Large Equipment Fault Diagnosis and Intelligent Operation and Maintenance Team

 

Academic Leader:

Deqiang He (PhD, Professor, PhD Supervisor): Guangxi BaGui Scholar, Model Teacher of Guangxi Zhuang Autonomous Region, Second-level Candidate of Guangxi Ten Hundred Thousand Talents Program, Recipient of Guangxi University Outstanding Talent Support Program, Baosteel Excellent Teacher Award, and Special Expert of Nanning City. Director of China Vibration Engineering Society, Executive Committee Member of Measurement and Control Professional Committee of China Instrument and Instrumentation Society, Director of Rotor Dynamics Professional Committee of China Vibration Engineering Society, Member and Deputy Secretary-General of Intelligent Manufacturing Professional Committee of China Artificial Intelligence Society, Member of Youth Work Committee of Materials Branch of China Mechanical Engineering Society, Member of Intelligent Manufacturing Working Group (WG1) of National Rail Transit Electrical Equipment and System Standardization Technical Committee (SAC/TC278), Member of Electric Earthmoving Machinery Subcommittee (SAC/TC334/SC3) of National Earthmoving Machinery Standardization Technical Committee, Director of the 8th Council of Guangxi Mechanical Engineering Society, Editorial Board Member of Journal of Guangxi University (Natural Science Edition), Editorial Board Member of Control and Information Technology, etc.

 

Main Members:

Jian Miao (PhD, Professor), Jianxin Deng (PhD, Professor), Bin Liu (PhD, Associate Professor), Yanjun Chen (PhD, Associate Professor), Xianwang Li (PhD, Lecturer), Zhenzhen Jin (PhD, Assistant Professor), Zaiyu Xiang (PhD, Assistant Professor), Yang Fu (PhD, Assistant Professor), Qin Li (PhD, Assistant Professor), Qiumei Yang (PhD, Assistant Professor), Hongwei Li (PhD, Assistant Professor).

 

Research Directions:

1.  Remote Train Fault Diagnosis: Based on the characteristics and needs of China's rail transit trains, research focuses on key technologies such as onboard information collection and fault diagnosis systems based on high-capacity networks, train-to-ground wireless data transmission systems, and ground information processing with intelligent maintenance systems. These efforts aim to achieve remote status monitoring and fault diagnosis for rail transit trains, establish a fault diagnosis information technology platform adapted to rail transit trains, enhance their operational, maintenance, and management levels, and provide an information-assisted platform to improve the safety, reliability, availability, and maintainability of rail transit trains.

2.  Intelligent Operation and Maintenance of Trains: Addressing the operational needs of rail transit trains in high-temperature and high-humidity environments and karst terrain, research focuses on key technologies for a rail transit train health management system based on the Internet of Vehicles. Methods such as data mining and machine learning are used to analyze and process real-time status data and onboard recorded data of trains. This analysis includes fault trend identification through data fitting, enabling functions such as proactive safety protection, fault warning, life prediction, and intelligent maintenance for trains.

3.  Energy Management and Control of Electric Engineering Machinery/Vehicles: Addressing the high energy loss and low energy conversion efficiency of electric engineering machinery/vehicles, research focuses on key technologies such as topology and modulation optimization of rectifier circuits, rapid fault diagnosis of main circuits, and battery energy management and optimization control. These efforts aim to improve energy conversion efficiency, enhance the operational efficiency and reliability of rectifier systems, and achieve more precise energy control and monitoring for electric engineering machinery/vehicles.

4.  Design and Optimization of Forestry Machinery Equipment: Addressing the characteristics of southern hilly and mountainous areas and the modern operational needs of forestry, research focuses on multifunctional forestry machinery suitable for steep slope terrains, reliability optimization design of forestry machinery supporting equipment, and modern automatic control technology for forestry machinery equipment. The aim is to design mechanically diverse and easily switchable machinery to achieve multifunctional forestry operations, improve the utilization rate of hilly and mountainous forestry machinery, reduce energy consumption, and enhance the production efficiency of forestry operations.

 

Research Achievements:

Representative Papers Published in the Past Three Years

[1]  Zhenzhen Jin, Deqiang He*, Zexian Wei. Intelligent Fault Diagnosis of Train Axle Box Bearing Based on Parameter Optimization VMD and Improved DBN[J]. Engineering Applications of Artificial Intelligence, 2022,110:104713, doi:10.1016/j.engappai.2022.104713 . (JCR Q1, IF= 7.5，ESI Highly Cited Paper).

[2]  Zexian Wei, Deqiang He*, Zhenzhen Jin, Bin Liu, Sheng Shan, Yanjun Chen, Jian Miao, Density-Based Affinity Propagation Tensor Clustering for Intelligent Fault Diagnosis of Train Bogie Bearing [J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(6):6053-6064. doi: 10.1109/TITS.2023.3253087.( JCR Q1, IF=7.9, ESI Highly Cited Paper)

[3]  Zhenpeng Lao, Deqiang He*, Zhenzhen Jin. Intelligent fault diagnosis for rail transit switch machine based on adaptive feature selection and improved LightGBM[J]. Engineering Failure Analysis,2023,148: 107219. doi:10.1016/ j.engfailanal.2023.107219. (JCR Q1, IF= 4.4，ESI Highly Cited Paper).

[4]  Jinxin Wu, Deqiang He*, Zhenzhen Jin, Xianwang Li, Qin Li, Weibin Xiang. Learning spatial-temporal pairwise and high-order relationships for short-term passenger flow prediction in urban rail transit[J]. Expert Systems with Applications, 2024, 245: 123091. doi: 10.1016/j.eswa.2023.123091.(JCR Q1, IF= 7.5).

[5]  Jinxin Wu, Deqiang He*, Jiayi Li, Jian Miao, Xianwang Li, Hongwei Li, Sheng Shan. Temporal multi-resolution hypergraph attention network for remaining useful life prediction of rolling bearings[J]. Reliability Engineering & System Safety, 2024, 247: 110143. doi: 10.1016/j.ress.2024.110143.(JCR Q1, IF=9.4).

[6]  Yiling He, Deqiang He*, Zhenpeng Lao. Few-shot fault diagnosis of turnout switch machine based on flexible semi-supervised meta-learning network[J]. Knowledge-Based Systems,2024, 294: 111746. doi: 10.1016/j.knosys.2024.111746. (JCR Q1, IF=7.3).

[7]  Qi Liu, Deqiang He*, Zhenzhen Jin, Jian Miao, Sheng Shan, Yanjun Chen, Mingchao Zhang. ViTR-Net: An unsupervised lightweight transformer network for cable surface defect detection and adaptive classification[J]. Engineering Structures, 2024, 313: 118240, doi:10.1016/j.engstruct.2024.118240. (JCR Q1, IF= 5.6).

[8]  Zhenpeng Lao, Deqiang He*, Haimeng Sun, Yiling He, Zhiping Lai, Sheng Shan, Yanjun Chen. Few-shot fault diagnosis of switch machine based on data fusion and balanced regularized prototypical network[J]. Engineering Applications of Artificial Intelligence, 2024, 135: 108847. doi: 10.1016/j.engappai.2024.108847.(JCR Q1, IF=7.5).

[9]  Zheng Sun, Deqiang He*, Yan He, Sheng Shan, Jixu Zhou. A bi-objective optimization model of metro trains considering energy conservation and passenger waiting time[J]. Journal of Cleaner Production, 2024, 437: 140427. doi: 10.1016/j.jclepro.2023.140427.(JCR Q1, IF=9.7).

[10]  Zhenpeng Lao, Deqiang He*, Zhenzhen Jin, Chang Liu, Hui Shang, Yiling He. Few-shot fault diagnosis of turnout switch machine based on semi-supervised weighted prototypical network[J]. Knowledge-Based Systems, 2023, 274: 110634. doi: 10.1016/j.knosys.2023.110634.(JCR Q1, IF=7.2).

[11]  Deqiang He, Chenyu Liu, Zhenzhen Jin*, Rui Ma, Yanjun Chen, Sheng Shan. Fault diagnosis of flywheel bearing based on parameter optimization variational mode decomposition energy entropy and deep learning[J]. Energy, 2022,239:122108. doi: 10.1016/j.energy.2021.122108. (JCR Q1, IF= 8.8).

[12]  Lang Zhang, Deqiang He*, Yan He, Bin Liu, Yanjun Chen, Sheng Shan. Real-time energy saving optimization method for urban rail transit train timetable under delay condition[J], Energy, 2022, 258:124853. doi:10.1016/j.energy.2022.124853. (JCR Q1, IF= 8.85).

[13]  Deqiang He*, Xiaoliang Teng, Yanjun Chen*, Bin Liu, Heliang Wang, Xianwang Li, Rui Ma. Energy saving in metro ventilation system based on multi-factor analysis and air characteristics of and air characteristics of piston vent[J].Applied Energy, 2022, 307:118295. doi: 10.1016/j.apenergy.2021.118295. (JCR Q1, IF=11.44)

[14]  Deqiang He, Lang Zhang, Songlin Guo, Yanjun Chen*, Sheng Shan, Hanqing Jian. Energy-efficient Train Trajectory Optimization Based on Improved Differential Evolution Algorithm and Multi-particle Model[J]. Journal of Cleaner Production, 2021,304:127163. doi:10.1016/j.jclepro.2021.127163. (JCR Q1, IF=11.07)

[15]  Haimeng Sun, Deqiang He*, Jiecheng Zhong, Zhenzhen Jin, Zexian Wei, Zhenpeng Lao, Sheng Shan. Preventive maintenance optimization for key components of subway train bogie with consideration of failure risk[J]. Engineering Failure Analysis, 2023. doi: 10.1016/j.engfailanal.2023.107634. (JCR Q1, IF=4.4).

[16]  Haimeng Sun, Deqiang He*, Hailong Ma, Zefeng Wen, Jianxin Deng. The parameter identification of metro rail corrugation based on effective signal extraction and inertial reference method[J]. Engineering Failure Analysis, 2024, 158: 108043.doi: 10.1016/j.engfailanal.2024.108043. (JCR Q1, IF=4.4).

[17]  Changfu He, Deqiang He*, Zexian Wei, Kai Xu, Yanjun Chen, Sheng Shan. A train bearing imbalanced fault diagnosis method based on extended CCR and multi-scale feature fusion network[J]. Nonlinear Dynamics, 2024, 112:13147–13173. doi: 10.1007/s11071-024-09733-2. (JCR Q1, IF= 5.2).

[18]  Zhenzhen Jin, Deqiang He*,Zhenpeng Lao, Zexian Wei, Xianhui Yin, Weifeng Yang. Early intelligent fault diagnosis of rotating machinery based on IWOA-VMD and DMKELM[J]. Nonlinear Dynamics, 2023,116(6):5287-5306. doi: 10.1007/s11071-022-08109-8 . (JCR Q1, IF= 5.2).

[19]  Deqiang He*, Zhenpeng Lao, Zhenzhen Jin, Changfu He, Sheng Shan, Jian Miao. Train bearing fault diagnosis based on multi-sensor data fusion and dual-scale residual network[J]. Nonlinear Dynamics, 2023, 111(16):14901-14924. doi: 10.1007/s11071-023-08638-w. (JCR Q1, IF=5.2).

[20]  Deqiang He*, Daliang Sun, Yanjun Chen, Guoqiang Liu, Songlin Guo, Rui Ma, Jian Miao, Jianren Liu. Topology Design and Optimization of Train Communication Network Based on Industrial Ethernet[J]. IEEE Transactions on Vehicular Technology, 2022, 71(1):844-855. doi: 10.1109/TVT.2021.3128143. (JCR Q1, IF= 6.8)

 

Representative patents authorized in the past three years.

[1]  Deqiang He, Xueyan Zou, Zhenzhen Jin, et al. An intelligent diagnosis method for train axle bearing faults, June 25, 2024, China, ZL 202210604058.1

[2]  Deqiang He, Zhiheng Zou, Yanjun Chen, et al. A multi-strategy obstacle recognition method for railway transportation based on lidar, April 2, 2024, ZL 202110740833.1

[3]  Deqiang He, Lang Zhang, Yanjun Chen, et al. An algorithm for optimizing urban rail transit train operation parameters, December 8, 2023, China, ZL 202110861678.9

[4]  Deqiang He, Chenyu Liu, Zhenzhen Jin, et al. A fault diagnosis method for rolling bearings of railway rolling stock based on lightweight networks, August 4, 2023, China, ZL 202110741768.4

[5]  Deqiang He, Zhenzhen Jin, Yanjun Chen, et al. A fault diagnosis method for bearings of flywheel energy storage systems based on multi-objective optimization, August 4, 2023, China, ZL 202110813261.5

[6]  Deqiang He, Daliang Sun, Yanjun Chen, et al. A topology optimization method for high-speed train vehicle-to-vehicle network based on IAGA algorithm, August 1, 2023, China, ZL 202110813225.9

[7]  Deqiang He, Zhiheng Zou, Yanjun Chen, et al. A detection method for railway transportation obstacles based on improved convolutional neural networks, August 1, 2023, China, ZL 202110658218.6

[8]  Deqiang He, Zeqian Chen, Daliang Sun, et al. A real-time flow scheduling optimization method for train communication networks based on QSILP algorithm, July 28, 2023, China, ZL 202210604051.X

[9]  Deqiang He, Nianwen Zhou, Chenyu Liu, et al. A reliability prediction and optimization method for key components of urban rail transit trains, May 5, 2023, China, ZL 202110597052.1

[10]  Deqiang He, Zhou Jiang, Jian Miao, et al. An alien object detection method for high-speed train undercarriage based on Faster R-CNN, April 7, 2023, China, ZL 201910633675.2

[11]  Deqiang He, Zhiheng Zou, Liqiong Liu, et al. A railway transportation obstacle detection method based on deep learning, March 14, 2023, China, ZL 202011550241.5

[12]  Deqiang He, Jiwei Meng, Jian Miao, et al. A proactive maintenance decision optimization model for subway vehicle bogie components, November 11, 2022, China, ZL 202010141832.0

[13]  Deqiang He, Zikai Yao, Tao Chen, et al. An undercarriage foreign object recognition method for high-speed trains based on deep learning, November 11, 2022, China, ZL 202010141770.3

[14]  Deqiang He, Chao Ge, Qiyang Liu, et al. A proactive maintenance optimization method for multi-component reliability of subway vehicles based on reliability, October 11, 2022, China, ZL 201810994975.9

[15]  Deqiang He, Songlin Guo, Yanjun Chen, et al. Optimization method for urban rail transit train operation timetable and speed-running curve, October 11, 2022, China, ZL 202010141777.5

 

Main Awards Received:

[1]  Deqiang He (3/15), Application Research of Inverter Type Rail Transit Regenerative Braking Energy Recovery Device, First Prize of Engineering Construction Science and Technology Award, 2022.

[2]  Deqiang He (1/8), Energy-saving Optimization Control and Multi-train Collaborative Scheduling Technology and Application of Urban Rail Transit Trains, Second Prize in the Technical Invention Category of Guangxi Science and Technology Progress Award, 2019.

[3]  Deqiang He (1/7), Key Technologies and Applications of Cloud Platform-based Intelligent Operation and Maintenance System for Urban Rail Transit Trains, Third Prize of Guangxi Science and Technology Progress Award, 2018.

[4]  Deqiang He (1/7), Research and Application of Key Technologies of Remote Fault Diagnosis System for Rail Transit Trains, Third Prize of Guangxi Science and Technology Progress Award, 2016.

[5]  Deqiang He (2/9), Research on High-speed Train Fault Diagnosis and Intelligent Maintenance Technology, Second Prize of Hunan Science and Technology Progress Award, 2014.

[6]  Deqiang He (4/15), Locomotive Non-Fire Return Power Supply Device, Third Prize of China Railway Society Science and Technology Award, 2022.

 

Main Scientific Research Projects Undertaken:：

[1]  National Natural Science Foundation of China Joint Fund Key Project, U22A2053, Research on Intelligent Operation and Maintenance Basic Theory and Key Technologies of Urban Rail Transit Train Key Components.

[2]  National Natural Science Foundation of China General Project, 52072081, Research on High-Reliability Large-Capacity High-Speed Train Internet of Vehicles Architecture and Key Technologies.

[3]  National Natural Science Foundation of China Regional Project, 51765006, Research on Energy-saving Optimization Control and Multi-train Cooperative Scheduling of Urban Rail Transit Trains under Complex Line Conditions.

[4]  National Natural Science Foundation of China Regional Project, 51165001, Research on High-Speed Train State Monitoring and Fault Diagnosis Technology Based on Ethernet.

[5]  Guangxi Innovation-Driven Development Special Project, Guike AA20302010, Research and Application of Urban Rail Transit Fully Automatic Driving Train Development and Achievement Transformation.

[6]  Guangxi Science and Technology Major Project, Guike 2023AA10002, Research and Application of Key Technologies for Tractor-type Electric Excavator.

[7]  Guangxi Key R&D Program, Guike AB22035008, Research and Application of Key Technologies for Intelligent Operation and Maintenance of Smart Metro Signaling Based on Big Data and Cloud Platform.

[8]  Guangxi Key R&D Program Project, Guike AB17195046, Research on Key Technologies for Comprehensive State Safety Perception and Early Warning Network of High-Speed Trains.

[9]  Guangxi Natural Science Foundation Key Project, 2017GXNSFDA198012, Research on Key Technologies for Energy-saving Optimization Control of Urban Rail Transit Trains.

[10]  Guangxi Science and Technology Tackle Key Project, Guike GONG1598009-6, Development and Application Demonstration of Harmonic Electric Locomotive Power Supply Device Detection System.