[HTML][HTML] A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems

JS Farkhani, Ö Çelik, K Ma, CL Bak, Z Chen - Renewable and Sustainable …, 2024‏ - Elsevier
High voltage direct current (HVDC) transmission systems represent a significant
development for future power systems due to presenting promising solutions for long …

[HTML][HTML] Machine learning and deep learning for safety applications: Investigating the intellectual structure and the temporal evolution

L Leoni, A BahooToroody, MM Abaei, A Cantini… - Safety science, 2024‏ - Elsevier
Over the last decades, safety requirements have become of primary concern. In the context
of safety, several strategies could be pursued in many engineering fields. Moreover, many …

A novel wind power forecasting system integrating time series refining, nonlinear multi-objective optimized deep learning and linear error correction

J Wang, Y Qian, L Zhang, K Wang, H Zhang - Energy Conversion and …, 2024‏ - Elsevier
Wind power prediction is crucial for successfully integrating large-scale wind energy with the
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …

Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines

X Jiang, Q Song, H Wang, G Du, J Guo, C Shen… - … and Machine Theory, 2022‏ - Elsevier
To overcome current challenges in variational mode decomposition (VMD) and its variants
for the fault diagnosis of rotating machines, the decomposing characteristics of two sub …

SO-slope entropy coupled with SVMD: A novel adaptive feature extraction method for ship-radiated noise

Y Li, B Tang, S Jiao - Ocean Engineering, 2023‏ - Elsevier
Slope entropy (SloEn) has been applied as a powerful nonlinear dynamic tool for signal
complexity measurement and is widely used for ship-radiated noise signal (S-RNS) feature …

Empirical Fourier decomposition: An accurate signal decomposition method for nonlinear and non-stationary time series analysis

W Zhou, Z Feng, YF Xu, X Wang, H Lv - Mechanical Systems and Signal …, 2022‏ - Elsevier
Signal decomposition is an effective tool to assist identification of modal information in time-
domain signals. Two signal decomposition methods, including the empirical wavelet …

A new underwater acoustic signal denoising method based on modified uniform phase empirical mode decomposition, hierarchical amplitude-aware permutation …

G Li, Y Han, H Yang - Ocean Engineering, 2024‏ - Elsevier
Underwater acoustic signal (UAS) denoising is base and prerequisite for UAS detection,
recognition and classification. In order to perform UAS denoising effectively, a new UAS …

Generalized refined composite multiscale fuzzy entropy and multi-cluster feature selection based intelligent fault diagnosis of rolling bearing

J Zheng, H Pan, J Tong, Q Liu - ISA transactions, 2022‏ - Elsevier
Extracting the failure related information from vibration signals is a very important aspect of
vibration-based fault detection for rolling bearing Multiscale entropy and its improvement …

Novel hybrid intelligence predictive model based on successive variational mode decomposition algorithm for monthly runoff series

A Parsaie, R Ghasemlounia, A Gharehbaghi… - Journal of …, 2024‏ - Elsevier
A high-accuracy estimation of the runoff has always been an extremely relevant and
challenging subject in hydrology science. Therefore, in the current research, a novel hybrid …

Time-varying damage detection in beam structures using variational mode decomposition and continuous wavelet transform

JL Liu, SF Wang, YZ Li, AH Yu - Construction and Building Materials, 2024‏ - Elsevier
Civil engineering structures in operation are likely to suffer damage. During the service life,
structural damage evolves gradually from minor to severe. However, most current studies …