Leaderboards/Engineering Diagnostics and Reliability

Engineering Diagnostics and Reliability

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
You Keshun
University of South China
2
Jiusi Zhang
University of Electronic Science and Technology of China
3
Chuang Chen
Nanjing University of Posts and Telecommunications
4
Yutong Dong
Northwestern Polytechnical University
5
Yiming Xiao
Hunan University
6
Zhuang Ye
Huzhou Vocational and Technical College
7
Yunjia Dong
Harbin Institute of Technology
8
Przemysław Pietrzak
Wrocław University of Science and Technology
9
Wonho Jung
Korea Advanced Institute of Science and Technology
10
Elsie Fezeka Swana
University of Johannesburg

Rising Stars Papers

1
Domain generalization for rotating machinery fault diagnosis: A survey
Advanced Engineering Informatics|2024
166 cit.
2
Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective
Reliability Engineering & System Safety|2024
137 cit.
3
A sound-vibration physical-information fusion constraint-guided deep learning method for rolling bearing fault diagnosis
Reliability Engineering & System Safety|2024
124 cit.
4
Toward Efficient and Interpretative Rolling Bearing Fault Diagnosis via Quadratic Neural Network With Bi-LSTM
IEEE Internet of Things Journal|2024
118 cit.
5
A trackable multi-domain collaborative generative adversarial network for rotating machinery fault diagnosis
Mechanical Systems and Signal Processing|2024
96 cit.
6
An adaptive fused domain-cycling variational generative adversarial network for machine fault diagnosis under data scarcity
Information Fusion|2025
90 cit.
7
Process monitoring for tower pumping units under variable operational conditions: From an integrated multitasking perspective
Control Engineering Practice|2025
70 cit.
8
Multi-sensor data fusion-enabled lightweight convolutional double regularization contrast transformer for aerospace bearing small samples fault diagnosis
Advanced Engineering Informatics|2024
69 cit.
9
Dynamic normalization supervised contrastive network with multiscale compound attention mechanism for gearbox imbalanced fault diagnosis
Engineering Applications of Artificial Intelligence|2024
66 cit.
10
An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples
Reliability Engineering & System Safety|2024
65 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Haidong Shao
South China University of Technology
2
Zitong Zhou
Nanjing University of Posts and Telecommunications
3
Haidong Shao
Hunan University
4
Yudong Cao
Southeast University
5
Mir Biuok Ehghaghi
University of Tabriz
6
Mustafa Kuntoğlu
Selçuk University
7
Hong‐Liang Song
Southwest Jiaotong University
8
Xingkai Yang
Hunan University
9
Zhiwen Liu
Dalian University of Technology
10
Huiwei Zhao
Northwestern Polytechnical University

Emerging Leaders Papers

1
Artificial intelligence systems for tool condition monitoring in machining: analysis and critical review
Journal of Intelligent Manufacturing|2022
341 cit.
2
Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework
Advanced Engineering Informatics|2022
323 cit.
3
Dual-Threshold Attention-Guided GAN and Limited Infrared Thermal Images for Rotating Machinery Fault Diagnosis Under Speed Fluctuation
IEEE Transactions on Industrial Informatics|2023
275 cit.
4
Multi-scale integrated deep self-attention network for predicting remaining useful life of aero-engine
Engineering Applications of Artificial Intelligence|2023
219 cit.
5
Development of lattice structure with selective laser melting process: A state of the art on properties, future trends and challenges
Journal of Manufacturing Processes|2022
199 cit.
6
Few-Shot Cross-Domain Fault Diagnosis of Bearing Driven by Task-Supervised ANIL
IEEE Internet of Things Journal|2024
176 cit.
7
A novel conditional weighting transfer Wasserstein auto-encoder for rolling bearing fault diagnosis with multi-source domains
Knowledge-Based Systems|2022
154 cit.
8
Prior Knowledge-Augmented Self-Supervised Feature Learning for Few-Shot Intelligent Fault Diagnosis of Machines
IEEE Transactions on Industrial Electronics|2022
125 cit.
9
Class-Aware Adversarial Multiwavelet Convolutional Neural Network for Cross-Domain Fault Diagnosis
IEEE Transactions on Industrial Informatics|2023
98 cit.
10
Few-shot learning under domain shift: Attentional contrastive calibrated transformer of time series for fault diagnosis under sharp speed variation
Mechanical Systems and Signal Processing|2022
82 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
Yaguo Lei
Xi'an Jiaotong University
2
Minping Jia
Southeast University
3
Yanyang Zi
Xi'an Jiaotong University
4
Xuefeng Chen
Xi'an Jiaotong University
5
Hongkai Jiang
Northwestern Polytechnical University
6
Yu Yang
Hainan University
7
Jing Lin
Xiamen University
8
Na Lü
Southwest Petroleum University
9
Ming J. Zuo
Fuzhou University
10
Wenyu Zhao
Hunan University of Technology

Current Senior Leaders Papers

1
Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
Mechanical Systems and Signal Processing|2015
1.7k cit.
2
A recurrent neural network based health indicator for remaining useful life prediction of bearings
Neurocomputing|2017
1.2k cit.
3
An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data
IEEE Transactions on Industrial Electronics|2016
1.2k cit.
4
Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection
Mechanical Systems and Signal Processing|2012
729 cit.
5
A sparse auto-encoder-based deep neural network approach for induction motor faults classification
Measurement|2016
692 cit.
6
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
ISA Transactions|2020
634 cit.
7
A Model-Based Method for Remaining Useful Life Prediction of Machinery
IEEE Transactions on Reliability|2016
614 cit.
8
Physics-informed neural network for lithium-ion battery degradation stable modeling and prognosis
Nature Communications|2024
607 cit.
9
Application of the EEMD method to rotor fault diagnosis of rotating machinery
Mechanical Systems and Signal Processing|2008
582 cit.
10
A roller bearing fault diagnosis method based on EMD energy entropy and ANN
Journal of Sound and Vibration|2005
559 cit.

Reagents for Engineering Diagnostics and Reliability

Citation-validated products used in this field

🔥 Trending

Gaining adoption fast

⭐ Top Rated

Best all-around

🌟 All-Time

Most validated

Cell Signaling TechnologyEvidence 66

Nestin (E4O9E) Rabbit Monoclonal Antibody (BSA and Azide Free)

#73262$865
View Evidence →
Cell Signaling TechnologyEvidence 65

Phospho-GADS (Thr262) (E8L3B) Rabbit Monoclonal Antibody

#78972$194,437
View Evidence →
Cell Signaling TechnologyEvidence 64

Non-Canonical BAF Complex Antibody Sampler Kit

#48585$427
View Evidence →