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Dandan Peng / 彭丹丹
Dandan Peng / 彭丹丹
Ph.D, Department of Mechanical Engineering, KU Leuven, Belgium
Verified email at kuleuven.be
Title
Cited by
Cited by
Year
Understanding and learning discriminant features based on multiattention 1DCNN for wheelset bearing fault diagnosis
H Wang, Z Liu, D Peng, Y Qin
IEEE Transactions on Industrial Informatics 16 (9), 5735-5745, 2019
3092019
A novel deeper one-dimensional CNN with residual learning for fault diagnosis of wheelset bearings in high-speed trains
D Peng, Z Liu, H Wang, Y Qin, L Jia
Ieee Access 7, 10278-10293, 2018
2372018
Multibranch and multiscale CNN for fault diagnosis of wheelset bearings under strong noise and variable load condition
D Peng, H Wang, Z Liu, W Zhang, MJ Zuo, J Chen
IEEE Transactions on Industrial Informatics 16 (7), 4949-4960, 2020
2032020
Attention-guided joint learning CNN with noise robustness for bearing fault diagnosis and vibration signal denoising
H Wang, Z Liu, D Peng, Z Cheng
ISA transactions 128, 470-484, 2022
1232022
Multitask learning based on lightweight 1DCNN for fault diagnosis of wheelset bearings
Z Liu, H Wang, J Liu, Y Qin, D Peng
IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020
1192020
Feature-level attention-guided multitask CNN for fault diagnosis and working conditions identification of rolling bearing
H Wang, Z Liu, D Peng, M Yang, Y Qin
IEEE transactions on neural networks and learning systems 33 (9), 4757-4769, 2021
922021
Improved Hilbert–Huang transform with soft sifting stopping criterion and its application to fault diagnosis of wheelset bearings
Z Liu, D Peng, MJ Zuo, J Xia, Y Qin
ISA transactions 125, 426-444, 2022
582022
Self-supervised signal representation learning for machinery fault diagnosis under limited annotation data
H Wang, Z Liu, Y Ge, D Peng
Knowledge-Based Systems 239, 107978, 2022
492022
Interpretable convolutional neural network with multilayer wavelet for Noise-Robust Machinery fault diagnosis
H Wang, Z Liu, D Peng, MJ Zuo
Mechanical Systems and Signal Processing 195, 110314, 2023
462023
ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis
Z Liu, Y Jin, MJ Zuo, D Peng
ISA transactions 95, 346-357, 2019
372019
Domain adaptation digital twin for rolling element bearing prognostics
C Liu, A Ricardo Mauricio, J Qi, D Peng, K Gryllias
Online proceedings of PHM2020, 1-10, 2020
242020
RMA-CNN: A residual mixed-domain attention CNN for bearings fault diagnosis and its time-frequency domain interpretability
D Peng, H Wang, W Desmet, K Gryllias
Journal of Dynamics, Monitoring and Diagnostics, 2023
152023
Deep unsupervised transfer learning for health status prediction of a fleet of wind turbines with unbalanced data
D Peng, C Liu, W Desmet, K Gryllias
Proceedings of the Annual Conference of the PHM Society 2021, 2021
122021
An improved 2DCNN with focal loss function for blade icing detection of wind turbines under imbalanced SCADA data
D Peng, C Liu, W Desmet, K Gryllias
International Conference on Offshore Mechanics and Arctic Engineering 84768 …, 2021
72021
基于软筛分停止准则的改进经验模态分解及其在旋转机械故障诊断中的应用
彭丹丹, 刘志亮, 靳亚强, 秦勇
机械工程学报 55 (10), 122-132, 2019
62019
Informative frequency band selection based on a new indicator: Accuracy rate
Y Jin, Z Liu, D Peng, J Kang, J Ding
Journal of Intelligent & Fuzzy Systems 34 (6), 3487-3498, 2018
52018
Blind source separation and identification for speech signals
J Yin, Z Liu, Y Jin, D Peng, J Kang
2017 International conference on sensing, diagnostics, prognostics, and …, 2017
52017
Semi-Supervised CNN-Based SVDD Anomaly Detection for Condition Monitoring of Wind Turbines
D Peng, C Liu, W Desmet, K Gryllias
International Conference on Offshore Mechanics and Arctic Engineering 86618 …, 2022
32022
A transfer learning-based rolling bearing fault diagnosis across machines
D Peng, C Liu, A Ricardo Mauricio, W Desmet, K Gryllias
Proceedings of the Annual Conference of the PHM Society 2022 14 (1), 2022
32022
Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description
D Peng, C Liu, W Desmet, K Gryllias
Journal of Engineering for Gas Turbines and Power 145 (9), 091009, 2023
12023
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Articles 1–20