Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

Author:

He Yun-Peng,Cheng Hai-Bo,Zeng Peng,Zang Chuan-Zhi,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

Reference44 articles.

1. Identification of downhole conditions in sucker rod pumped wells using deep neural networks and genetic algorithms;Abdalla;SPE Prod. Oper.,2020

2. Using the motor power and XGBoost to diagnose working states of a sucker rod pump;Chen;J. Petrol. Sci. Eng.,2021

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

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

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

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