摘要
结合稠油热采过程中柱塞泵设备运行及其故障特点,设计了一种基于物联网的稠油注采柱塞泵状态监控系统。介绍了系统物联网架构、监控系统的功能模块和软件构成。该系统采用无线振动与温度传感器、无线通信网关,对柱塞泵振动等状态实时数据进行采集和传输,构建了基于BP神经网络柱塞泵运行状态预测模型,并选用稠油开采生产背景资料进行BP神经网络的训练。实际应用结果表明,该系统可实现稠油注采过程中柱塞泵实时监测、故障预测和动态分析,系统运行可靠,在稠油开发生产方面具有典型的应用价值。
Based on the operation and fault characteristics of plunger pump in thermal recovery process of heavy oil,the condition monitoring system of plunger pump for heavy oil injection and production based on Internet of Things( IOT) is studied. The IOT architecture of the condition monitoring system of plunger pump is proposed. The data of plunger pump's vibration state are collected and transmitted in real time by wireless vibration and temperature sensors and wireless communication gateway. By designing the condition monitoringfunctions and software composition,the prediction model of plunger pump operation state based on BP neural network was established,and it was trained with the data of heavy oil production. The application results show that,the system can improve the reliability of state prediction and operation of plunger pump in heavy oil injection and production process,and has a certain application value in heavy oil production.
引文
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