基于思维进化算法和BP神经网络的电动潜油柱塞泵故障诊断方法  

Failure Diagnosis Method for Electric Submersible Plunger Pump Based on Mind Evolutionary Algorithm and Back Propagation Neural Network

作　　者：于德亮[1,2] 李妍美 丁宝 任玉龙[1] 齐维贵 

机构地区：[1]哈尔滨理工大学电气与电子工程学院,黑龙江哈尔滨150001 [2]大庆油田人才开发院,黑龙江大庆163000 [3]哈尔滨工业大学,黑龙江哈尔滨150001

出　　处：《信息与控制》2017年第6期698-705,共8页Information and Control

基　　金：黑龙江省自然科学基金资助项目(E201305)

摘　　要：针对电动潜油柱塞泵在生产过程中具有故障率高、检泵周期短的问题,提出了一种基于思维进化算法(MEA)和反向传播(BP)神经网络的电动潜油柱塞泵故障诊断方法,可有效地诊断出电动潜油柱塞泵发生的故障,从而延长检泵周期.通过搭建实验平台解决了电动潜油柱塞泵在实际生产过程中获取的历史故障数据少、故障数据类型不全面的问题.首先,在实验平台上模拟电动潜油柱塞泵的不同故障状态,利用井下多参数采集模块和井口仪表测量其运行参数.然后,从相关运行参数中提取出故障特征参数,构造故障特征向量及样本集;利用样本集训练和验证MEA-BP故障诊断模型.最后,使用从实际生产中的电动潜油柱塞泵获取的故障数据集进一步验证该故障诊断模型的有效性.实验结果表明:该故障诊断方法能够实现对电动潜油柱塞泵的故障诊断,避免其故障事故的发生,有效延长检泵周期.We propose a failure diagnosis method for an electric submersible plunger pump on the basis of the mind evolutionary algorithm( MEA) and the back propagation( BP) neural network to solve the problem of high failure rate and short pump inspection period of the electric submersible plunger pump. This method can effectively diagnose failure accidents to prolong the pump inspection cycle. To solve the problem of minimal historical fault data and fault data that do not consider the electric submersible plunger pump in the actual production process,an experimental platform that can simulate the working condition of the electric submersible plunger pump is established. First,we simulate different failure states of the electric submersible plunger pump on the experimental platform,and the operating parameters are measured by using a multi-parameter acquisition module fixed at the bottom of the pump and wellhead instruments. Then,the most representative parameters are extracted from those relative operating parameters to structure the failure feature vectors and sample set. We use the sample set to train and validate the failure diagnosis model. Finally,the effectiveness of the fault diagnosis method is verified by the fault data set of the electric submersible plunger pump obtained from the actual production process. Experimental results show that this failure diagnosis method can diagnose the failure states of electric submersible plunger pump accurately and avoid failure accidents. Thus,this method can prolong the pump inspection cycle of the electric submersible plunger pump effectively.

关 键 词：电动潜油柱塞泵 检泵周期 模拟 神经网络 

分 类 号：TE933.3[石油与天然气工程—石油机械设备] TP18[自动化与计算机技术—控制理论与控制工程]