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邓艾东

时间:2024-08-25浏览:879

论文:

[1]  Liu YangDeng AidongDeng MinqiangShi YaoweiLi Jing. Transforming the Open Set Into a Pseudo-Closed Set: A Regularized GAN for Domain Adaptation in Open-Set Fault Diagnosis[J] IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT202372:7355-7366.

[2]  Xu Meng Shi Yaowei Deng Minqiang Liu Yang Ding Xue Deng Aidong. An improved multi-scale branching convolutional neural network for rolling bearing fault diagnosis [J]. PLOS ONE202318(9)1-21.

[3]  Shi YaoweiDeng AidongDeng MinqiangLi JingXu MengZhang Shun Xu Shuo. Domain transferability-based deep domain generalization method towards actual fault diagnosis scenarios [J]. IEEE Transactions on Industrial Informatics202219(6):7355-7366.

[4]  Shi YaoweiDeng AidongDeng MinqiangXu MengLiu YangDing XueBian Wenbin. Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY2023235109188

[5]  Deng Minqiang Deng Aidong Shi Yaowei Xu Meng. Correlation regularized conditional adversarial adaptation for multi-target -domain fault diagnosis [J]. IEEE Transactions on Industrial Informatics 2022 18(12) 8692-8702.  

[6]  Shi YaoweiDeng AidongDeng MinqiangXu MengLiu YangDing XueBian Wenbin. Instance adaptive multisource transfer for fault diagnosis of rotating machinery under variable working conditions [J]. MEASUREMENT2022202111797

[7]  Shi YaoweiDeng AidongDeng MinqiangXu MengLiu YangDing XueLi Jing. Transferable adaptive channel attention module for unsupervised cross-domain fault diagnosis[J]. Reliability Engineering & System Safety20222261-12. 

[8]  Deng Minqiang Deng Aidong Shi Yaowei Liu Yang Xu Meng. A novel sub-label learning mechanism for enhanced cross-domain fault diagnosis of rotating machinery [J]. Reliability Engineering & System Safety 2022 225108589.

[9]  Shi YaoweiDeng AidongDeng MinqiangXu MengLiu YangDing Xue. A novel multiscale feature adversarial fusion network for unsupervised cross-domain fault diagnosis [J]. MEASUREMENT2022200111616

[10]Deng Minqiang Deng Aidong Shi Yaowei Liu Yang Xu Meng. Intelligent fault diagnosis based on sample weighted joint adversarial network [J]. Neurocomputing 2022 488168-182.

[11]Shi YaoweiDeng AidongDing XueZhang ShunXu ShuoLi Jing .Multisource domain factorization network for cross-domain fault diagnosis of rotating machinery An unsupervised multisource domain adaptation method[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING2022164108219 

[12]Deng MinqiangDeng AidongZhu JingShi YaoweiLiu Yang. Intelligent fault diagnosis of rotating components in the absence of fault data A transfer-based approach[J]. MEASUREMENT20211731-15 

[13]Deng MinqiangDeng AidongZhu JingShi YaoweiLiu YangChen Qiang. Resonance-based bandwidth Fourier decomposition method for gearbox fault diagnosis[J]. Measurement Science and Technology2021323):1-15

[14]Shi YaoweiDeng AidongDeng MinqiangZhu JingLiu YangCheng Qiang. Enhanced Lightweight Multiscale Convolutional Neural Network for Rolling Bearing Fault Diagnosis[J].IEEE ACCESS20208217723-217734.

[15]Zhu JingDeng AidongLi JingDeng MinqiangSun WenqingCheng QiangLiu Yang. Resonance-based sparse adaptive variational mode decomposition and its application to the feature extraction of planetary gearboxes[J]. PLOS ONE2020154):1-20

[16]Zhu JingDeng AidongLi JingDeng MinqiangSun WenqingCheng QiangLiu Yang. Resonance-based sparse improved fast independent component analysis and its application to the feature extraction of planetary gearboxes[J]. Journal of Mechanical Science and Technology20203411):4465-4474

[17]Deng MinqiangDeng AidongZhu JingZhai YimengSun WenqingChen QiangLiu Yang. Bandwidth Fourier decomposition and its application in incipient fault identification of rolling bearings[J]. Measurement Science and Technology 2020311):1-18 

[18]Minqiang DengAidong DengJing Zu and Wenqing Sun. Adaptive Bandwidth Fourier Decomposition Method for Multi-Component Signal Processing [J]. IEEE ACCESS20197 109776-109791 

[19]Qiang ChengAidong DengJing LiYimeng Zhai. Application of Gradient Boosting Decision Tree in Wind Turbine Drivetrain Recognition[C].Lect. Notes Comput. Sci. ICAIS 20192019 - July 28New York cityUnited statesv 11632 LNCS585-594

[20]Chen GHao HTDeng AD. Linear and nonlinear modeling of self-excited acoustic oscillations in a T-shaped thermoacoustic engine[J]. AIP ADVANCES20218(11)

[21]Yang WeiboLi JingPeng WeiDeng Aidong. A Rub-Impact Recognition Method Based on Improved Convolutional Neural Network[J]. CMC-COMPUTERS MATERIALS & CONTINUA2020,(63):283-299

[22]Jing LiAidong DengYong YangXinmin ChengDongying Liuand Li Zhao. A new iterative near-field coherent subspace method for rub-impact fault localization using AE technique[J]Journal of Mechanical Science and Technology201731(5)2035-2045.

[23]Li JingDeng AidongLiu DongyingZhang RuiZhao Li. Near-field multiple signal classification algorithm for acoustic emission source localization in rolling element rub-impact fault diagnostics[J]. ICIC Express Letters2016103):663 - 668  

[24]Aidong DengHao CaoHang TongLi ZhaoKang QinXi YanRecognition of Acoustic Emission Signal Based on the Algorithms of TDNN and GMM[J]Applied Mathematics & Information Sciences201482):907-916

[25]Aidong DengHang TongJianeng TangHao CaoKang QinXi YanStudy on Location Algorithms of Beamforming based on MVDR [J]Applied Mathematics & Information Sciences201376):2455-2466

[26]Deng Aidong Zhang Xiaodan Tang Jianeng Zhao LiQin KangLocalization of Acoustic Emission Source Based on Chaotic Neural Networks [J]Applied Mathematics & Information Sciences201263):713-719

[27]Deng AidongTang JianengZhao LiZou CairongThe variable-interval arithmetic coding using asymptotic deterministic randomness for data compression and encryption[J]Journal of Statistical Computation and Simulation20128310):1545-1555

[28]Aidong DengLi ZhaoXin WeiApplication of quantum neural networks in localization of acoustic emission [J]Journal of Systems Engineering and Electronics201122(3)507-512

[29]Shi Yaowei Deng Aidong Xu Meng Deng Minqiang. Adaptive mixup-based domain adaptation method for intelligent fault diagnosis [C]. 2023 13th International Conference on Power Energy and Electrical Engineering2023 296-300.

[30]Xu MengDeng Aidong Liu Dongchuan Shi Yaowei. An enhanced deep forest rolling bearing fault diagnosis method [C]. 2023 13th International Conference on Power Energy and Electrical Engineering2023 306-310.

[31]Deng MinqiangDeng AidongShi Yaowei. Self-supervised Adversarial Network for Intelligent Fault Diagnosis [A]. IEEE 2021 IEEE International Conference on Electronic Communications Internet of Things and Big Data [C]. China Taiwan 2021 323-326. 

[32]Aidong DengLi ZhaoYongqiang BaoAcoustic Emission Recognition Using Fuzzy Entropy       [C]Proceedings of 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems ICIS 2009ShanghaiChina2009V475-79

[33]Aidong DengLi ZhaoXin WeiThe Application of Wavelet Neural Network Optimized by Particle Swarm in Localization of Acoustic Emission Source[C]Proceedings of 16th International Conference on Neural Information Processing ICONIP 2009Lect Notes ComputSci.,BangkokThailand20095864738-745

[34]Aidong DengLi ZhaoYan ZhaoStudy on Algorithms of Acoustic Emission Source Localization in Complicated Environment[C]Proceedings of 9th International Conference on Electronic Measurement & InstrumentsICEMI’2009BeijingChina2009V22_462-2_466

[35]Aidong DengLi ZhaoYan ZhaoRecognition of Acoustic Emission Signal Based on MAE and Propagation Theory[C]Management and Service Science2009MASS '09BeijingChina2009V61-4

[36]Aidong DengLi ZhaoYan ZhaoA New Algorithm of AE Localization Using Sub-gradient Projection[C]Proceedings of the Second International Conference on Computer Science and Software Engineering CSSE2009WuhanChina

[37]Aidong DENGWei GAOYongqiang BAOLi ZhaoResearch of acoustic emission signal enhancement based on Discrete Fractional cosine Transform[C]Proceedings of the 7th World Congress on Intelligent Control and AutomationWCICA'08ChongqingChina20085852-5857

[38]Aidong DENGWei GAOYongqiang BAOLi ZhaoStudy on Recognition Characteristics of Acoustic Emission Based on Fractal Dimension[C]Proceedings - The 2008 International Conference on Embedded Software and SystemsICESS2008 SymposiaChengduChina2008475-478

[39]邓艾东,赵力,包永强.粒子群优化小波神经网络用于碰摩声发射源定位[J].中国电机工程学报,200929(32)83-87

[40]邓艾东,包永强,赵力.转子碰摩声发射源定位中的广义互相关时延估计研究[J].中国电机工程学报,200929(14)86-92

[41]邓艾东,高亹,杨建刚,赵力.离散分数余弦变换在碰摩声发射信号降噪中的应用研究[J].中国电机工程学报,20082820):72-76

[42]邓艾东,包永强赵力.基于高斯混合模型的转子碰摩声发射识别方法研究[J].机械工程学报,201046(15)52-58

[43]邓艾东,包永强赵力基于能量衰减模型的转子碰摩声发射源次梯度投影定位方法[J].机械工程学报,2010469):66-72

[44]邓艾东,包永强赵力.基于模糊熵的转子碰摩声发射信号的识别[J].机械工程学报,201046(3)71-75

[45]邓艾东,包永强,高亹,赵力.旋转机械碰摩声发射信号的分形特征分析算法研究[J].仪器仪表学报,200829(6)1285-1289

[46]邓艾东童航秦康曹浩颜喜.一种改进的最小方差自适应时延估计算法在碰摩声发射定位中的应用[J].东南大学学报:自然科学版,201242(z2)320-325

[47]邓艾东,童航,张如洋,蒋章,高亹.基于模态分析的转子碰摩声发射特征研究[J].东南大学学报:自然科学版,201040(6)1232-1237

[48]邓艾东,赵力包永强,高亹.噪声环境下基于小波熵的声发射识别研究[J].东南大学学报:自然科学版,200939(6)1151-1155

[49]卞文彬,邓艾东,刘东川,赵敏,刘洋,李晶. 基于改进深度残差收缩网络的风电机组滚动轴承故障诊断方法[J].机械工程学报,202359(12)202-214.

[50]徐硕,邓艾东,杨宏强,范永胜,邓敏强,刘东川. 基于改进残差网络的旋转机械故障诊断[J].太阳能学报,202344(07)409-418. 2023-07-28

[51]马天霆,孙振波,邓艾东等.基于频率诱导变分模态分解的齿轮箱故障诊断[J].东南大学学报(自然科学版)202353(04)702-708.

[52]王鹏程,邓艾东,凌峰,邓敏强,刘洋.基于PSO-SEBD的风电机组滚动轴承故障诊断[J].振动与冲击,202342(07):281-288.

[53]凌峰,杨宏强,邓艾东,王鹏程,董路南,卞文彬. 基于SHAVD-AS的风电齿轮箱故障诊断[J].太阳能学报,202344(06)477-483.

[54]刘东川,邓艾东,赵敏,卞文彬,许猛. 基于改进深度森林的旋转机械故障诊断方法[J]. 振动与冲击,202241(21)19-27

[55]刘洋,程强,史曜炜,王煜伟,王姗,邓艾东.基于注意力模块及1D-CNN的滚动轴承故障诊断[J].太阳能学报,202243(03)462-468.

[56]孙文卿,邓艾东,邓敏强,刘洋,程强.基于模型融合的风电机组齿轮箱故障诊断[J].太阳能学报,202243(01)64-72.

[57]丁雪,邓艾东,李晶,邓敏强,徐硕,史曜炜.基于多尺度和注意力机制的滚动轴承故障诊断[J].东南大学学报(自然科学版)202252(01)172-178.

[58]邓敏强,邓艾东,朱静,史曜炜,马天霆. 基于BFDMSCNN的风电滚动轴承智能故障诊断[J].东南大学学报(自然科学版)202151(03)521-528.  

[59]邓敏强,邓艾东,朱静,许千寿,王姗,王圣. 基于模态叠加法的风电机组塔架实时状态研究[J].太阳能学报,202142(03)63-70.

[60]朱静,邓艾东,邓敏强,程强,刘洋.基于MED和自适应VMD的行星齿轮箱故障诊断方法[J].东南大学学报(自然科学版)202050(04)698-704.

[61]董路南,邓艾东,范永胜,等. 基于VMD和改进DenseNet的滚动轴承故障诊断[J]. 动力工程学报,202343(11)1500-1505.

[62]马天霆,孙振波,邓敏强,邓艾东. 基于RSBLMD算法的风机滚动轴承早期故障诊断[J].动力工程学报,202040(12)982-987.

[63]朱静,邓艾东,邓敏强,翟怡萌,孙文卿,王姗. 基于RSIFICA的行星齿轮箱故障诊断方法[J].东南大学学报(自然科学版)202050(02)377-384 

[64]孙文卿,邓艾东,邓敏强,朱静,翟怡萌,程强,刘洋. 基于随机森林和自编码的滚动轴承多视角特征融合(英文)[J] .东南大学学报(英文版)2019353):302-309 

[65]张瑞,邓艾东,司晓东,刘东瀛,李晶. 一种新的声发射信号消噪及故障诊断方法[J]. 振动与冲击,2018374):75-81

[66]刘东瀛,邓艾东,刘振元,李晶,张瑞,黄宏伟.基于EMD与相关系数原理的故障声发射信号降噪研究[J]. 振动与冲击,20173619):71-77

[67]秦康,邓艾东,张红星,颜喜.基于压缩感知技术的旋转机械碰摩声发射信号压缩[J].中国电机工程学报,201333(增刊):160-165

[68]彭威,李晶,刘卫东,邓艾东. AE声谱图特征的转子碰摩故障识别方法研究[J]. 振动工程学报,201932(06)1094-1103. 

[69]李晶,邓艾东,杨勇,赵力,郭如雪.近场子空间聚焦的碰摩故障声发射定位方法[J].声学学报,2017426):703-712

[70]蒋章,邓艾东.以赫斯特指数与近似熵为声发射特征参数的碰摩故障识别[J].中国电机工程学报,201030(29)96-102

[71]蒋章,邓艾东,蔡宾宏.基于梯度法的自适应广义形态滤波在碰摩声发射信号降噪中的应用[J].中国电机工程学报,201131(8)87-92

合著:

Acoustic Emission》.ISBN978-953-51-0056-0 PublisherInTech2012-3

《能源动力工程导论》. ISBN978 7 5198 6807 9,中国电力出版社,20229月第一版