电潜螺杆泵过程控制故障模型与智能诊断方法

Failure Model and Intelligent Diagnosis Method of Process Control of EPCP

故障诊断指标具有非线性可分相似性、故障与征兆关系不确定性等特点,使得电潜螺杆泵机组难以有效进行现场故障诊断。基于统计过程控制拓展判异准则和经验判断、多参数规则图版、故障权重因子和现场采集数据归一,构建电潜螺杆泵机组现场故障诊断模型,并提出一种多参数过程控制的故障诊断方法。将电潜螺杆泵机组运行和故障类型划分为12种工况,选取电参数、生产参数等7种表征油井生产工况的特征参数,确定现场故障工况判断准则和权重因子,结合过程控制拓展判异准则判断趋势和数据反馈,分析并输出最大概率的故障。依据新疆油田20余口故障井现场所测参数进行实例计算与验证分析,结果表明多参数过程控制与数据反馈现场故障诊断系统具备较强分析功能和直观表现性,能够准确识别电潜螺杆泵机组故障。该方法可为及时诊断和准确判定电潜螺杆泵机组现场运行工况及其故障提供了理论依据和技术支持。

The failure diagnosis indicators are featured by nonlinear separable similarity and uncertain relationship between failures and indications.It is difficult to conduct effective failure diagnosis on site for the electric submersible screw pump(EPCP) unit.Based on the statistical process control extended criterion and empirical judgment, multi-parameter rule charts, failure weight factor and normalization of collected field data, a failure diagnosis model of ESPCP unit was established, and a failure diagnosis method of multi-parameter process control was proposed.The operation and failure types of electric submersible screw pump unit are divided into 12 working conditions, 7 characteristic parameters such as electrical parameters and production parameters were selected to characterize the production conditions of oil wells, and the judgment criteria and weight factors of on-site failure conditions were determined.Combined with the judgment trend of process control extended criteria and data feedback analysis, the failure with the highest probability is output.According to the on-site measured parameters of more than 20 failure wells in Xinjiang Oilfield, example calculation and verification analysis were carried out.The results show that the failure diagnosis method of multi-parameter process control and data feedback has strong analysis function and visualization.It provides theoretical basis and technical support for timely diagnosis and accurate judgment of the operation conditions and failures of ESPCP units.