摘要
针对抽油机在运行时易出现异常工况的问题,对基于电参数信息的抽油机井远程故障诊断方法进行了研究。讨论了故障诊断时电能参数推算变量的测量与计算方法,并将其集成到相关的故障诊断系统中。鉴于诊断模型获取的故障模态的实时性和可靠性,利用fuzzy-ARTMAP神经网络建立了抽油机井电能信息诊断模型。最终的现场试验结果验证了该方法在油井远程故障诊断方面的有效性,表明该项技术具有一定的实用和推广价值。
Aiming at the problem of abnormal conditions often occur when the pumping unit is running,the remote fault diagnosis method based on information of electrical parameters for pumping well is researched.The measurement and calculation methods for calculating variables using electric energy parameters during fault diagnosis are discussed and integrated them into fault diagnosis system.Due to the real-time performance and reliability of acquired fault modes by diagnostic model,by adopting fuzzy-ARTMAP neural network the diagnostic model of diagnostic model of electric energy information of pumping well is established.The result of final field test verifies the effectiveness of this method;this indicates that the technology is valuable in practical application and promotion.
出处
《自动化仪表》
CAS
北大核心
2012年第5期22-24,共3页
Process Automation Instrumentation
关键词
抽油机
故障诊断
电能信息
远程监控系统
神经网络
Pumping unit Fault diagnosis Information of electric energy Remote monitoring system Neural network
