Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines
KTP Nguyen, K Medjaher, DT Tran - Artificial Intelligence Review, 2023 - Springer
The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …
applications. It is of no exception in the area of prognostics and health management (PHM) …
Fault location and detection techniques in power distribution systems with distributed generation: A review
Distribution systems are continuously exposed to fault occurrences due to various reasons,
such as lightning strike, failure of power system components due to aging of equipment and …
such as lightning strike, failure of power system components due to aging of equipment and …
Fault detection, classification and location for transmission lines and distribution systems: a review on the methods
A comprehensive review on the methods used for fault detection, classification and location
in transmission lines and distribution systems is presented in this study. Though the three …
in transmission lines and distribution systems is presented in this study. Though the three …
Self attention convolutional neural network with time series imaging based feature extraction for transmission line fault detection and classification
This paper introduces a novel self-attention convolutional neural network (SAT-CNN) model
for detection and classification (FDC) of transmission line faults. The transmission lines …
for detection and classification (FDC) of transmission line faults. The transmission lines …
Detection and classification of transmission line faults based on unsupervised feature learning and convolutional sparse autoencoder
We present in this paper a novel method for fault detection and classification in power
transmission lines based on convolutional sparse autoencoder. Contrary to conventional …
transmission lines based on convolutional sparse autoencoder. Contrary to conventional …
Hybrid CNN-LSTM approaches for identification of type and locations of transmission line faults
A Moradzadeh, H Teimourzadeh… - International Journal of …, 2022 - Elsevier
Timely and accurate detection of transmission line faults is one of the most important issues
in the reliability of the power systems. In this paper, in order to assess the effects of …
in the reliability of the power systems. In this paper, in order to assess the effects of …
Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems
A Ajagekar, F You - Applied Energy, 2021 - Elsevier
Quantum computing (QC) and deep learning have shown promise of supporting
transformative advances and have recently gained popularity in a wide range of areas. This …
transformative advances and have recently gained popularity in a wide range of areas. This …
[PDF][PDF] A comprehensive survey on support vector machine in data mining tasks: applications & challenges
During the last two decades, a substantial amount of research efforts has been intended for
support vector machine at the application of various data mining tasks. Data Mining is a …
support vector machine at the application of various data mining tasks. Data Mining is a …
[HTML][HTML] Support vector machine based fault classification and location of a long transmission line
This paper investigates support vector machine based fault type and distance estimation
scheme in a long transmission line. The planned technique uses post fault single cycle …
scheme in a long transmission line. The planned technique uses post fault single cycle …