學(xué)術(shù)帶頭人:
賀德強(qiáng)(博士,二級(jí)教授,博士研究生導(dǎo)師):廣西八桂學(xué)者,廣西模范教師,廣西十百千人才工程第二層次人選、廣西高校優(yōu)秀人才資助計(jì)劃資助人選、寶鋼優(yōu)秀教師獎(jiǎng)、南寧市特聘專家等榮譽(yù)稱號(hào)。中國(guó)振動(dòng)工程學(xué)會(huì)理事、中國(guó)儀器儀表協(xié)會(huì)測(cè)量與控制專業(yè)委員會(huì)常務(wù)委員、中國(guó)振動(dòng)工程學(xué)會(huì)轉(zhuǎn)子動(dòng)力學(xué)專業(yè)委員會(huì)理事、中國(guó)人工智能學(xué)會(huì)智能制造專業(yè)委員會(huì)委員兼副秘書長(zhǎng)、中國(guó)機(jī)械工程學(xué)會(huì)材料分會(huì)青年工作委員會(huì)委員、全國(guó)軌道交通電氣設(shè)備與系統(tǒng)標(biāo)準(zhǔn)化技術(shù)委員會(huì)(SAC/ TC278)智能制造工作組(WG1)委員、全國(guó)土方機(jī)械標(biāo)準(zhǔn)化技術(shù)委員會(huì)電動(dòng)土方機(jī)械分技術(shù)委員會(huì)(SAC/TC334/SC3)委員、廣西機(jī)械工程學(xué)會(huì)第八屆理事會(huì)理事,《廣西大學(xué)學(xué)報(bào)(自然科學(xué)版)》編委、《控制與信息技術(shù)》編委等。
主要成員:
苗劍(博士,教授),鄧建新(博士,教授),劉斌(博士,副教授),陳彥君(博士,副教授),李先旺(博士,講師),靳震震(博士,助理教授),項(xiàng)載毓(博士,助理教授),付洋(博士,助理教授),李琴(博士,助理教授),楊秋梅(博士,助理教授),李宏偉(博士,助理教授)。
研究方向:
1、列車遠(yuǎn)程故障診斷:針對(duì)我國(guó)軌道交通列車的特點(diǎn)和需求,研究基于大容量網(wǎng)絡(luò)的車載信息采集與故障診斷系統(tǒng)、車-地?zé)o線數(shù)據(jù)傳輸系統(tǒng)、地面信息處理與智能維護(hù)系統(tǒng)關(guān)鍵技術(shù),實(shí)現(xiàn)對(duì)軌道交通列車的遠(yuǎn)程狀態(tài)監(jiān)控和故障診斷功能,構(gòu)筑適應(yīng)軌道交通列車的故障診斷信息技術(shù)平臺(tái),為提高軌道交通列車的運(yùn)用、維護(hù)與管理水平,為提高軌道交通列車安全性、可靠性、可用性和可維護(hù)性提供信息化輔助支撐平臺(tái)。
2、列車智能化運(yùn)維:針對(duì)高溫高濕環(huán)境和喀斯特地貌下軌道交通列車運(yùn)維的需求,開展基于車聯(lián)網(wǎng)的軌道交通列車健康管理系統(tǒng)關(guān)鍵技術(shù)研究,利用數(shù)據(jù)挖掘、機(jī)器學(xué)習(xí)等方法對(duì)列車實(shí)時(shí)狀態(tài)數(shù)據(jù)和車載記錄數(shù)據(jù)進(jìn)行分析處理,通過(guò)數(shù)據(jù)擬合完成故障趨勢(shì)判別,實(shí)現(xiàn)列車的主動(dòng)安全防護(hù)、故障預(yù)警、壽命預(yù)測(cè)和智能維護(hù)等功能。
3、電動(dòng)工程機(jī)械/汽車能源管理與控制:針對(duì)電動(dòng)工程機(jī)械/汽車能源損耗高和電能變換效率低的現(xiàn)狀,研究換流電路拓?fù)浜驼{(diào)制優(yōu)化方法、主電路快速故障診斷、電池能源管理與優(yōu)化控制關(guān)鍵技術(shù),通過(guò)提升能量轉(zhuǎn)換效率,提高換流系統(tǒng)的運(yùn)行效率和可靠性,實(shí)現(xiàn)電動(dòng)工程機(jī)械/汽車更加精確的電能控制和監(jiān)測(cè)。
4、營(yíng)林機(jī)械裝備設(shè)計(jì)與優(yōu)化:針對(duì)南方丘陵山地的特點(diǎn)和現(xiàn)代營(yíng)林作業(yè)的需求,研究適應(yīng)陡坡山地的南方丘陵多功能營(yíng)林機(jī)械、營(yíng)林機(jī)械配套裝備可靠性優(yōu)化設(shè)計(jì)、營(yíng)林機(jī)械裝備現(xiàn)代自動(dòng)控制技術(shù),通過(guò)設(shè)計(jì)功能多樣化且功能切換方便的機(jī)械來(lái)實(shí)現(xiàn)營(yíng)林作業(yè)的一機(jī)多用,提高丘陵山地營(yíng)林機(jī)械的利用率,降低工作能耗并提高營(yíng)林業(yè)的生產(chǎn)效率。
科研成果:
近三年發(fā)表的代表性論文
[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 . (SCI一區(qū), Top, IF= 7.5,ESI高被引).
[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, doi: 10.1109/TITS.2023.3253087.(SCI一區(qū), Top, IF=7.9, ESI高被引)
[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. (SCI一區(qū), IF=4.4,ESI高被引).
[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.(SCI一區(qū), Top, 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.(SCI一區(qū), Top, 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. (SCI一區(qū), Top, 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. (SCI一區(qū),Top, 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.(SCI一區(qū),TOP,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.(SCI一區(qū), 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.(SCI一區(qū), Top, 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. (SCI一區(qū), Top, 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. (SCI一區(qū), Top, 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. (SCI一區(qū), Top, 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. (SCI一區(qū), Top, 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. (SCI一區(qū), 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. (SCI一區(qū), 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. (SCI二區(qū), TOP, 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 . (SCI二區(qū), TOP, 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. (SCI二區(qū),TOP, 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. (SCI二區(qū), Top, IF= 6.8)
近三年授權(quán)的代表性專利
[1]賀德強(qiáng),鄒雪妍,靳震震,等.一種列車軸承故障智能診斷方法,2024.06.25,中國(guó),ZL 202210604058.1
[2]賀德強(qiáng),鄒智恒,陳彥君,等.一種基于激光雷達(dá)的多策略軌道交通障礙物識(shí)別方法,2024.04.02,ZL 202110740833.1
[3]賀德強(qiáng),張朗,陳彥君,等.一種城市軌道交通列車運(yùn)行參數(shù)優(yōu)化算法,2023.12.08,中國(guó),ZL 202110861678.9
[4]賀德強(qiáng),劉晨宇,靳震震,等.一種基于輕量級(jí)網(wǎng)絡(luò)的軌道列車滾動(dòng)軸承故障診斷方法,2023.08.04,中國(guó),ZL 202110741768.4
[5]賀德強(qiáng),靳震震,陳彥君,等.一種基于多目標(biāo)優(yōu)化飛輪儲(chǔ)能系統(tǒng)軸承的故障診斷方法,2023.08.04,中國(guó),ZL 202110813261.5
[6]賀德強(qiáng),孫大亮,陳彥君,等.一種基于IAGA算法的高速列車車聯(lián)網(wǎng)拓?fù)鋬?yōu)化方法,2023.08.01,中國(guó),ZL 202110813225.9
[7]賀德強(qiáng),鄒智恒,陳彥君,等.一種基于改進(jìn)卷積神經(jīng)網(wǎng)絡(luò)的軌道交通障礙物檢測(cè)方法,2023.08.01,中國(guó),ZL 202110658218.6
[8]賀德強(qiáng),陳澤前,孫大亮,等.一種基于QSILP算法的列車通信網(wǎng)絡(luò)實(shí)時(shí)流調(diào)度優(yōu)化方法,2023.07.28,中國(guó),ZL 202210604051.X
[9]賀德強(qiáng),周念玟,劉晨宇,等.一種城軌列車關(guān)鍵部件的可靠度預(yù)測(cè)優(yōu)化方法,2023.05.05,中國(guó),ZL 202110597052.1
[10]賀德強(qiáng),江洲,苗劍,等.一種基于FasterR-CNN的高速列車車底異物檢測(cè)方法,2023.04.07,中國(guó),ZL 201910633675.2
[11]賀德強(qiáng),鄒智恒,劉力瓊,等.一種基于深度學(xué)習(xí)的軌道交通障礙物檢測(cè)方法,2023.03.14,中國(guó),ZL 202011550241.5
[12]賀德強(qiáng),蒙基偉,苗劍,等.一種地鐵車輛轉(zhuǎn)向架多部件預(yù)防性維修決策優(yōu)化模型,2022.11.11,中國(guó),ZL 202010141832.0
[13]賀德強(qiáng),姚子鍇,陳滔,等.一種基于深度學(xué)習(xí)的高速列車車底異物識(shí)別方法,2022.11.11,中國(guó),ZL 202010141770.3
[14]賀德強(qiáng),葛超,劉旗揚(yáng),等.一種基于可靠度的地鐵車輛多部件的預(yù)防性維修優(yōu)化方法,2022.10.11,中國(guó),ZL 201810994975. 9
[15]賀德強(qiáng),郭松林,陳彥君,等.城市軌道交通列車運(yùn)營(yíng)時(shí)刻表和速度運(yùn)行曲線優(yōu)化方法,2022.10.11,中國(guó),ZL 202010141777.5
獲得的主要獎(jiǎng)勵(lì):
[1]賀德強(qiáng)(3/15),逆變式軌道交通制動(dòng)能量回收裝置的應(yīng)用研究,2022年工程建設(shè)科學(xué)技術(shù)獎(jiǎng),一等獎(jiǎng),2022
[2]賀德強(qiáng)(1/8),城市軌道交通列車節(jié)能優(yōu)化控制與多車協(xié)同調(diào)度技術(shù)及應(yīng)用,廣西科技進(jìn)步獎(jiǎng)技術(shù)發(fā)明類,二等獎(jiǎng),2019
[3]賀德強(qiáng)(1/7),基于云平臺(tái)的城市軌道交通列車智能化運(yùn)維系統(tǒng)關(guān)鍵技術(shù)及應(yīng)用,廣西科技進(jìn)步獎(jiǎng),三等獎(jiǎng),2018
[4]賀德強(qiáng)(1/7),軌道交通列車遠(yuǎn)程故障診斷系統(tǒng)關(guān)鍵技術(shù)研究與應(yīng)用,廣西科技進(jìn)步獎(jiǎng),三等獎(jiǎng),2016
[5]賀德強(qiáng)(2/9),高速列車故障診斷與智能維護(hù)技術(shù)研究,湖南省科技進(jìn)步獎(jiǎng),二等獎(jiǎng),2014
[6]賀德強(qiáng)(4/15),機(jī)車無(wú)火回送電源裝置,2022年度中國(guó)鐵道學(xué)會(huì)科學(xué)技術(shù)獎(jiǎng),三等獎(jiǎng),2022
主持的主要科研項(xiàng)目:
[1]國(guó)家自然科學(xué)基金聯(lián)合基金重點(diǎn)項(xiàng)目,U22A2053,城市軌道交通列車關(guān)鍵部件智能運(yùn)維基礎(chǔ)理論與關(guān)鍵技術(shù)研究
[2]國(guó)家自然科學(xué)基金面上項(xiàng)目,52072081,高可靠大容量高速列車車聯(lián)網(wǎng)架構(gòu)及關(guān)鍵技術(shù)研究
[3]國(guó)家自然科學(xué)基金地區(qū)項(xiàng)目,51765006,復(fù)雜線路條件下城市軌道交通列車節(jié)能優(yōu)化控制與多車協(xié)同調(diào)度研究
[4]國(guó)家自然科學(xué)基金地區(qū)項(xiàng)目,51165001,基于以太網(wǎng)的高速列車狀態(tài)監(jiān)測(cè)與故障診斷技術(shù)研究
[5]廣西創(chuàng)新驅(qū)動(dòng)發(fā)展專項(xiàng),桂科AA20302010,城市軌道交通全自動(dòng)駕駛列車研發(fā)及成果轉(zhuǎn)化應(yīng)用
[6]廣西科技重大專項(xiàng),桂科2023AA10002,拖電式電動(dòng)挖掘機(jī)關(guān)鍵技術(shù)研究和應(yīng)用
[7]廣西重點(diǎn)研發(fā)計(jì)劃,桂科AB22035008,基于大數(shù)據(jù)和云平臺(tái)的智慧地鐵信號(hào)智能運(yùn)維關(guān)鍵技術(shù)研究及應(yīng)用
[8]廣西重點(diǎn)研發(fā)計(jì)劃項(xiàng)目,桂科AB17195046,高速列車綜合狀態(tài)安全感知與預(yù)警網(wǎng)絡(luò)關(guān)鍵技術(shù)研究
[9]廣西自然科學(xué)基金重點(diǎn)項(xiàng)目,2017GXNSFDA198012,城市軌道交通列車節(jié)能優(yōu)化控制關(guān)鍵技術(shù)研究
[10]廣西科技攻關(guān)項(xiàng)目,桂科攻1598009-6,和諧型電力機(jī)車供電裝置檢測(cè)系統(tǒng)開發(fā)及應(yīng)用示范