A Flexible Probabilistic Framework With Concurrent Analysis of Continuous and Categorical Data for Industrial Fault Detection and Diagnosis

Author:

Chen Junhao1ORCID,Zhao Chunhui1ORCID,Ding Jinliang2ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China

2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cross-Domain Bilateral Transfer Learning for Fault Diagnosis Under Incomplete Multisource Domains;IEEE Transactions on Automation Science and Engineering;2024

2. Continual learning classification method with human-in-the-loop based on the artificial immune system;Engineering Applications of Artificial Intelligence;2023-11

3. Intermittent fault detection based on feature ensemble;2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS);2023-09-22

4. Deep Wavelet Neural Process: Modeling Stochastic Variation of Non-Euclidean Functional Data for Manufacturing Quality Inference;IEEE Transactions on Industrial Informatics;2023

5. Fault Diagnosis and Cause Analysis Using Dynamic Adaptive Fuzzy Petri Nets;Fuzzy Petri Nets for Knowledge Representation, Acquisition and Reasoning;2023

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