| Slow down to go better: A survey on slow feature analysis P Song, C Zhao IEEE Transactions on Neural Networks and Learning Systems, 2022 | 71 | 2022 |
| SFNet: A slow feature extraction network for parallel linear and nonlinear dynamic process monitoring P Song, C Zhao, B Huang Neurocomputing 488, 359-380, 2022 | 23 | 2022 |
| MPGE and RootRank: A sufficient root cause characterization and quantification framework for industrial process faults P Song, C Zhao, B Huang Neural Networks 161, 397-417, 2023 | 14 | 2023 |
| Explicit representation and customized fault isolation framework for learning temporal and spatial dependencies in industrial processes P Song, C Zhao, B Huang, J Ding IEEE Transactions on Neural Networks and Learning Systems, 2023 | 9 | 2023 |
| Sparse and time-varying predictive relation extraction for root cause quantification of nonstationary process faults P Song, C Zhao, B Huang, M Wu IEEE Transactions on Instrumentation and Measurement 71, 1-13, 2022 | 6 | 2022 |
| Sparse adjacency forecasting and its application to efficient root cause diagnosis of process faults P Song, C Zhao IFAC-PapersOnLine 54 (3), 439-444, 2021 | 4 | 2021 |
| Section division and multi-model method for early detection of icing on wind turbine blades P Song, Z Yao, C Zhao 2019 34rd Youth Academic Annual Conference of Chinese Association of …, 2019 | 4 | 2019 |
| Dynamic causal modeling for nonstationary industrial process performance degradation analysis and fault prognosis S Duan, K Zhu, P Song, C Zhao Journal of Process Control 129, 103050, 2023 | 2 | 2023 |
| Structure feature extraction for hierarchical alarm flood classification and alarm prediction C Tian, P Song, C Zhao, J Ding IEEE Transactions on Automation Science and Engineering, 2023 | 2 | 2023 |
| Federated knowledge amalgamation with unbiased semantic attributes under cloud–edge collaboration for heterogeneous fault diagnosis J Wang, P Song, C Zhao, J Ding Journal of Process Control 131, 103095, 2023 | 1 | 2023 |
| Finding trustworthy neighbors: Graph aided federated learning for few-shot industrial fault diagnosis with data heterogeneity Z Yao, P Song, C Zhao Journal of Process Control 129, 103038, 2023 | 1 | 2023 |
| Multimodal Decoupled Representation With Compatibility Learning for Explicit Nonstationary Process Monitoring P Song, C Zhao, J Ding, S Zhao IEEE Transactions on Industrial Electronics, 2023 | 1 | 2023 |
| Spatiotemporal Multiscale Correlation Embedding With Process Variable Reorder for Industrial Soft Sensing J Chen, P Song, C Zhao, J Ding IEEE Transactions on Instrumentation and Measurement, 2023 | 1 | 2023 |
| Parallel Temporal and Spatial Modeling for Interpretable Fault Detection and Isolation of Industrial Processes P Song, C Zhao, J Ding, Y Sun, X Jin 2021 8th International Conference on Information, Cybernetics, and …, 2021 | 1 | 2021 |
| Fuzzy State-Driven Cross-Time Spatial Dependence Learning for Multivariate Time-Series Anomaly Detection K Zhu, P Song, C Zhao IEEE Transactions on Neural Networks and Learning Systems, 2024 | | 2024 |
| Fusing consensus knowledge: A federated learning method for fault diagnosis via privacy-preserving reference under domain shift B Li, P Song, C Zhao Information Fusion, 102290, 2024 | | 2024 |
| Facing spatiotemporal heterogeneity: A unified federated continual learning framework with self-challenge rehearsal for industrial monitoring tasks B Li, P Song, C Zhao, M Xie Knowledge-Based Systems, 111491, 2024 | | 2024 |
| Multi-scale self-supervised representation learning with temporal alignment for multi-rate time series modeling J Chen, P Song, C Zhao Pattern Recognition 145, 109943, 2024 | | 2024 |
| Multi-Conditional Adjacency Learning and Grouping Method for Monitoring Gas Turbine Generation Process with Nonstationarity S Zhang, P Song, C Zhao 2023 China Automation Congress (CAC), 1406-1411, 2023 | | 2023 |
| 面向少样本故障诊断的知识自监督深度表征学习方法 姚家琪， 宋鹏宇， 沈萌， 赵春晖， 王文海 控制与决策, 2023 | | 2023 |
Chunhui ZhaoZhejiang UniversityПотвърден имейл адрес: zju.edu.cn
