Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration

GS Chawda, AG Shaik, M Shaik, S Padmanaban… - IEEE …, 2020 - ieeexplore.ieee.org
The global concern with power quality is increasing due to the penetration of renewable
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …

Recursive sliding DFT algorithms: A review

A Chauhan, KM Singh - Digital Signal Processing, 2022 - Elsevier
This paper reviews different recursive structures of Sliding Discrete Fourier Transform
(SDFT) algorithms. Normally, a SDFT algorithm is introduced to design a filter or to compute …

Novel short-time fractional Fourier transform: Theory, implementation, and applications

J Shi, J Zheng, X Liu, W Xiang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
As a generalization of the classical Fourier transform (FT), the fractional Fourier transform
(FRFT) has proven to be a powerful tool for signal processing and analysis. However, it is …

Digital signal processing for self-vibration monitoring in grinding: A new approach based on the time-frequency analysis of vibration signals

R Thomazella, WN Lopes, PR Aguiar, FA Alexandre… - Measurement, 2019 - Elsevier
The occurrence of chatter can generate parts outside the dimensional and geometric
tolerances or even cause irreversible damage, such as changes to the hardness and …

Radar emitter recognition based on SIFT position and scale features

S Liu, X Yan, P Li, X Hao… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
As the complexity of the battlefield electromagnetic environment has increased, it has
become challenging to identify radiation sources using traditional radar emitter identification …

Second-order transient-extracting S transform for fault feature extraction in rolling bearings

Y Liu, H Xiang, Z Jiang, J Xiang - Reliability Engineering & System Safety, 2023 - Elsevier
Intelligent fault diagnosis methods can obtain promising results in ensuring the safety and
reliability of key parts of rotating machinery. However, the problems are the insufficient …

Deepvoice: A voiceprint-based mobile health framework for parkinson's disease identification

H Zhang, A Wang, D Li, W Xu - 2018 IEEE EMBS International …, 2018 - ieeexplore.ieee.org
Parkinsons disease (PD) identification has attracted a lot of attention in recent years.
However, there is still no standardized and convenient way to identify PD, because most …

An efficient short-time Fourier transform algorithm for grinding wheel condition monitoring through acoustic emission

WN Lopes, POC Junior, PR Aguiar… - … International Journal of …, 2021 - Springer
Indirect methods to monitor the surface integrity of grinding wheels by acoustic emission
(AE) have been proposed, aiming to ensure their optimal performance. However, the time …

Recognition of emotion with intensity from speech signal using 3D transformed feature and deep learning

MR Islam, MAH Akhand, MAS Kamal, K Yamada - Electronics, 2022 - mdpi.com
Abstract Speech Emotion Recognition (SER), the extraction of emotional features with the
appropriate classification from speech signals, has recently received attention for its …

Power Quality Analysis Based on Machine Learning Methods for Low-Voltage Electrical Distribution Lines

CA Iturrino Garcia, M Bindi, F Corti, A Luchetta… - Energies, 2023 - mdpi.com
The main objective of this paper is to propose two innovative monitoring methods for
electrical disturbances in low-voltage networks. The two approaches present a focus on the …