1. 高端装备状态监测与故障诊断 （Condition Monitoring and Faults Diagnosis, CMFD）

2. 机械系统动力学建模 （Mechanical System Dynamics Modeling, MSDM）

3. 信号处理与机器学习（Signal Processing and Machine Learning, SPML）

4. 人工智能与模式识别（Artificial Intelligence and Pattern Recognition, AIPR）

5. 故障预测与健康管理 （Prognostics and Health Management, PHM）

6. 结构损伤识别与健康监测 （Structural Damage Identification and Health Monitoring, SDIHM）

发表论文情况：

（1）以第一作者或通讯作者发表的学术论文（部分）：

[1] Xiaoan Yan, Minping Jia*. Application of CSA-VMD and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings[J]. Mechanical Systems and Signal Processing, 2019, 122: 56-86.（SCI一区TOP期刊，ESI高被引论文）

[2] Yan Xiaoan, Jia Minping*. Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection[J]. Knowledge-Based Systems, 2019, 163: 450-471.（SCI一区TOP期刊，ESI高被引论文）

[3] Xiaoan Yan , Minping Jia*. A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing[J]. Neurocomputing, 2018, 313: 47-64.（SCI二区TOP期刊，ESI高被引论文）

[4] Xiaoan Yan*, Daoming She, Yadong Xu. Deep order-wavelet convolutional variational autoencoder for fault identification of rolling bearing under fluctuating speed conditions[J]. Expert Systems with Applications, 2023, 216: 119479.（SCI一区TOP期刊，ESI高被引论文）

[5] Xiaoan Yan*, Wangji Yan, Yadong Xu, Ka-Veng Yuen. Machinery multi-sensor fault diagnosis based on adaptive multivariate feature mode decomposition and multi-attention fusion residual convolutional neural network[J]. Mechanical Systems and Signal Processing, 2023, 202: 110664.（SCI一区TOP期刊）

[6] Xiaoan Yan*, Ying Liu, Yadong Xu, Minping Jia. Multichannel fault diagnosis of wind turbine driving system using multivariate singular spectrum decomposition and improved Kolmogorov complexity[J]. Renewable Energy, 2021, 170: 724-748.（SCI一区TOP期刊）

[7] Xiaoan Yan*, Daoming She, Yadong Xu, Minping Jia. Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process[J]. Knowledge-Based Systems, 2021, 226: 107142.（SCI一区TOP期刊）

[8] Xiaoan Yan*, Ying Liu, Minping Jia. Multiscale cascading deep belief network for fault identification of rotating machinery under various working conditions[J]. Knowledge-Based Systems, 2020, 193(4): 105484.（SCI一区TOP期刊）

[9] Xiaoan Yan*, Ying Liu, Yadong Xu, Minping Jia. Multistep forecasting for diurnal wind speed based on hybrid deep learning model with improved singular spectrum decomposition[J]. Energy Conversion and Management, 2020, 225: 113456.（SCI一区TOP期刊）

[10] Maoyou Ye, Xiaoan Yan*, Dong Jiang, Ling Xiang, Ning Chen. MIFDELN: A multi-sensor information fusion deep ensemble learning network for diagnosing bearing faults in noisy scenarios[J]. Knowledge-Based Systems, 2024, 284: 111294.（SCI一区TOP期刊）

[11] Xiaoan Yan, Minping Jia*, Wan Zhang, Lin Zhu. Fault diagnosis of rolling element bearing using a new optimal scale morphology analysis method[J]. ISA transactions, 2018, 73: 165-180.（SCI二区TOP期刊）

[12] Xiaoan Yan, Minping Jia*, Zhuanzhe Zhao. A novel intelligent detection method for rolling bearing based on IVMD and instantaneous energy distribution-permutation entropy[J]. Measurement, 2018: 435-447.（SCI二区TOP期刊）

[13] Xiaoan Yan*, Ying Liu, Minping Jia. Health condition identification for rolling bearing using a multi-domain indicator-based optimized stacked denoising autoencoder[J]. Structural Health Monitoring, 2020, 19: 1602-1626.（SCI二区TOP期刊）

[14] Xiaoan Yan*, Wangji Yan, Ka-Veng Yuen, Zhixin Yang, Xianbo Wang. An adaptive variational mode extraction method based on multi-domain and multi-objective optimization for bearing fault diagnosis[J]. Structural Health Monitoring, 2023, 22: 2708-2733.（SCI二区TOP期刊）

[15] Xiaoan Yan*, Ying Liu, Dongsheng Huang, Minping Jia. A new approach to health condition identification of rolling bearing using hierarchical dispersion entropy and improved Laplacian score[J]. Structural Health Monitoring, 2021, 20: 1169-1195.（SCI二区TOP期刊）

[16] Xiaoan Yan*, Minping Jia. Bearing fault diagnosis via a parameter-optimized feature mode decomposition[J]. Measurement, 2022, 203: 112016.（SCI二区TOP期刊）

[17] Xiaoan Yan*, Ying Liu, Minping Jia. Research on an enhanced scale morphological-hat product filtering in incipient fault detection of rolling element bearings[J]. Measurement, 2019, 147: 106856.（SCI二区TOP）

[18] Maoyou Ye, Xiaoan Yan*, Ning Chen, Ying Liu. A robust multi-scale learning network with quasi-hyperbolic momentum-based Adam optimizer for bearing intelligent fault diagnosis under sample imbalance scenarios and strong noise environment[J]. Structural Health Monitoring, 2023: 14759217231192363.（SCI二区TOP期刊）

[19] Maoyou Ye, Xiaoan Yan*, Ning Chen, Minping Jia. Intelligent fault diagnosis of rolling bearing using variational mode extraction and improved one-dimensional convolutional neural network[J]. Applied Acoustics, 2023, 202: 109143.（SCI二区期刊）

[20] Xiaoan Yan, Minping Jia*, Ling Xiang. Compound fault diagnosis of rotating machinery based on OVMD and a 1.5-dimension envelope spectrum[J]. Measurement Science and Technology, 2016, 27(7): 075002.（SCI三区期刊）

[21] Xiaoan Yan*, Wan Zhang, Minping Jia. A bearing fault feature extraction method based on optimized singular spectrum decomposition and linear predictor[J]. Measurement Science and Technology 32.11 (2021): 115023.（SCI三区期刊）

[22] Xiaoan Yan*, Ying Liu, Minping Jia. A fault diagnosis approach for rolling bearing integrated SGMD, IMSDE and multiclass relevance vector machine[J]. Sensors, 2020, 20(15): 4352.（SCI三区期刊，入选Editor's Choice Articles）

[23] Xiaoan Yan*, Xing Hua, Dong Jiang, Ling Xiang. A novel robust intelligent fault diagnosis method for rolling bearings based on SPAVMD and WOA-LSSVM under noisy conditions[J]. Measurement Science and Technology, 2024, 35(5): 056121.（SCI三区期刊）

[24] Xiaoan Yan*, Daoming She, Yadong Xu, Minping Jia. Application of generalized composite multiscale Lempel-Ziv complexity in identifying wind turbine gearbox faults[J]. Entropy, 2021, 23(11): 1372.（SCI收录）

[25] Xiaoan Yan*, Ying Liu, Minping Jia, Yinlong Zhu. A multi-stage hybrid fault diagnosis approach for rolling element bearing under various working conditions[J]. IEEE Access, 2019, 7: 138426-138441.（SCI收录）

[26] Xiaoan Yan, Minping Jia*. Improved singular spectrum decomposition based 1.5-dimension energy spectrum for rotating machinery fault diagnosis[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2019, 41(1): 50.（SCI收录）

[27] 鄢小安, 贾民平*. 基于改进奇异谱分解的形态学解调方法及其在滚动轴承故障诊断中的应用[J]. 机械工程学报, 2017, 53(7): 104-112.（EI收录，卓越期刊，入选领跑者5000中国精品期刊顶尖学术论文）

[28] 鄢小安, 贾民平*. 参数优化的组合形态-hat变换及其在风力发电机组故障诊断中的应用[J]. 机械工程学报, 2016, 52(13): 103-110.（EI收录，卓越期刊）

[29] 鄢小安*, 贾民平. 基于参数自适应特征模态分解的滚动轴承故障诊断方法[J]. 仪器仪表学报, 2022, 43(10): 252-259.（EI收录，卓越期刊）

[30] 鄢小安*, 贾民平. 基于层次多尺度散布熵的滚动轴承智能故障诊断[J]. 农业工程学报, 2021, 37(11): 67-75.（EI收录，卓越期刊）

[31] 鄢小安, 贾民平*. 自适应多尺度开闭平均-hat变换及在轴承故障诊断中的应用[J]. 东南大学学报(自然科学版), 2019, 49(05): 826-832.（EI收录）

[32] 鄢小安*, 张知行. 基于LABVIEW的振动数据采集与分析系统设计[J]. 林业机械与木工设备, 2021, 49(10): 18-24.（SCD期刊）

（2）以第一作者（除导师外）或主要参与者发表的学术论文（部分）：

[1] Yadong Xu, Ke Feng, Xiaoan Yan, Ruqiang Yan, Qing Ni, Beibei Sun, Zihao Lei, Yongchao Zhang, Zheng Liu. CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery[J]. Information Fusion, 2023, 95: 1-16.（SCI一区TOP期刊，ESI高被引论文）

[2] Yadong Xu, Ke Feng, Xiaoan Yan, Xin Sheng, Beibei Sun, Zheng Liu, Ruqiang Yan. Cross-modal fusion convolutional neural networks with online soft label training strategy for mechanical fault diagnosis[J]. IEEE Transactions on Industrial Informatics, 2024, 20: 73-84.（SCI一区TOP期刊）

[3] Xianbo Wang, Zhixin Yang, Xiaoan Yan. Novel particle swarm optimization-based variational mode decomposition method for the fault diagnosis of complex rotating machinery[J]. IEEE/ASME Transactions on Mechatronics, 2017, 23(1): 68-79.（SCI一区TOP期刊，ESI高被引论文）

[4] Yadong Xu, Xiaoan Yan, Ke Feng, Yongchao Zhang, Xiaoli Zhao, Beibei Sun, Zheng Liu. Global contextual multiscale fusion networks for machine health state identification under noisy and imbalanced conditions[J]. Reliability Engineering & System Safety, 2023, 231: 108972.（SCI一区TOP期刊）

[5] Yudong Cao, Minping Jia, Xiaoli Zhao, Xiaoan Yan, Zheng Liu. Semi-supervised machinery health assessment framework via temporal broad learning system embedding manifold regularization with unlabeled data[J]. Expert Systems with Applications, 2023, 222: 119824.（SCI一区TOP期刊）

[6] Yadong Xu, Yan Xiaoan, Beibei Sun, Jinhui Zhai, Zheng Liu. Multireceptive field denoising residual convolutional networks for fault diagnosis[J]. IEEE Transactions on Industrial Electronics, 2022, 69: 11686-11696.（SCI一区TOP期刊）

[7] Yadong Xu, Xiaoan Yan, Beibei Sun, Zheng Liu. Hierarchical multiscale dense networks for intelligent fault diagnosis of electromechanical systems[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-12.（SCI二区TOP期刊）

[8] Yadong Xu, Xiaoan Yan, Beibei Sun, Zheng Liu. Deep coupled visual perceptual networks for motor fault diagnosis under nonstationary conditions[J]. IEEE/ASME Transactions on Mechatronics, 2022, 27(6): 4840-4850.（SCI一区TOP期刊）

[9] Yadong Xu, Xiaoan Yan, Beibei Sun, Ke Feng, Yuejian Chen, Yifan Li, Hongtian Chen, Engang Tian, Qing Ni, Yulin Wang. Online Knowledge Distillation Based Multiscale Threshold Denoising Networks for Fault Diagnosis of Transmission Systems[J]. IEEE Transactions on Transportation Electrification, 2023.（SCI一区TOP期刊）

[10] Yadong Xu, Xiaoan Yan, Ke Feng, Xin Sheng, Beibei Sun, Zheng Liu. Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery[J]. Reliability Engineering & System Safety, 2022, 226: 108714.（SCI一区TOP期刊）

[11] Yadong Xu, Xiaoan Yan, Beibei Sun, Zheng Liu. Dually attentive multiscale networks for health state recognition of rotating machinery[J]. Reliability Engineering & System Safety, 2022: 108626.（SCI一区TOP）

[12] Wan Zhang, Xiaoan Yan, Minping Jia. Sparse enhancement based on the total variational denoising for fault feature extraction of rolling element bearings[J]. Measurement, 2022, 195: 111163.（SCI二区TOP期刊）

[13] Daoming She, Jin Chen, Xiaoan Yan, Hu Wang, Hongfei Zhang, Michael Pecht. Deep multi feature dynamic adversarial diagnosis approach of rotating machinery[J]. Measurement Science and Technology, 2022, 33(12): 125023.（SCI三区期刊）

[14] Peng Ding, Minping Jia, Xiaoan Yan. Stationary subspaces-vector autoregressive with exogenous terms methodology for degradation trend estimation of rolling and slewing bearings[J]. Mechanical Systems and Signal Processing, 2021, 150: 107293.（SCI一区TOP期刊）

[15] Yifei Ding, Minping Jia, Yudong Cao, Xiaoan Yan, Xiaoli Zhao, Chi-Guhn Lee. Unsupervised fault detection with deep one-class classification and manifold distribution alignment[J]. IEEE Transactions on Industrial Informatics, 2024, 20: 1313-1323.（SCI一区TOP期刊）

[16] Yudong Cao, Minping Jia, Xiaoli Zhao, Xiaoan Yan, Ke Feng. Complex augmented representation network for transferable health prognosis of rolling bearing considering dynamic covariate shift[J]. Reliability Engineering & System Safety, 2024, 241: 109692.（SCI一区TOP期刊）

[17] Yongjie Mao, Minping Jia, Xiaoan Yan. A new bearing weak fault diagnosis method based on improved singular spectrum decomposition and frequency-weighted energy slice bispectrum[J]. Measurement, 2020, 166: 108235.（SCI二区TOP期刊）

[18] Ling Xiang*, Xiaoan Yan. A self-adaptive time-frequency analysis method based on local mean decomposition and its application in defect diagnosis[J]. Journal of Vibration and Control, 2016, 22(4): 1049-1061.（SCI三区期刊）

[19] Aijun Hu, Xiaoan Yan, Ling Xiang*. A new wind turbine fault diagnosis method based on ensemble intrinsic time-scale decomposition and WPT-fractal dimension[J]. Renewable Energy, 2015, 83: 767-778.（SCI一区TOP期刊）

[20] Daoming She, Jin Chen, Xiaoan Yan, Xiaoli Zhao, Michael Pecht. Diversity maximization based transfer diagnosis approach of rotating machinery[J]. Structural Health Monitoring, 2024, 23: 410-420.（SCI二区TOP）

[21] Duanwu Yang, Jinyong Wang, Xiaoan Yan, Liu Hongbin. Subway Air Quality Modeling Using Improved Deep Learning Framework[J]. Process Safety and Environmental Protection, 2022.（SCI二区期刊）

[22] Wan Zhang, Minping Jia, Lin Zhu, Xiaoan Yan. Comprehensive overview on computational intelligence techniques for machinery condition monitoring and fault diagnosis[J]. Chinese Journal of Mechanical Engineering, 2017, 30(4): 782-795.（SCI二区期刊，卓越期刊，综述论文）

[23] 向玲*, 鄢小安. 汽轮机转子故障诊断中LMD法和EMD法的性能对比研究[J]. 动力工程学报, 2014, 34(12): 945-951.（一级学报，入选领跑者5000（F5000）中国精品期刊顶尖学术论文）

[24] 向玲*, 鄢小安. 基于小波包的EITD风力发电机组齿轮箱故障诊断[J]. 动力工程学报, 2015, 35(03): 205-212.（一级学报）

[25] 向玲*, 鄢小安. 基于集成固有时间尺度分解和谱峭度的电机轴承故障检测[J]. 中南大学学报(自然科学版), 2016, 47(07): 2273-2280.（EI收录）

申报专利情况：

[1] 鄢小安*; 叶茂友; 姜东; 陈宁; 刘英; 谢超. 一种基于强鲁棒性多尺度网络的机械故障诊断方法和系统, 2024-01-30, 中国, 202310063113.5.（发明授权）

[2] 鄢小安*; 姜东; 谢超; 刘英. 基于参数自适应特征模态分解故障诊断方法和系统, 2023-04-07, 中国, 202210571899.7.（发明授权）

[3] 鄢小安*; 谢超; 刘英; 姜东. 基于多尺度残差卷积变分网络故障诊断方法和诊断系统, 2023-04-07, 中国, 202210317326.1.（发明授权）

[4] 鄢小安*; 姜东; 刘英. 基于深度小波核变分自编码器的机械故障诊断方法和系统, 2022-05-26, 中国, 202210589411.3.（发明受理）

[5] 鄢小安*; 叶茂友; 姜东; 刘英; 陈宁. 基于多信息融合深度集成网络的故障诊断方法和系统[P]. 2023-09-13, 中国, 202311178807.X.（发明受理）

[6] 鄢小安*; 叶茂友; 谢超; 卢彦宇; 姜东. 基于增强型卷积神经网络的机械故障诊断方法和诊断系统, 2022-05-24, 中国, 202210567779.X.（发明受理）

[7] 鄢小安*; 卢彦宇; 谢超; 叶茂友. 基于深度残差变分自编码器的故障诊断方法和诊断系统, 2022-04-07, 中国, 202210359430.7.（发明受理）

[8] 贾民平, 鄢小安, 许飞云, 胡建中, 黄鹏, 朱林, 张菀. 一种基于奇异谱分解的旋转机械故障诊断方法, 2019-03-19, 中国, 201610730284.9.（发明授权）

[9] 谢超; 朱泓宇; 鄢小安; 费叶琦; 刘英. 基于深度坐标注意力网络模型的图像超分辨率重建方法[P]. 2022-01-25, 中国, 202110399796.2.（发明授权）

[10] 谢超; 朱泓宇; 鄢小安; 汤浩; 刘英. 基于选择性通道处理机制的轻量级遥感图像超分辨率方法[P]. 2023-04-07, 中国, 202210784242.9.（发明授权）

[11] 贾民平*, 佘道明, 许飞云, 胡建中, 黄鹏, 鄢小安.  一种深度自编码网络的旋转机械健康评估方法[P]. 2020-03-31, 中国, CN201810736521.1.（发明授权）

[12] 贾民平*, 赵孝礼, 胡建中, 许飞云, 黄鹏, 佘道明, 鄢小安. 一种无监督深度学习网络的机械故障诊断方法[P]. 2020-03-31, 中国, CN201810949099.8.（发明授权）

[13] 马晨波; 陆志杰; 孙见君; 鄢小安; 张玉言; 韩权; 王志良; 刘德利. 一种滚动轴承早期微弱故障诊断方法[P]. 2023-09-06, 中国, 202311147203.9.（发明受理）

[14] 费叶琦, 鄢小安, 谢超, 陈天熙, 张豪, 赵朋飞. 齿轮品质检测装置[P]. 2022-11-22, 中国, 202221609162.1（实用新型授权）

[15] 向玲; 崔伟; 胡爱军; 鄢小安; 陈涛; 李淑东. 一种风力发电机组传动系统故障预警的方法, 2016-09-07, 中国, 201310414203.0.（发明授权）

[16] 向玲; 陈涛; 胡爱军; 鄢小安; 贾轶. 一种架空输电线路振动监测系统及监测方法[P]. 2015-04-01, 中国, 201410662722.3.（发明授权）

向玲; 胡思磊; 陈涛; 鄢小安. 一种输电线路巡线机器人[P]. 2014-11-12, 中国, 201420364744.7, （实用新型授权）

主要讲授测试技术、数控技术、机电一体化系统设计等专业核心课程

1）IOP Outstanding Reviewer Awards（杰出审稿人奖），2023年

2）江苏省仪器仪表学会“优秀科技工作者”，2023年

3）澳门青年学者（2021年全国仅25人入选），2021年

4）江苏省双创人才计划（科技副总类），2021年

5）江苏省“双创博士”人才计划（世界名校类），2020年

6）江苏省优秀博士学位论文，2020年

7）指导学生获得“江苏省大学生机器人大赛”一等奖，2020年

8）指导学生获得“江苏省大学生机器人大赛”三等奖，2019年

9）东南大学优秀毕业研究生，2018年

10）江苏省省级“三好研究生”称号，2017年

11）河北省优秀硕士学位论文，2015年

12）校级优秀毕业生，2012年

河北省“数学竞赛”一等奖，2012年