Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network-Reference-Cited by-同舟云学术

Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

Published:2023-04 Issue:2 Volume:20 Page:1142-1154
ISSN:1995-8226
Container-title:Petroleum Science
language:en
Short-container-title:Petroleum Science

Author:

He Yun-Peng,Zang Chuan-Zhi,Zeng Peng,Wang Ming-Xin,Dong Qing-Wei,Wan Guang-Xi,Dong Xiao-Ting

Funder

National Natural Science Foundation of China

State Key Laboratory of Robotics

Publisher

Elsevier BV

Subject

Economic Geology,Geochemistry and Petrology,Geology,Geophysics,Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference49 articles.

1. Critical infrastructure protection based on memory-augmented meta-learning framework;Bing;Neural Comput. Appl.,2020

2. Survey of monocular camera-based visual relocalization;Chen;Robot,2021

3. Automatic recognition of sucker-rod pumping system working conditions using dynamometer cards with transfer learning and svm;Cheng;Sensors-Basel,2020

4. An algorithm for the machine calculation of complex fourier series;Cooley;Math. Comput.,1965

5. Crack Detection for Aerospace Quality Spur Gears. Crack Detection for Aerospace Quality Spur Gears;Decker,2002

Cited by 6 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. Intelligent diagnosis method of torque-angle dynamometer cards for beam pumping units based on transfer learning;Geoenergy Science and Engineering;2024-10

2. Few-shot learning fault diagnosis of rolling bearings based on siamese network;Measurement Science and Technology;2024-06-27

3. A Hybrid Method for Solving the One-Dimensional Wave Equation of Tapered Sucker-Rod Strings;Axioms;2024-06-20

4. Multisource working condition recognition via nonlinear kernel learning and p-Laplacian manifold learning;Heliyon;2024-03

5. Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16