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Using the curve moment and the PSO-SVM method to diagnose downhole conditions of a sucker rod pumping unit 被引量:25
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作者 Li Kun Gao Xianwen +1 位作者 Tian Zhongda Qiu Zhixue 《Petroleum Science》 SCIE CAS CSCD 2013年第1期73-80,共8页
Downhole working conditions of sucker rod pumping wells are automatically identified on a computer from the analysis of dynamometer cards. In this process, extraction of feature parameters and pattern classification a... Downhole working conditions of sucker rod pumping wells are automatically identified on a computer from the analysis of dynamometer cards. In this process, extraction of feature parameters and pattern classification are two key steps. The dynamometer card is firstly divided into four parts which include different production information according to the "four point method" used in actual oilfield production, and then the moment invariants for pattern recognition are extracted. An improved support vector machine (SVM) method is used for pattern classification whose error penalty parameter C and kernel function parameter g are optimally chosen by the particle swarm optimization (PSO) algorithm. The simulation results show the method proposed in this paper has good classification results. 展开更多
关键词 Sucker rod pumping unit diagnosis of downhole conditions dynamometer card curvemoment support vector machine particle swarm optimization
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