基于云平台的钻机远程状态监测与诊断系统

Remote Monitoring and Diagnosis System for Drilling Rig Based on Cloud Platform

为了高效利用石油钻机各钻井设备的运行状态数据,提前对设备的故障进行预警,减小停机损失,利用石油钻机的远程数据采集、存储及后期的融合、应用分析方法,研究了基于云存储计算平台的石油钻机远程状态监测与预警诊断系统。该系统依靠大数据、云计算技术,充分整合钻机控制器数据资源,并针对钻井泵、绞车等重要设备关键部位增加相应传感器进行重点监测,开发了数据预处理归档模块和后台大数据分析模块等,借助移动网络架构综合实现了钻机制造厂以及钻探公司对目标钻机的实时状态监测、预测性维护与健康管理、故障诊断、统计分析、移动终端人机交互等功能。工业实践结果表明:该系统的建立实现了对目标钻机更及时、全面的远程状态监测与故障预警、诊断服务。研究结果可为钻机的预知维修和按需维修提供可靠的数据支撑。

To efficiently make the most of the operational states data of every equipment of oil drilling rig,so as to conduct early warning of equipment failures and reduce downtime losses,the remote data acquisition,storage and later fusion and application analysis methods of oil drilling rigs were used to develop a remote state monitoring and early warning diagnosis system for oil rigs based on cloud storing and computing platform. The system,depending on big data and cloud computing technology,fully integrates the data resources of the rig controller,and focuses on monitoring the key parts of important equipment like drilling pumps and drawworks by adding sensors. The data pre-processing archive modules and background big data analysis modules were developed. With the help of the mobile network architecture,the rig manufacturer and the drilling company can realize the real-time condition monitoring,predictive maintenance and health management,fault diagnosis,statistical analysis of the garget rig,and human-machine interaction of the mobile terminal. The results of industrial practice show that the establishment of the system realizes a more timely and comprehensive remote condition monitoring and fault warning and diagnosis service for the target drilling rig. The study could provide reliable data support for predictive maintenance and ondemand repair of the rig.