Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network
The core components of submersible screw pump are concentrated underground, so it is difficult to judge the fault timely and accurately. Based on this, this paper proposes a fault diagnosis method of submersible screw pump based on probabilistic neural network (PNN), and develops the corresponding f...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Tamkang University Press
2022-04-01
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| Series: | Journal of Applied Science and Engineering |
| Subjects: | |
| Online Access: | http://jase.tku.edu.tw/articles/jase-202212-25-6-0002 |
| _version_ | 1811297614940864512 |
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| author | Kangxing Dong Qiaoer Li Ziheng Zhang Minzheng Jiang Shufan Xu |
| author_facet | Kangxing Dong Qiaoer Li Ziheng Zhang Minzheng Jiang Shufan Xu |
| author_sort | Kangxing Dong |
| collection | DOAJ |
| description | The core components of submersible screw pump are concentrated underground, so it is difficult to judge the fault timely and accurately. Based on this, this paper proposes a fault diagnosis method of submersible screw pump based on probabilistic neural network (PNN), and develops the corresponding fault diagnosis system. Wavelet packet theory is used to decompose and reconstruct the active power signal of submersible screw pump, extract the main fault information contained in the power signal, and construct the fault feature vector of submersible screw pump combined with the parameters such as output, oil pressure, casing pressure and dynamic liquid level. Based on the historical data of submersible screw pump, a probabilistic neural network model is constructed. The mapping relationship between fault feature vector and fault form is obtained through the historical data training model, so as to judge the fault form to be logged according to the fault feature vector to be logged. 142 groups of fault data are collected to train the model and verify the accuracy of the diagnosis model and the test shows that the accuracy of the diagnosis model is 90.5%. The test results show that the fault diagnosis method of submersible screw pump based on PNN can timely and accurately judge the fault type of submersible screw pump and reduce the economic loss of oilfield production. |
| first_indexed | 2024-04-13T06:06:57Z |
| format | Article |
| id | doaj.art-569294625b8c4140af1b27b1a0ca0a29 |
| institution | Directory Open Access Journal |
| issn | 2708-9967 2708-9975 |
| language | English |
| last_indexed | 2024-04-13T06:06:57Z |
| publishDate | 2022-04-01 |
| publisher | Tamkang University Press |
| record_format | Article |
| series | Journal of Applied Science and Engineering |
| spelling | doaj.art-569294625b8c4140af1b27b1a0ca0a292022-12-22T02:59:13ZengTamkang University PressJournal of Applied Science and Engineering2708-99672708-99752022-04-0125691592310.6180/jase.202212_25(6).0002Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural NetworkKangxing Dong0Qiaoer Li1Ziheng Zhang2Minzheng Jiang3Shufan Xu4School of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, ChinaSchool of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, ChinaSchool of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, ChinaSchool of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, ChinaNo.2 Oil Provide Factory of Daqing Oilfield Co., Ltd., Daqing 163001, ChinaThe core components of submersible screw pump are concentrated underground, so it is difficult to judge the fault timely and accurately. Based on this, this paper proposes a fault diagnosis method of submersible screw pump based on probabilistic neural network (PNN), and develops the corresponding fault diagnosis system. Wavelet packet theory is used to decompose and reconstruct the active power signal of submersible screw pump, extract the main fault information contained in the power signal, and construct the fault feature vector of submersible screw pump combined with the parameters such as output, oil pressure, casing pressure and dynamic liquid level. Based on the historical data of submersible screw pump, a probabilistic neural network model is constructed. The mapping relationship between fault feature vector and fault form is obtained through the historical data training model, so as to judge the fault form to be logged according to the fault feature vector to be logged. 142 groups of fault data are collected to train the model and verify the accuracy of the diagnosis model and the test shows that the accuracy of the diagnosis model is 90.5%. The test results show that the fault diagnosis method of submersible screw pump based on PNN can timely and accurately judge the fault type of submersible screw pump and reduce the economic loss of oilfield production.http://jase.tku.edu.tw/articles/jase-202212-25-6-0002fault diagnosisprobabilistic neural networksubmersible screw pumpwavelet packet |
| spellingShingle | Kangxing Dong Qiaoer Li Ziheng Zhang Minzheng Jiang Shufan Xu Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network Journal of Applied Science and Engineering fault diagnosis probabilistic neural network submersible screw pump wavelet packet |
| title | Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network |
| title_full | Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network |
| title_fullStr | Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network |
| title_full_unstemmed | Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network |
| title_short | Submersible Screw Pump Fault Diagnosis Method Based on a Probabilistic Neural Network |
| title_sort | submersible screw pump fault diagnosis method based on a probabilistic neural network |
| topic | fault diagnosis probabilistic neural network submersible screw pump wavelet packet |
| url | http://jase.tku.edu.tw/articles/jase-202212-25-6-0002 |
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