Известия Томского политехнического университета: Инжиниринг георесурсов (Nov 2017)
Evaluation of submersible electric motor insulation residual resource in oil production electric centrifugal pumps under the influence of impulse overvoltages
Abstract
Research relevance. Submersible electric motors are one of the main elements of electric centrifugal pumps in oil industry. Among the reasons for significant non-production losses and decline in oil production is the failure of submersible electric motors, which leads to significant financial costs. The main submersible electric motors faults include: turn-to-turn faults, bearing damage, winding damage, rotor imbalance, wear and breakdown of insulation, and the share of the latter reaches 11 %. The technical service life of submersible electric motors insulation is significantly affected by the number of pulses and the magnitude of energy of internal and external overvoltages, leading to breakdown of insulation. To ensure the required reliability of the electric submersible pumps, it is necessary to monitor the state of the submersible electric motors insulation, therefore, a method is needed to evaluate its residual resource. The main aim of the research is to evaluate the residual resource of the submersible motor insulation of electric centrifugal oil pump installations under the influence of internal and external impulse overvoltages. Research methods. To evaluate the technical isolation resource the authors have proposed the method based on the analysis of the values of the energy consumed by the submersible electric motor insulation, including the algorithms of the Neural Network Toolbox package in Matlab Simulink. Research results. Using an artificial neural network the authors determined the dependence of residual resource of submersible electric motors insulation on energy value of overvoltage, nominal voltage and insulation resistance released by a certain number of impulses. A simulation model of a diagnostic system for monitoring the state of submersible electric motors insulation based on an artificial neural network was developed. The residual insulation resource of two submersible motors was calculated. The authors proposed the measures for protection of submersible motors against impulse overvoltages.
