A Lightweight Fault Diagnosis Method of Beam Pumping Units Based on Dynamic Warping Matching and Parallel Deep Network

Author:

Liu Shuo1ORCID,Song Chunhe1ORCID,Wu Tingting1,Zeng Peng1ORCID

Affiliation:

1. Key Laboratory of Networked Control Systems, the State Key Laboratory of Robotics, and the Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

Funder

National Natural Science Foundation of China

State Key Laboratory of Robotics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering,Software

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. A lightweight convolutional neural network for working condition intelligent diagnosis of pumping units;Engineering Research Express;2024-06-01

2. Challenges of Data Consistency in High-Concurrency Environments: Algorithms and Implementation for the Electric Power Industrial Internet Platform;2024 5th International Conference on Information Science, Parallel and Distributed Systems (ISPDS);2024-05-31

3. Advances and Challenges in Large Model Compression: A Survey;Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence;2024-01-19

4. Few-shot bearing fault detection based on multi-dimensional convolution and attention mechanism;Mathematical Biosciences and Engineering;2024

5. Fault Diagnosis Algorithm for Pumping Unit Based on Dual-Branch Time–Frequency Fusion;IEEE Transactions on Reliability;2024

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