职 称 : 讲师（高校）
学 科 :
单 位 : 电气工程学院
[1]. 西安交通大学 | 机械工程学院 机械工程 | 博士研究生 | 博士学位 导师：雷亚国 教授
[2]. 西安交通大学 | 能源与动力工程学院 动力工程 | 硕士研究生 | 硕士学位 导师：林梅 研究员
[1]. 中国能源建设集团山西省电力设计院 | 电厂设计
[1]. 担任MSSP、IEEE TII、IEEE TIE、TIM、ISA transactions、IEEE sensors journal、EAAI、MST、Frontiers in Nuclear Engineering等20余个学术权威期刊审稿人
[2]. 中国振动工程学会会员
[3]. 河北振动工程学会会员
共发表学术论文48篇，以第一作者/通讯作者发表SCI/EI共25篇，其中ESI高被引论文2篇、中科院一区或TOP论文14篇、卓越科技期刊论文1篇（并入选封面文章），授权国家发明专利4项，主持在研国家、省自然科学基金青年基金项目、全国重点实验室开放基金、教育部重点实验室开放基金2项、燕山大学基础创新科研培育项目、军工类和企事业委托横向等项目。
[1] Xuefang Xu, Xu Yang, Zijian Qiao, Pengfei Liang, Changbo He, Peiming Shi. Multi-source domain adaptation using diffusion denoising for bearing fault diagnosis under variable working conditions. Knowledge-Based Systems. 2024, 302:112396. (SCI影响因子:7.2 , 中科院1区TOP期刊)
[2] Peiming Shi, Shengmao Lin, Dongran Song, Xuefang Xu*, Jie Wu. TRNet: A trend and residual network utilizing novel hilly attention 1 mechanism for wind speed prediction in complex scenario.Energy, 2024: 130404. (SCI影响因子:9.0, 中科院1区TOP期刊)
[3] Xuefang Xu, Xu Yang, Changbo He, Peiming Shi, Changchun Hua. Adversarial Domain Adaptation Model Based on LDTW for Extreme Partial Transfer Fault Diagnosis of Rotating Machines.IEEE Transactions on Instrumentation and Measurement.2024.(中科院 2 区 TOP 期刊，IF:5.6)
[4] Xuefang Xu, Shuo Bao, Haidong Shao, et al. A multi-sensor fused incremental broad learning with D-Sheory for online fault diagnosis of rotating machinery. Advanced Engineering Informatics. 2024.(中科院 1 区 TOP 期刊，IF:8.8);
[5] Shiting Hu, Xuefang Xu*, Mengdi Li, et al. Incremental forecaster using C–C algorithm to phase space reconstruction and broad learning network for short-term wind speed prediction[J]. Engineering Applications of Artificial Intelligence, 2024, 128: 107461.(中科院2 区 TOP 期刊，所指导学生为第一作者)
[6] Bo Li, Xuefang Xu*, Hang Tan, Peiming Shi, Zijian Qiao. Cyclogram: an effective method for selecting frequency bands for fault diagnosis of rolling element bearings[J]. Measurement Science and Technology, 2023, 34(9): 094003. (SCI 影响因子: 2.4，中科院3区期刊，所指导学生为第一作者);
[7] Shengmao Lin, Shu Wang, Xuefang Xu*, Ruixiong Li, Peiming Shi. GAOformer: An adaptive spatiotemporal feature fusion transformer utilizing GAT and optimizable graph matrixes for offshore wind speed prediction[J]. Energy, 2024: 130404. (SCI影响因子:9.0, 中科院1区TOP期刊，所指导学生为第一作者)
[8]Xuefang Xu, Shuo Bao, Pengfei Liang, et al. A broad learning model guided by global and local receptive causal features for online incremental machinery fault diagnosis. Expert Systems with Applications.2024. (中科院 1 区 TOP 期刊，IF:8.5);
[9] Xuefang Xu, Bo Li, Zijian Qiao, et al. Caputo-Fabrizio fractional order derivative stochastic resonance enhanced by ADOF and its application in fault diagnosis of wind turbine drivetrain. Renewable Energy.2023.119398. (中科院 1 区 TOP 期刊，IF:8.7);
[10] Xuefang Xu, Bo Li, Wenyue Zhang, et al. Caputo–Fabrizio fractional stochastic resonance with graphene potential enhanced by NLOF and its applications in fault diagnosis of rotating machinery[J]. Nonlinear Dynamics, 2023: 1-27. (中科院 2 区 TOP 期刊，IF:5.6);
[11] Xuefang Xu, Shiting Hu, Peiming Shi, Huaishuang Shao, Ruixiong Li, Zhi Li. Natural phase space reconstruction-based broad learning system for short-term wind speed prediction: Case studies of an offshore wind farm[J]. Energy, 2023, 262: 125342. (SCI 影响因子: 8.857, 中科院 1 区 TOP 期刊)
[12] Xuefang Xu, Shiting Hu, Huaishuang Shao, Peiming Shi, Ruixiong Li, Deguang Li. A spatio-temporal forecasting model using optimally weighted graph convolutional network and gated recurrent unit for wind speed of different sites distributed in an offshore wind farm[J]. Energy, 2023, 284: 128565. (SCI 影响因子: 8.857, 中科院 1 区 TOP 期刊、ESI高被引论文)
[13] Xuefang Xu, Yaguo Lei, Zeda Li. An incorrect data detection method for big data cleaning of machinery condition monitoring[J]. IEEE Transactions on Industrial Electronics, 2020, 67(3): 2326-2336. (SCI 影响因子: 8.162, ESI高被引, 中科院 1 区 TOP 期刊、ESI高被引论文)
[14] Xuefang Xu, Zijian Qiao, Yaguo Lei. Repetitive transient extraction for machinery fault diagnosis using multiscale fractional order entropy infogram[J]. Mechanical Systems and Signal Processing, 2018, 103: 312-326. (SCI 影响因子: 8.934, 中科院 1 区 TOP 期刊)
[15] Xuefang Xu, et al. Intelligent Fault Diagnosis for variable working conditions based on the SAAFN and the BICP [J]. IEEE Sensors Journal, 2024.(SCI 影响因子: 4.3 中科院 2 区)
[16] 雷亚国, 许学方, 蔡潇, 李乃鹏, 孔德同, 张勇铭. 面向机械装备健康监测的数据质量保障方法研究[J]. 机械工程学报, 2021, 57(4): 1-9. （中国科技期刊卓越行动计划入选期刊, 中国机械工程学会会刊, 被选为期刊封面文章）
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