 ◽  
Author(s):  
Nabil Ngote ◽  
Said Guedira ◽  
Mohammed Ouassaid ◽  
Mohamed Cherkaoui
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Discrete Wavelet Transform ◽  
Induction Motor ◽  
Discrete Wavelet

Pendeteksian Misalignment Menggunakan Multi Level Transformasi Wavelet Haar dan Coiflet pada Motor Induksi

2020 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
P.P.S Saputra
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Induction Motor ◽  
High Frequency ◽  
High Efficiency ◽  
Vibration Signal ◽  
Normal Operation ◽  
Discrete Wavelet ◽  
High Frequency Signal ◽  
Motor Operation

Currently induction motors are widely used in industry due to strong construction, high efficiency, and cheap maintenance. Machine maintenance is needed to prolong the life of the induction motor. As studied, bearing faults may account for 42% -50% of all motor failures. In general it is due to manufacturing faults, lack of lubrication, and installation errors. Misalignment of motor is one of the installation errors. This paper is concerned to simulation of discrete wavelet transform for identifying misalignment in induction motor. Modelling of motor operation is introduced in this paper as normal operation and two variations of misalignment. For this task, haar and coiflet discrete wavelet transform in first level until fifth level is used to extract vibration signal of motor into high frequency of signal. Then, energy signal and other signal extraction gotten from high frequency signal is evaluated to analysis condition of motor. The results show that haar discrete wavelet transform at thirth level can identify normal motor  and misalignment motor conditions well

scholarly journals High impedance fault detection in 11 kV overhead line with discrete wavelet transform and independent component analysis

2021 ◽  
Vol 24 (2) ◽  
pp. 661
Author(s):  
Md Ferdouse Hossain Bhuiya ◽  
Rohaiza Hamdan ◽  
Dur Mohammad Soomro ◽  
Abdelrehman Omer Idris ◽  
Hussain Sharif
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Independent Component Analysis ◽  
Discrete Wavelet Transform ◽  
Component Analysis ◽  
Independent Component ◽  
Discrete Wavelet ◽  
Advanced Technique ◽  
High Impedance ◽  
High Impedance Fault

This paper proposes an analysis of high-impedance fault detection algorithms for medium voltage distribution lines based on the discrete wavelet transform (DWT) technique and a more advanced technique named independent component analysis (ICA) independently. Three-phase distribution line model and two diodes high impedance fault model, which represents the unsymmetrical fault current of electric arc, simulated using MATLAB/Simulink. High impedance fault (HIF) detection algorithm initially analyzes the sampled current waveforms through DWT and the resultant third level high-frequency components “d3” coefficients are analyzed through one cycle moving window approach. The proposed algorithm successfully detects any HIF in the distribution current even if there is a slight or no difference in the amplitude of the HIF and the waveform of the phase current. On the other hand, the ICA more developed algorithm than DWT successfully separated the noise signals from the obtained current waveforms and HIF noise signals can be differentiated with non-HIF noise signals. Because of this reason ICA is chosen in this research. The detected HIF current can be from 50 ma and up.

Sign in / Sign up

Export Citation Format

Share Document