Fault diagnosis of sucker rod pumping systems based on Curvelet Transform and sparse multi-graph regularized extreme learning machine
A novel approach is proposed to complete the fault diagnosis of pumping systems automatically. Fast Discrete Curvelet Transform is firstly adopted to extract features of dynamometer cards that sampled from sucker rod pumping systems, then a sparse multi-graph regularized extreme learning machine alg...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2018-01-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/25888774/view |