Results 51 to 60 of about 1,401 (153)

Distribution Network Fault Detection and Classification Using an Improved S‐Transform and a Modified Convolutional Neural Network

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
ABSTRACT In recent years, smart distribution networks have developed rapidly. However, complex electrical equipment and multisource monitoring data present great challenges for efficient fault detection in distribution networks. Accordingly, this study designs a multistage fault diagnosis framework based on a modified convolutional neural network (MCNN)
Fei Xiao, Rui Li, Hui Wang, Chunfang Zheng, Youya Shang, Qian Ai   +5 more
wiley   +1 more source

Fractional Synchrosqueezing Transformation and its Application in the Estimation of the Instantaneous Frequency of a Rolling Bearing

IEEE Access, 2020
The time-frequency energy distribution processed by a short-time Fourier transform can be compressed to the real instantaneous frequency by the synchrosqueezing transformation (SST), which improves the time-frequency energy concentration of the signal ...
Xin Li, Zengqiang Ma, Suyan Liu, Feiyu Lu   +3 more
doaj   +1 more source

Dynamic Analysis of a Rotating Cardan Shaft under the Influence of a Breathing Crack and Dense Fluid Force

Shock and Vibration, 2022
To extract any information from a complex data vibration, the time-frequency technique represents a suitable tool and a better indicator of the overall asset health of a rotating machine. Fluid influences on a cracked driveshaft and dynamic analysis of a
Bernard Xavier Tchomeni Kouejou, Alfayo Anyika Alugongo   +1 more
doaj   +1 more source

A Power Quality Disturbance Classification Method Based on Fine‐Tuned Moment Foundation Model

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
This paper introduces a robust power quality disturbance (PQD) classification method by fine‐tuning the moment time‐series foundation model to address the challenges of non‐Gaussian noise and varying sampling rates in inverter‐dominated grids. By utilising a resolution‐invariant patching mechanism and robust statistical normalisation, the proposed ...
Chengrui Zhang, Dechang Yang, Takayuki Ishizaki, Ruijin Zhu, Bin Li, Wenlong Liao   +5 more
wiley   +1 more source

A Hybrid Approach for Time-Varying Harmonic and Interharmonic Detection Using Synchrosqueezing Wavelet Transform

Applied Sciences, 2021
With widespread non-linear loads and the increasing penetration of distributed generations in the power system, harmonic pollution has become a great concern.
Gary W. Chang, Yu-Luh Lin, Yu-Jen Liu, Gary H. Sun, Johnson T. Yu   +4 more
doaj   +1 more source

A TC‐Based Multicomponent LFM Signal Characterization Method Under Impulsive Noise and Its Application

IET Signal Processing, Volume 2026, Issue 1, 2026.
The burst‐like and high‐amplitude characteristics of impulsive noise, which markedly differ from those of Gaussian noise, render methods based on the Gaussian assumption unable to accurately characterize signals under impulsive noise. Moreover, when dealing with multicomponent signal, existing impulsive noise suppression methods inevitably introduce ...
Weiwei Shang, Yong Guo, Lidong Yang, Tianyuan Liu   +3 more
wiley   +1 more source

Application and Evolution for Neural Network and Signal Processing in Large-Scale Systems

Complexity, 2021
Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation (ALFF) is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the ...
Dongbao Jia, Cunhua Li, Qun Liu, Qin Yu, Xiangsheng Meng, Zhaoman Zhong, Xinxin Ban, Nizhuan Wang   +7 more
doaj   +1 more source

Application of the Chaotic System–Based Error Trace Diagrams for Partial Discharge Feature Extraction

IET Science, Measurement &Technology, Volume 20, Issue 1, January/December 2026.
This study uses chaotic synchronisation and fractal analysis of acoustic partial discharge signals in 25‐kV cable joints. Extracted 3D error trace features combined with a neural network enable accurate, noise‐robust defect recognition, effectively distinguishing different cable joint defect types with high reliability and ease of implementation ...
Feng‐Chang Gu, Sen‐Fu Chan
wiley   +1 more source

sEMG signal filtering study using synchrosqueezing wavelet transform with differential evolution optimized threshold

Results in Engineering, 2023
Most gesture recognition studies based on surface electromyography (sEMG) signals focus on filtering, in which the lack of diversity for considered noises can still be the problem.
Chuanjiang Li, Huiyin Deng, Shiyi Yin, Chenming Wang, Yanfei Zhu   +4 more
doaj   +1 more source

AI‐Based Approaches for Analyzing EEG Signals to Identify Epileptic Seizures: A Survey

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Electroencephalography (EEG) is a fundamental tool for monitoring brain activity and is widely used in the diagnosis and management of epilepsy. With the growing prevalence of epilepsy and the limitations of manual EEG interpretation, artificial intelligence (AI) techniques, particularly machine learning (ML) and deep learning (DL), have gained ...
Daniel Moges Tadesse, Olyad Mulugeta Gonfa, Naod Demissie Workafesku, Eshtaol Girma Bayessa, Samuel Rahimeto Kebede, Taye Girma Debele, Fraol Gelana Waldamichael, Hiwot Taye Mekonnen, Tariku Fekadu Assore, Medina Fedlu Mehammed, Paulo Sergio Marques dos Santos   +10 more
wiley   +1 more source