摘要
针对抽油机受周期性交变载荷,容易造成载荷传感器漂移、失真等问题,导致影响工况诊断结果,基于三相电参数反演示功图深度学习模型,固化在相应的计算模块中,并将其内嵌在设备中,并研发了三相电参采集、功率计算、深度学习模型系统集成、数据传输功能等模块,设计了一种基于电参数转示功图的设备。现场试验表明,电参数转示功图技术终端设备提高了示功图预测精度,可以逐步替换载荷传感器,实现无传感器低成本、高效率的油井数字化管理。
In view of the problems of load sensor drift and distortion easily caused by pumping unit subjected to periodic alternating load, which will affect the working condition diagnosis results, based on the three-phase electrical parameters inverse demonstration power diagram deep learning model, solidified in the corresponding calculation module, and embedded in the equipment, and developed three-phase electrical parameter acquisition, power calculation, deep learning model system integration, data transmission power In this paper, a kind of device is designed based on the conversion of electrical parameters to indicator diagram. The field test shows that the terminal equipment of electric parameter conversion indicator diagram technology improves the accuracy of indicator diagram prediction, and can gradually replace the load sensor, so as to realize low-cost and high-efficiency digital management of oil wells without sensors.
作者
梁毅
甘庆明
赵春
雷宇
Liang Yi;Gan Qing Ming;Zhao Chun;Lei Yu(National Engineering Laboratory for Exploration and Development of Low-Penneability Oil and Gas Fields Shanxi Xian;Gas Technology Research Institute of Changqing oilfield company,Shanxi Xian)
出处
《长江信息通信》
2021年第4期94-97,共4页
Changjiang Information & Communications
关键词
抽油机
载荷传感器
电参数
示功图
Oil pumping machine
Load cell
Electrical parameters
Indicator diagram