| 基于RBF神经网络的往复泵泵阀故障诊断研究 |
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| 引用本文： | 王长忠,李伟平,吴正军. 基于RBF神经网络的往复泵泵阀故障诊断研究[J]. 石油矿场机械, 2011, 40(1): 24-27 |
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| 作者姓名： | 王长忠 李伟平 吴正军 |
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| 作者单位： | 1. 大庆职业学院,黑龙江,大庆,163000
2. 大庆油田,采油六厂,黑龙江,大庆,163000 |
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| 基金项目： | 黑龙江省教育厅科研项目(11515001) |
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| 摘 要： | 根据小波包分析,获得了各频带能量的分布规律,构造了泵阀状态特征向量,训练了RBF神经网络。大量的现场试验证明,构造的故障特征向量与RBF神经网络配合使用的方法可以明显提高泵阀故障诊断的准确率。
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| 关 键 词： | 往复泵 故障诊断 故障特征向量 RBF神经网络 |
Fault Diagnosis Approach Based on RBF Neural Network for Valves of Reciprocating Pumps |
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| WANG Chang-zhong,LI Wei-ping,WU Zheng-jun. Fault Diagnosis Approach Based on RBF Neural Network for Valves of Reciprocating Pumps[J]. Oil Field Equipment, 2011, 40(1): 24-27 |
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| Authors: | WANG Chang-zhong LI Wei-ping WU Zheng-jun |
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| Affiliation: | WANG Chang-zhong1,LI Wei-ping2,WU Zheng-jun2(1.Daqing Vocational College,Daqing 163000,China,2.No.6 Oil Production Plant,Daqing Oilfield,China) |
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| Abstract: | According to wavelet analysis,the energy regularity of each frequency band is found,the characteristic vectors for values of pumps are constructed,the RBF neural network is trained.Through a lot of practices,both the characteristic vectors and the RBF neural network are proved to raise the diagnosis rate for valves of reciprocating pumps. |
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| Keywords: | reciprocating pump fault diagnosis fault characteristic vector RBF neural network |
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