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High-Voltage Circuit-Breaker Fault Diagnosis Based on Mechanical Vibration Signals
2016
Revista Técnica de la Facultad de Ingeniería Universidad del Zulia
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After that, the author conducts training of the well-built BP network to lay the foundation for the building of the high-voltage circuit-breaker fault diagnosis model based on the BP neural network and ...
In order to guarantee the operation stability of high-voltage circuit-breaker, this paper extracts eigenvector of vibration signals based on mining of characteristic entropy of the wavelet packet obtained ...
After that, the high-voltage circuit-breaker fault diagnosis model based on the BP neural network and the wavelet characteristic entropy is put forward. ...
doi:10.21311/001.39.4.48
fatcat:x77j72tejvdtlplrttfu3iyqvq
Intelligent Starting Current-Based Fault Identification of an Induction Motor Operating under Various Power Quality Issues
2021
Energies
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The proposed method uses power quality data along with starting current data to identify the broken rotor bar and bearing fault in induction motors. ...
The neural network (NN) classifier is used for classifying the faults and for analyzing the classification accuracy for various cases. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/en14020304
fatcat:z3pjtrr2fbgw3oeyo2jsogta3u
State Diagnosis of Elevator Control Transformer over Vibration Signal Based on MEA-BP Neural Network
2021
Shock and Vibration
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Finally, a fault diagnosis model composed of MEA and BP neural network is developed, which avoids the problems of premature convergence and poor diagnosis effect. ...
BP neural network. ...
Li et al. introduced a power transformer fault diagnosis method based on an optimized generalized regression neural network by integrating with characteristic gas, cuckoo search algorithm, and rough set ...
doi:10.1155/2021/9755094
fatcat:c3e3nuryabd6tlm4wvs64dhgxu
AUTOMATED RECOGNITION OF SINGLE & HYBRID POWER QUALITY DISTURBANCES USING WAVELET TRANSFORM BASED SUPPORT VECTOR MACHINE
2016
Jurnal Teknologi
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The classification performance of the proposed algorithm is also compared with wavelet based radial basis function neural network, probabilistic neural network and feed-forward neural network. ...
The monitoring of power quality (PQ) disturbances in a systematic and automated way is an important issue to prevent detrimental effects on power system. ...
Test Results On Distribution Network A typical 132/11kV radial distribution network system in Malaysia shown in Figure 5 was simulated using PSCAD/EMTDC power system simulation software. ...
doi:10.11113/jt.v79.5693
fatcat:zddxpv6vqna77b5pn3orxlri7u
Fault Detection for Multi-terminal Transmission Line with Nuclear Power Plant Based on Wavelet Transform Ahmed R. Adly(1),*, Alaa M. Abdel-hamed (2), Said A. Kotb (1), Magdy M. Zak (1) 1) ETRR-2, Nuclear Research Center, Atomic Energy Authority, Egypt 2) High Institute of Engineering, EL Shorouk Academy, Egypt
2019
Arab Journal of Nuclear Sciences and Applications
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Additionally, the nuclear power plants are planned to be integrated with the Egypt electric network in 2026, hence, the presented approach takes into consideration the installation of El Dabaa power station ...
This scheme is derived in the spectral domain and is based on the application of the DWT. The scheme uses an adaptive threshold level to detect and classify the faults. ...
line faults, and uses a radial basis function neural network to recognize and classify 10 fault types of power transmission lines. ...
doi:10.21608/ajnsa.2019.6832.1162
fatcat:zf4qdcqrbjfhtcuxsgfimplmui
Denoising and Harmonic Detection Using Nonorthogonal Wavelet Packets in Industrial Applications
2007
Journal of Systems Science and Complexity
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In training neural networks, for the sake of dimensionality and of ratio of time, compact information is needed. ...
A quasi-harmonic signal is a signal with one dominant harmonic and some more sub harmonics in superposition. Such signals often occur in rail vehicle systems, in which noisy signals are present. ...
For the sake of data compression the signal should be compressed with a small number k of parameters. All the m bases of the wavelet library have the dimension k × k. ...
doi:10.1007/s11424-007-9028-z
fatcat:i7ufbtjn35ejpgrqiumek244vm
An Image Compression Method Based on Wavelet Transform and Neural Network
2015
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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This paper applies the integration of wavelet analysis and artificial neural network in the image compression, discusses its performance in the image compression theoretically, analyzes the multiresolution ...
analysis thought, constructs a wavelet neural network model which is used in the improved image compression and gives the corresponding algorithm. ...
is 0.ISSN: 1693-6930 An Image Compression Method Based on Wavelet Transform and Neural .... ...
doi:10.12928/telkomnika.v13i2.1430
fatcat:6j7iethrtjhc5ov54r2scsf7ji
A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery
2019
Entropy
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After a brief introduction of early fault diagnosis techniques, the applications of EFD of rotating machine are reviewed in two aspects: fault frequency-based methods and artificial intelligence-based ...
As a promising field for reliability of modern industrial systems, early fault diagnosis (EFD) techniques have attracted increasing attention from both academia and industry. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/e21040409
pmid:33267123
pmcid:PMC7514898
fatcat:drfigyw7gzemfirsswsjuzfrii
A Three Decades of Marvellous Significant Review of Power Quality Events Regarding Detection & Classification
2018
Journal of Power and Energy Engineering
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The induction of these devices in the system attracts the attention of engineers towards the complexity of networks for planning and operation of electrical supply with the quality of power [9]. ...
has been impacted by faults. ...
Classification Based on the Neural Network The neural networks (NN) are good at Optimization and data clustering, pattern matching, classification, function approximation. ...
doi:10.4236/jpee.2018.68001
fatcat:5a7ubwe75jae3ouaylucyq5zca
Power Quality Classification of disturbances using Discrete Wavelet Packet Transform (DWPT) with Adaptive Neuro-Fuzzy System
2021
Turkish Journal of Computer and Mathematics Education
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Transform based Artificial neural networks etc.. ...
With the development of the technologies, the demand for good quality of electric power is increasing day by day. ...
Neural Network (ANN) [13] and so on. ...
doi:10.17762/turcomat.v12i3.1995
fatcat:plqdhwmsoje67ehak7gob56wem
A Novel Method for Intelligent Fault Diagnosis of Bearing Based on Capsule Neural Network
2019
Complexity
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In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis. ...
The newly proposed neural network named capsules network takes into account the size and location of the image. ...
of the North University of China under Grant XJJ201802. ...
doi:10.1155/2019/6943234
fatcat:ap7afclulve6vfjgdd3z77uwrq
Aeroengine Control System Sensor Fault Diagnosis Based on CWT and CNN
2020
Mathematical Problems in Engineering
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A convolutional neural network (CNN) model trained with preprocessed and labeled datasets is then used to extract the features of a time-frequency graph based on which faults can be identified and isolated ...
The continuous wavelet transform (CWT) is first applied to seven common health condition signals in an engine control system sensor in order to generate scalograms that capture the characteristics of the ...
the effectiveness of fault diagnosis based on CNN. ...
doi:10.1155/2020/5357146
fatcat:yl7mknv35jelzktbikcunujhda
Feature Recognition of Crop Growth Information in Precision Farming
2018
Complexity
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Finally, the classification method of BP neural network is used to classify the obtained feature vectors. ...
To identify plant electrical signals effectively, a new feature extraction method based on multiwavelet entropy and principal component analysis is proposed. ...
Henan University of Technology (2016QNJH02) and funded by the Henan Provincial Department of Education Natural Science Project (19B120001). ...
doi:10.1155/2018/9250832
fatcat:6zyxrzdyevczxfd35kixuuoo44
Classification of Power Quality Disturbances Using GA Based Optimal Feature Selection
[chapter]
2009
Lecture Notes in Computer Science
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Wavelet Transform (WT) has been used to extract some useful features of the power system disturbance signal and Gray-coded Genetic Algorithm (GGA) have been used for feature dimension reduction in order ...
Next, a Probabilistic Neural Network (PNN) has been trained using the optimal feature set selected by GGA for automatic Power Quality (PQ) disturbance classification. ...
Acknowledgement The authors acknowledge the financial grant by Department of Science and Technology (DST), Govt of India, for the research project on Power Quality Assessment in Distribution Network, to ...
doi:10.1007/978-3-642-11164-8_91
fatcat:3hdfye5usneq5bwfjl7wfwtwya
Power quality analysis using complex wavelet transform
2010
2010 Joint International Conference on Power Electronics, Drives and Energy Systems & 2010 Power India
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A neural network based on these parameters was trained and tested. It has been shown that the accuracy achieved by using complex wavelet is higher than obtained by the use of 'db4' wavelet. ...
Cite as: Panigrahi, K.B.; Baijal, A.; Krishna Chaitanya, P.; Nayak, P.P., "Power quality analysis using complex wavelet transform," Abstract--This paper deals with analysis of power signals using complex ...
The authors wish to acknowledge GIPEDI.AICET of Bharti School of Telecom Technology and Management, IIT Delhi and the Indian Academy of Sciences for providing an opportunity to undertake this project. ...
doi:10.1109/pedes.2010.5712564
fatcat:nh5v47x4b5aevhkuahggf7g6ca
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