教师姓名：王志坚
教师资料：男，博士/博士后，教授，博士生导师
研究方向：复杂设备可靠性建模与数字孪生技术，机械装备剩余寿命预测与健康管理、数据驱动的智能诊断、机械信号处理与分析
学科领域：机械工程
个人简介：1985年出生，河南郑州人。2015年6月毕业于太原理工大学，获工学博士学位，2017年聘为副教授，2019年特殊破格聘为教授，2022年西安交通大学现代设计及转子轴承系统教育部重点实验室博士后出站。山西省委联系的服务专家，山西省科技创新重点人才团队负责人，九三学社中北大学委员会副主委，中北大学学报（自然科学版）副主编，Journal of Dynamics, Monitoring and Diagnostics（JDMD）青年编委，轴承期刊青年编委，中北大学机械工程学科带头人，入选美国斯坦福大学发布的全球前2%顶尖科学家榜单。国家自然基金委通讯评审专家，中国振动工程学会动态信号分析专业委员会常务理事，中国振动工程学会故障诊断专业委员会理事，中国振动工程学会转子动力学专业委员会理事，中国现场统计研究会可靠性工程分会理事，《IEEE Transactions on Industrial Informatics》《IEEE Transactions on Industrial Electronics》《Mechanical systems and signal processing》《ISA Transactions》《Structural Health Monitoring》《Measurement》 《IEEE Transactions on Instrumentation and Measurement》《Journal of Vibration and Control》《Journal of sound and vibration》 等SCI期刊的审稿专家，《振动与冲击》《电机与控制学报》《农业工程学报》《振动、测试与诊断》等EI期刊的审稿专家。
联系方式：wangzhijian1013@163.com
主要论著教学科研
（1）简述
主持国家自然基金面上项目、国家自然基金青年项目、山西省科技创新重点人才团队、中央引导地方专项、山西省重点研发项目、山西省专利推广转化项目、山西省应用基础研究项目、山西省高校科技创新项目、企业横向项目等15余项，荣获山西省自然科学二等奖（排名第一），获得2020年“粤港澳大湾区高性能计算”全国博士后学术论坛二等奖。发表学术论文70余篇， SCI收录50余篇、ESI高被引论文11篇、热点论文2篇，以第一作者发表EI收录论文7篇。第一发明人申请国家发明专利20余项，授权10项，出版专著1部。
（2）部分SCI成果
1.Li, Yajing,Zhijian Wang*, Feng Li, Yanfeng Li, Xiaohong Zhang, Hui Shi, Lei Dong, and Weibo Ren. "An Ensembled Remaining Useful Life Prediction Method with Data Fusion and Stage Division." Reliability Engineering & System Safety 242 (2024). https://doi.org/10.1016/j.ress.2023.109804. SCI 1区, TOP
2.L. Yang,Wang Z*, Y. Li, L. Dong, W. Du, J. Wang, X. Zhang, H. Shi, Two-stage prediction technique for rolling bearings based on adaptive prediction model, Mechanical Systems and Signal Processing 206 (2024). https://doi.org/10.1016 /j.ymssp.2023.110931。SCI 1区, TOP
3.Zhijian Wang, Yuntian Ta, Yanfeng Li, Research on a remaining useful life prediction method for degradation angle identification two-stage degradation process, Mechanical Systems and Signal Processing, 184,2023. DOI:10.1016 /j.ymssp. 2022.109747 0888-3270.SCI 1区, TOP
4.Yang N,Wang Z*, Cai W, et al. Data Regeneration Based on Multiple Degradation Processes for Remaining Useful Life Estimation. Reliability Engineering & System Safety, 2022: 108867. doi:10.1016/j.ress.2022.108867. SCI 1区, TOP
5. Yuntian Ta, Wang Z* Yanfeng Li, Adaptive staged remaining useful life prediction method based on multi-sensor andmulti-feature fusion. Reliability Engineering & System Safety. DOI:10.1016/j.ress.2022.109033 SCI 1区, TOP
6.Zhijian Wang, Xinxin He, Bin Yang, Naipeng Li. Subdomain adaptation transfer learning network for fault diagnosis of roller bearings. IEEE Transactions on Industrial Electronics, 2021, DOI: 10.1109/TIE.2021.3108726. SCI 1区, TOP
7.Xinxin He,Zhijian Wang*, Yanfeng Li, Svetlana Khazhina, Wenhua Du, Junyuan Wang. Joint decision-making of parallel machine scheduling restricted in job-machine release time and preventive maintenance with remaining useful life constraints. Reliability Engineering & System Safety, 2022, DOI: 10.1016/j.ress.2022.108429. SCI 1区, TOP
8.Wang Z, Zhou J, Lei Y, Du W. Bearing fault diagnosis method based on adaptive maximum cyclostationarity blind deconvolution. Mechanical systems and signal processing, 2022, 162: 108018，SCI 1区, TOP
9.Wang Z, Yang N, Li N. A new fault diagnosis method based on adaptive spectrum mode extraction. Structural Health Monitoring, 2021, 20: 3354- 3370，SCI 2区, ESI高被引
10.Wang, Zhijian, Yajing Li, Lei Dong, Yanfeng Li, and Wenhua Du. A Rul Prediction of Bearing Using Fusion Network through Feature Cross Weighting. Measurement Science and Technology 34, (2023).https://doi.org/10.1088/ 1361-6501/acdf0d.
11.Zhijian Wang, Wenyan Zhao, Yanfeng Li, Lei Dong, Junyuan Wang, Wenhua Du, Xingxing Jiang.Adaptive staged RUL prediction of rolling bearing.Measurement,2023,113478,DOI:https://doi.org/10.1016/j.measurement.2023.113478. TOP
12.Wang Z, Zhao W, Du W, Li N, Wang J. Data-riven fault diagnosis method based on EOSTI and Convolutional Neural Network. Process Safety and Environmental Protection, 2021, 149: 591-601. SCI 2区. ESI高被引
13.Zhijian Wang, Jie Cui, Wenan Cai,and Yanfeng Li.Partial Transfer Learning of Multi-discriminator Deep Weighted Adversarial Network in Cross-machine Fault Diagnosis.IEEE Transactions on Instrumentation and Measurement. 2022, SCI 2区
14.Wenlei Zhao,Zhijian Wang*, Wenan Cai, Qianqian Zhang, Junyuan Wang. Multiscale inverted residual convolutional neural network for intelligent diagnosis of bearings under variable load condition, Measurement, 2022, 188: 110511. SCI 2区，ESI高被引，TOP
15.Zhijian Wang*, Yuanmeng Wu, Qianqian Zhang, Yanfeng Li. A Multi Branch Residual Network for Fault Diagnosis of Bearings. Transactions of the Canadian Society for Mechanical Engineering, 2021, DOI: 10.1139/tcsme-2021-0107.
16.Zhijian Wang，Wenhua Du，Junyuan Wang. Research and Application of Improved Adaptive MOMEDA Fault Diagnosis Method, Measurement, 2019, 140, 63-75. SCI2区, ESI高被引,热点
17. Zhijian Wang, Zhennan Han, Fengshou Gu. A novel procedure for diagnosing multiple faults in rotatin machinery. ISA transactions, 2016, SCI2区, TOP
18.Wang Z, Wang C, Li N. Bearing fault diagnosis method based on similarity measure and ensemble learning[J]. Measurement Science and Technology, 2021, 32: 055005. SCI 2区
19.Li N, Lei Y, Gebraeel N,Wang Z. Multi-Sensor Data-Driven Remaining Useful Life Prediction of Semi-Observable Systems. IEEE Transactions on Industrial Electronics, 2020, doi:10.1109/TIE.2020.3038069. SCI 1区, TOP
20.Zhijian Wang, Wang Junyuan, Zhou Jie. Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault diagnosis, Complexity. 2019, doi: 10.1155/2019/1564243. SCI2区, ESI高被引
21.Zhijian Wang, Likang Zheng, Du Wenhua, A novel method for intelligent fault diagnosis of bearing based on capsule neural network. Complexity.2019, SCI2区, ESI高被引
22.Z. Wang, G. He, W. Du, J. Zhou, X. Han, J. Wang, H. He, Xi. Guo, J. Wang, and Y. Kou, Application of Parameter Optimized Variational Mode Decomposition Method in Fault Diagnosis of Gearbox, IEEE Access.2019. SCI2区, ESI高被引
23. Wang Zhijian, Zhou Jie, Wang Junyuan, Wenhua Du. A novel Fault Diagnosis Method of Gearbox Based on Maximum Kurtosis Spectral Entropy Deconvolution. IEEE Access. 2019. SCI2区, ESI高被引
24.Wang, Z.J , Wang, J.Y. Weak Fault Diagnosis of Wind Turbine Gearboxes Based on MED-LMD. Entropy 2017，SCI3区
25.ZHIJIAN WANG, HUIHUI HE, JUNYUAN WANG. Application Research of a Novel Enhanced SSD Method in Composite Fault Diagnosis of Wind Power Gearbox. Sensors, 2018.SCI3区
（3）获奖和主要在研项目
1.山西省自然科学二等奖：旋转机械的自适应降噪机理及智能诊断（排名第一）
2.国家自然科学面上基金：数字孪生驱动的空间谐波齿轮在线剩余寿命预测方法研究52275139.（主持）
3. 国家自然科学青年基金：空间齿轮微动载荷谱自适应提取及疲劳寿命预测方法研究51905496（主持）
4.山西省科技创新重点人才团队：复杂装备智能运维（主持）
5. 山西省重点研发计划：基于大数据分析的高速公路风险评估与协同管控技术研究（202102020101015）（主持）
6. 中央引导地方专项：数字孪生驱动的传动部件剩余寿命预测研究（YDZJSX2022A029）（主持）
7.山西省专利推广转化成果项目：风电齿轮箱在线剩余寿命预测关键技术及应用202201051（主持）
8. 山西省应用基础研究项目：基于MOMEDA的强噪声环境下复合故障自适应提取新方法研究201801D221237，2018/12-2020/12.（主持）
9. 山西省高校科技创新项目：航天器在轨微振动载荷谱自适应提取方法研究（主持）
10.太原矿山机器集团装备有限公司：井下采煤机行星减速器关键零部件健康状态实时监测与故障预警研究（主持）
11. 中北大学校基金：基于微动损伤模型的空间疲劳寿命预测与延寿新方法研究(NO. XJJ201802)（主持）
12.大秦铁路股份有限公司：大型养路机械智能诊断系统开发.（主持）
13.太原理工大学：新型矿用钢丝绳芯输送带无损检测系统开发.（主持）
