Fault diagnosis strategy for few shot industrial process based on data augmentation and depth information extraction-Reference-Cited by-同舟云学术

Fault diagnosis strategy for few shot industrial process based on data augmentation and depth information extraction

Published:2023-01-26 Issue: Volume: Page:
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can J Chem Eng

Author:

Tian Ying¹^ORCID,Xiang Xin¹,Peng Xin²,Yin Zhong¹,Zhang Wei¹

Affiliation:

1. Department of Control Science and Engineering, School of Optical‐Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

2. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education East China University of Science and Technology Shanghai China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemical Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjce.24818

Reference37 articles.

1. Distinct Bearing Faults Detection in Induction Motor by a Hybrid Optimized SWPT and aiNet-DAG SVM

2. Evidential KNN-based condition monitoring and early warning method with applications in power plant

3. Fault Diagnosis of Complex Chemical Processes Based on Enhanced Naive Bayesian Method

Cited by 3 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. Review of imbalanced fault diagnosis technology based on generative adversarial networks;Journal of Computational Design and Engineering;2024-08-31

2. Few-shot learning based on hierarchical feature fusion via relation networks;International Journal of Approximate Reasoning;2024-07

3. Computer Aided Industrial Design Technology for Integrating Feature Point Coordinate Calculation in Toy Design;Journal of The Institution of Engineers (India): Series C;2024-05-27