Abstract
No public abstract is available from the verified source records.
Runze Qi, Bohao Peng, Tianyu Duan
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
pubmed
Confidence 98%
unpaywall
Confidence 95%
datacite
Confidence 0%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
DC voltage control and OLTC control strategy for MMC-based HVDC system under SM failure
10.1109/access.2021.3102377 · 2021
Mechanical fault diagnosis of on-load tap-changer based on improved variational mode decomposition and relative density-based outlier score
10.1049/elp2.12354 · 2023
A worldwide transformer reliability survey
2016
Vibro-acoustic diagnostic: contributing to an optimized on-load tap changer (OLTC) maintenance strategy
2011
Status and trends in transformer monitoring
10.1109/61.517495 · 1996
Condition assessment of power OLTC by vibration analysis using wavelet transform
10.1109/tpwrd.2009.2014268 · 2009
Intelligent fault diagnosis approach based on composite multi-scale dimensionless indicators and affinity propagation clustering
10.1109/jsen.2020.2995817 · 2020
Using deep learning to detect anomalies in on-load tap changer based on vibro-acoustic signal features
10.3390/en17071665 · 2024
A mechanical fault identification method for on-load tap changers based on hybrid time-frequency graphs of vibration signals and DSCNN-SVM with small sample sizes
10.3390/vibration7040051 · 2024
Fault diagnosis of on-load tap-changer in converter transformer based on time-frequency vibration analysis
10.1109/tie.2016.2524399 · 2016
Multi-feature fusion-based mechanical fault diagnosis for on-load tap changers in smart grid with electric vehicles
10.1109/jsen.2020.3021920 · 2021
Detection of on-load tap-changer contact wear using vibroacoustic measurements
10.1109/tpwrd.2024.3474420 · 2024
Condition assessment of power transformer on-load tap-changers using wavelet analysis
10.1109/61.924817 · 2001
A method for diagnosing mechanical faults of on-load tap changer based on ensemble empirical mode decomposition, Volterra model and decision acyclic graph support vector machine
10.1109/access.2019.2925046 · 2019
An antinoise feature extraction and improved Harris hawks optimization for on-load tap changer mechanical fault diagnosis
10.1109/jsen.2024.3350167 · 2024
Mechanical fault diagnostics of power transformer on-load tap changers using dynamic time warping
10.1109/tim.2018.2872385 · 2019
A parallel deep neural network for intelligent fault diagnosis of drilling pumps
10.1016/j.engappai.2024.108071 · 2024
Deep learning for time series anomaly detection: a survey
2024
CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis
10.1016/j.aei.2023.101877 · 2023
Transformer OLTC operation monitoring framework through acoustic signal processing and convolutional neural networks
10.1109/tim.2025.3550221 · 2025
Mechanical fault diagnosis of on-load tap changers using time–frequency vibration analysis and a lightweight YOLO model
10.1016/j.measurement.2025.118441 · 2025
A mechanical fault diagnosis model of on-load tap changer based on same-source heterogeneous data fusion
2022
Adaptive frequency attention-based interpretable Transformer network for few-shot fault diagnosis of rolling bearings
10.1016/j.ress.2025.111271 · 2025
EEG-based emotion recognition using MobileNet recurrent neural network with time-frequency features
10.1016/j.asoc.2024.111338 · 2024
A meta-learning method for electric machine bearing fault diagnosis under varying working conditions with limited data
10.1109/tii.2022.3165027 · 2023
Few-shot multi-domain text intent classification with dynamic balance domain adaptation meta-learning
10.1016/j.eswa.2024.124429 · 2024
Meta-learning approaches for few-shot learning: a survey of recent advances
10.1145/3659943 · 2024
Gradient-based domain-augmented meta-learning single-domain generalization for fault diagnosis under variable operating conditions
10.1177/14759217241230129 · 2024
Meta-learning in neural networks: a survey
2022
Advances and challenges in meta-learning: a technical review
10.1109/tpami.2024.3357847 · 2024
Cross-domain few-shot fault diagnosis based on meta-learning and domain adversarial graph convolutional network
10.1016/j.engappai.2024.108970 · 2024
A novel meta-transfer learning approach via convolutional multi-head self-attention network for few-shot fault diagnosis
10.1016/j.knosys.2024.112113 · 2024
Fault diagnosis for wind turbine generators based on model-agnostic meta-learning: a few-shot learning method
10.1016/j.eswa.2024.126171 · 2025
When meta-learning meets online and continual learning: a survey
10.1109/tpami.2024.3463709 · 2025
Transformer-based meta learning method for bearing fault identification under multiple small sample conditions
10.1016/j.ymssp.2023.110967 · 2024
Meta-learning with distributional similarity preference for few-shot fault diagnosis under varying working conditions
10.1109/tcyb.2023.3338768 · 2024
Few-shot fault diagnosis of switch machine based on data fusion and balanced regularized prototypical network
10.1016/j.engappai.2024.108847 · 2024
A novel dimensional variational prototypical network for industrial few-shot fault diagnosis with unseen faults
10.1016/j.compind.2024.104133 · 2024
Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds
10.1016/j.ress.2024.110001 · 2024
Wavelet networks
10.1109/72.165591 · 1992
10.1109/cvpr.2018.00131
10.1109/cvpr.2018.00131 · doi-reference
Subdomain adaptation joint attention network enabled two-stage strategy towards few-shot fault diagnosis of LRE turbopump
10.1016/j.aei.2024.102366 · doi-reference
Intelligent fault diagnosis of wind turbines via a deep learning network using parallel convolution layers with multi-scale kernels
10.1016/j.renene.2020.02.004 · doi-reference
Deep transfer multi-wavelet auto-encoder for intelligent fault diagnosis of gearbox with few target training samples
10.1016/j.knosys.2019.105313 · doi-reference