Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.803917
Title: Motor current signature analysis towards mechanical seal failure detection for electrical submersible pump
Author: Afrizal, Nurafnida
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2020
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Abstract:
Electrical Submersible Pump (ESP) is one of the most efficient and reliable devices to lift fluids to the surface. It is commonly used in the oil and gas industry, where it provides a low-cost solution for high volumes of lifting and the flexibility to cover a range of sizes, output flow capacities, production profiles and various well conditions. The ESP is operated in a very challenging environment and it is exposed to many factors that could lead to its downtime. One of the critical elements for the ESP failure is the mechanical seal. While a significant amount of research has been dedicated to the improvement of the seal design to enhance its performance and reduce the risk of failure, its failure remains among the major contributors towards the ESP failure, with significant consequences in terms of loss of production (downtime) and equipment replacement costs. The aim of the research presented in this thesis is to enhance the condition monitoring of the ESP to allow a more accurate detection of early conditions that could lead to the mechanical seal failure, such as excessive vibrations caused by a misalignment between the motor and the pump shafts. The proposed monitoring method is based on the Motor Current Signature Analysis (MCSA), i.e. the analysis of the stator current in the induction motor connected to the pump. It is known that vibrations produce characteristic features in the current signal, appearing as sidebands in its frequency spectrum; however, those sidebands are difficult to detect and measure because of their small amplitudes and the typical presence of large spectral leakage in the measured current spectra. The main objective of this research is to develop a novel signal processing method to compensate for the leakage error that affects the MCSA, in order to obtain more accurate measurements of the current features of interest to detect the shaft misalignment. An analytical model has been formulated to relate the shaft misalignment to vibrations, and the vibrations to specific sidebands in the motor current spectrum. The model has then been used to run numerical simulations, in order to validate the proposed method in a wide range of conditions, and with different motor power ratings. Finally, a small-scale experimental test rig has been designed to validate the proposed method with motor current measurements from a real motor. The obtained results confirm that the proposed method allows a significant decrease in the spectral leakage affecting sideband measurements in MCSA, with a consequent significant improvement in the estimation of the amplitudes of those sidebands. The method is therefore promising for the detection of vibrations that could lead to the mechanical seal failure in ESP, although further investigations on high-power motors are required in the future for a full validation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.803917  DOI:
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