教育经历

2013-09至2018-06，华东理工大学，控制科学与工程，博士

2009-09至2013-07，华东理工大学，自动化，学士

科研与学术工作经历

2020-07至今，太原科技大学，yl23455永利官网，教师

2018-07至2020-06，北京科技大学，自动化学院，博士后

研究方向

故障检测、故障诊断、工况监控、健康管理、智慧农机

代表性研究成果

[1]樊超，王帆。可解释的小波卷积神经网络机械故障诊断方法[J]. 振动工程学报，2024.

[2]Huang Jian, Wang Fan, Qiao Liang, Yang Xu. T-distributed stochastic neighbor embedding echo state network with state matrix dimensionality reduction for time series prediction[J]. Engineering Applications of Artificial Intelligence, 2023, 122, 106055.

[3]Huang Jian, Wang Fan, Yang Xu, Li Qing. Semi-supervised echo state network with partial correlation pruning for time-series variables prediction in industrial processes[J]. Measurement Science and Technology, 2023, 34, 095106.

[4]Wang Fan. Linear chain conditional random field for operating mode identification and multimode process monitoring[J]. ACS Omega, 2022, 7, 29483-29494.

[5]Zhang Kai, Peng Kaixiang, Zhao Shanshan, Wang Fan. A Novel Feature-Extraction-Based Process Monitoring Method for Multimode Processes With Common Features and Its Applications to a Rolling Process[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17(9), 6466-6475.

[6]Wang Fan, Zhang Sen, Yin Yixin. A new nonlinear process monitoring method based on linear and nonlinear partition[J]. Industrial & Engineering Chemistry Research, 2019, 58(37), 17445-17454.

[7]Rong Mengyu, Shi Hongbo, Wang Fan, Tan Shuai. Distributed process monitoring framework based on decomposed modified partial least squares[J]. Canadian Journal of Chemical Engineering, 2019, 97(12), 3087-3100.

[8]Fan Wang, Sen Zhang, Yixin Yin. Log likelihood monitoring for multimode process using variational Bayesian mixture factor analysis model[J]. IEEE Access, 2019, 7, 89083-89092.

[9] Fan Wang, Shuai Tan, Yawei Yang, Hongbo Shi. Hidden Markov model-based fault detection approach for a multimode process[J]. Industrial & Engineering Chemistry Research, 2016, 55(16), 4613-4621.

[10]Fan Wang, Honglin Zhu, Shuai Tan, Hongbo Shi. Orthogonal nonnegative matrix factorization based local hidden Markov model for multimode process monitoring[J]. Chinese Journal of Chemical Engineering, 2016, 24(7), 856-860.

[11]Fan Wang, Shuai Tan, Hongbo Shi. Hidden Markov model-based approach for multimode process monitoring[J]. Chemometrics and Intelligent Laboratory Systems, 2015, 148, 51-59.

[12]王帆，杨雅伟，谭帅，侍洪波. 基于稀疏性非负矩阵分解的故障监测方法[J]. 化工学报，2015，66（5），1798-1805.