Wind turbine drivetrain health assessment using discrete wavelet transforms and an artificial neural network

2014 ◽  
Author(s):  
C. Murray ◽  
C. Ng ◽  
N. Lieven ◽  
P. Morrish ◽  
M. Mulroy ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wind Turbine ◽  
Wavelet Transforms ◽  
Health Assessment ◽  
Discrete Wavelet ◽  
Discrete Wavelet Transforms ◽  
Artificial Neural

scholarly journals DIAGNOSIS OF INDUCTION MOTOR BEARING DEFECT USING DISCRETE WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORK

SINERGI ◽  
2020 ◽  
Vol 25 (1) ◽  
pp. 33
Author(s):  
Gigih Priyandoko ◽  
Istiadi Istiadi ◽  
Diky Siswanto ◽  
Dedy Usman Effendi ◽  
Eska Riski Naufal
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Motor ◽  
Wavelet Transforms ◽  
Industrial Applications ◽  
Discrete Wavelet ◽  
Motor Current Signature Analysis ◽  
Artificial Neural ◽  
Electromechanical Equipment ◽  
Motor Bearing

Induction motor is electromechanical equipment that is widely used in various industrial applications. The research paper presents the detection of the defect to three-phase induction motor bearing using discrete wavelet transforms and artificial neural networks to detect whether or not the motor is damaged. An experimental test rig was made to obtain data on healthy phase currents or damaged bearings on the induction motor using the motor current signature analysis (MCSA) method. Several mother-level wavelets are chosen on the wavelet method from the obtained current signal. The feature of the wavelet results is used as an input of the Artificial Neural Network to classify the condition of the induction motor. The results showed that the system could provide an accurate diagnosis of the condition of the induction motor.

Emotion Classification by EEG Signal Generated by Brain using Discrete Wavelet Transform and Artificial Neural Network Backpropagation with Classical Music Stimulus

2019 ◽  
Vol 1 (2) ◽  
pp. 1-4
Author(s):  
Aditya Dimas
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Classical Music ◽  
Brain Activity ◽  
Piano Music ◽  
Discrete Wavelet ◽  
Eeg Signal ◽  
Emotion Classification ◽  
Artificial Neural ◽  
Music Stimulus

People feel different emotions when listening to music on certain levels. Such feelings occur because the music stimuli causing reduced or increased brain activity and producing brainwave with specific characteristics. Results of research indicated that classical piano music can influence one’s emotional intelligent. By using Electroenchephalography (EEG) as a brainwave recording instrument, we can assess the effect of stimulation on the emotions generated through brain activity. This study aimed at developing a method that defines the effect of sound to brain activity using an EEG signal that can be used to identify one's emotion based on classical piano music stimulus reaction. Based on its frequency, this signal was the classified using DWT. To train Artificial Neural Network, some features were taken from the signal. This ANN research was carried out using the process of backpropagation

Wind turbine power modelling and optimization using artificial neural network with wind field experimental data

2020 ◽  
Vol 280 ◽  
pp. 115880 ◽  
Author(s):  
Haiying Sun ◽  
Changyu Qiu ◽  
Lin Lu ◽  
Xiaoxia Gao ◽  
Jian Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Artificial Neural Network ◽  
Wind Turbine ◽  
Wind Field ◽  
Artificial Neural ◽  
Modelling And Optimization
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