陆伟

发布者:研办发布时间:2025-03-04浏览次数:10

陆伟男,安徽肥东人,博士,讲师硕士生导师20236月毕业于中国科学技术大学,获控制科学与工程专业工学博士学位。先后主持和参与国家省部级、校厅级课题5在国内外重要学术刊物发表论文10篇,授权国家发明专利4参编教材1

联系方式:E-mail: weilu@fjut.edu.cn   

研究领域:

智能信息感知与控制、可穿戴外骨骼人机交互系统

工作经历:

2017.62019.4,合肥阳光电源股份有限公司,工程师

2024.09—至今,福建理工大学,讲师

主讲课程:

《自动控制原理》、《人工智能导论

主要科研项目

[1]福建省教育厅,福建省中青年教师教育科研项目,GY-Z24172上肢运动信息辨识与肌力预测研究,主持在研

[2]福建理工大学,科研启动基金GY-Z23201多模信息融合的人体肌肉协作质量模型与肌力预测方法研究主持,在研;

[3]福建理工大学,科研发展基金专项,GY-S24128人工智能驱动应用型高校教育高质量发展路径及策略研究,主持,在研;

[4]国家自然科学基金委,青年项目,51307041,区间上界保证机制的微电网数据通信无线传感器网络跨层协同控制模 型与优化策略研究,参与,已结题。

主要发表论文

[1] 陆伟,罗宇晨,高忠顺,等. 传感技术学报.基于多因素融合的上肢运动sEMG信号鲁棒预测模型研究.传感技术学报,2025, 已接收.

[2] Wei Lu, Dongliang Gong, Xue Xue. Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs.Frontiers in Bioengineering and Biotechnology, 2024.

[3] Wei Lu, Lifu Gao, Huibin Cao*, et.al. A Comparison of Contributions of Individual Muscle and Combination Muscles to Interaction Force Prediction Using KPCA-DRSN Model. Frontiers in Bioengineering and Biotechnology, 2022.

[4] Wei Lu, Lifu Gao, Huibin Cao*, et.al. sEMG-Upper Limb Interaction Force Estimation Framework Based on Residual Network and Bidirectional Long Short-Term Memory Network. Applied Sciences, 2022.

[5] Wei Lu, Lifu Gao, Zebin Li*, et.al. Prediction of Long-Term Elbow Flexion Force Intervals Based on the Informer Model and Electromyography. Electronics, 2021.

[6] Lu W, Gao L, Cao H, et.al. Research on Collaborative Quality Assessment Model of Elbow Muscles based on MC-MMG and DRSN. Proceedings of the 2nd International Symposium on Artificial Intelligence for Medicine Sciences, 2021.

[7] Lu W, Gao L, Zhang Q, et.al. A Hybrid Deep Learning Framework for Estimation of Elbow Flexion Force via Electromyography. Journal of Physics: Conference Series, 2021.

[8] Zebin Li, Lifu Gao, Wei Lu*, et.al. Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS‐SVR. Sensors, 2022. 

[9] Wei Sun, Wei Lu, Qiyue Li, et.al. WNN-LQE: Wavelet-Neural-Network-Based Link Quality Estimation for Smart Grid WSNs. IEEE Access, 2017.

[10]Zebin Li, Lifu Gao, Wei Lu, et.al. A Novel Noise Suppression and Artifacts Removal Method of Mechanomyography Based on RLS, IGWO-VMD and CEEMDAN. Journal of Sensors, 2022.

[11]Li Z, Gao L, Lu W, et.al. Estimation of Knee Joint Extension Force Using Mechanomyography Based on IGWO-SVR Algorithm. Electronics, 2021.

[12] Wei SunLu WeiJianping Wang, et.al. A Link Quality Estimation model of Wireless Sensor Networks for Smart Distribution GridPreprints of the 17th IFAC Symposium on System IdentificationBeijing2015. 

[13] 孙伟,陆伟,李奇越,. 智能电网中无线传感器网络通信链路可靠性置信区间预测,电力系统自动化2015.

发明专利

1.基于自适应长短时记忆网络的肘关节收缩肌力估计方法.

2.基于随机向量功能连接网络技术的人体肌音信号预测方法.

3.基于小波神经元网络的无线链路质量预测方法.

4.基于动态时间规整算法的无线链路质量预测方法.