2026 Yuequan Bao: Engineering and Technology Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Engineering and Technology	41	7077	6834	1303	1296	93	5570

Overview

Yuequan Bao is affiliated with the Harbin Institute of Technology in China, contributing extensively to the field of engineering with a particular focus on civil and structural engineering. Their research portfolio encompasses an array of publications primarily centered on structural health monitoring and related technical domains.

Their recent notable papers include:

Machine learning paradigm for structural health monitoring, 2020, Structural Health Monitoring
An active learning method combining deep neural network and weighted sampling for structural reliability analysis, 2020, Mechanical Systems and Signal Processing
Group sparsity-aware convolutional neural network for continuous missing data recovery of structural health monitoring, 2020, Structural Health Monitoring
Attribute-based structural damage identification by few-shot meta learning with inter-class knowledge transfer, 2020, Structural Health Monitoring
Transfer learning-based data anomaly detection for structural health monitoring, 2023, Structural Health Monitoring

Frequent coauthors collaborating with Yuequan Bao include:

Hui Li
Yang Xu
Zhiyi Tang
Huabin Sun
Xiaoshu Guan

The main publication venues where Yuequan Bao often contributes are:

Structural Health Monitoring
Reliability Engineering & System Safety
Structural Control and Health Monitoring
Mechanical Systems and Signal Processing
Engineering Structures

Their primary field of study is engineering, with a strong emphasis on subfields including:

Civil and Structural Engineering
Statistics, Probability and Uncertainty
Mechanical Engineering
Mechanics of Materials
Artificial Intelligence

Research topics that Yuequan Bao has extensively worked on cover:

Structural Health Monitoring Techniques
Infrastructure Maintenance and Monitoring
Concrete Corrosion and Durability
Probabilistic and Robust Engineering Design
Ultrasonics and Acoustic Wave Propagation
Non-Destructive Testing Techniques
Anomaly Detection Techniques and Applications

Best Publications

Computer vision and deep learning–based data anomaly detection method for structural health monitoring:

Yuequan Bao;Zhiyi Tang;Hui Li;Yufeng Zhang

589
Citations
The State of the Art of Data Science and Engineering in Structural Health Monitoring

Yuequan Bao;Zhicheng Chen;Shiyin Wei;Yang Xu

441
Citations
Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring

Zhiyi Tang;Zhicheng Chen;Yuequan Bao;Hui Li

406
Citations
Machine learning paradigm for structural health monitoring

Yuequan Bao;Hui Li

312
Citations
Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images:

Yang Xu;Yuequan Bao;Jiahui Chen;Wangmeng Zuo

290
Citations
Automatic seismic damage identification of reinforced concrete columns from images by a region-based deep convolutional neural network

Yang Xu;Yang Xu;Shiyin Wei;Shiyin Wei;Yuequan Bao;Yuequan Bao;Hui Li;Hui Li

197
Citations
Compressive sampling for accelerometer signals in structural health monitoring

Yuequan Bao;James L Beck;Hui Li

196
Citations
Compressive sampling–based data loss recovery for wireless sensor networks used in civil structural health monitoring

Yuequan Bao;Hui Li;Xiaodan Sun;Yan Yu

192
Citations
Embedding Compressive Sensing-Based Data Loss Recovery Algorithm Into Wireless Smart Sensors for Structural Health Monitoring

Zilong Zou;Yuequan Bao;Hui Li;Billie F. Spencer

137
Citations
Condition assessment of cables by pattern recognition of vehicle-induced cable tension ratio

Shunlong Li;Shiyin Wei;Yuequan Bao;Hui Li

132
Citations
Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations

Yuequan Bao;Yuequan Bao;Zuoqiang Shi;James L. Beck;Hui Li

119
Citations
Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach

Yuequan Bao;Zhiyi Tang;Hui Li

113
Citations
An active learning method combining deep neural network and weighted sampling for structural reliability analysis

Zhengliang Xiang;Jiahui Chen;Yuequan Bao;Hui Li

109
Citations
Selection of regularization parameter for l1-regularized damage detection

Rongrong Hou;Yong Xia;Yuequan Bao;Xiaoqing Zhou

103
Citations
Fractal Dimension‐Based Damage Detection Method for Beams with a Uniform Cross‐Section

Hui Li;Yong Huang;Jinping Ou;Yuequan Bao

100
Citations
Structural damage identification based on integration of information fusion and shannon entropy

Hui Li;Yuequan Bao;Jinping Ou;Jinping Ou

99
Citations
Optimal policy for structure maintenance: A deep reinforcement learning framework

Shiyin Wei;Yuequan Bao;Hui Li

98
Citations
Identification of spatio-temporal distribution of vehicle loads on long-span bridges using computer vision technology

Zhicheng Chen;Hui Li;Yuequan Bao;Na Li

87
Citations
Compressive sensing‐based lost data recovery of fast‐moving wireless sensing for structural health monitoring

Yuequan Bao;Yan Yu;Hui Li;Xingquan Mao

83
Citations
Analyzing and modeling inter-sensor relationships for strain monitoring data and missing data imputation: a copula and functional data-analytic approach:

Zhicheng Chen;Hui Li;Yuequan Bao

80
Citations