Application of Sweep Frequency Response Analysis and Locked-Rotor Test for Stator Winding Inter-Turn and Broken Rotor Bar Fault Detection of Squirrel-Cage Induction Motors

Master Thesis

2021

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The field of electromagnetic energy conversion has been dominated by induction motors, where more than 80% are three-phase squirrel-cage induction motors (SCIM) [1], [2]. Despite their flexibility, robustness, and high efficiency, they are susceptible to various types of failures due to external or internal factors. Several studies have shown that 30%-40% [3], [4] and 5- 10% [5], [6] of the total failures of induction motor are due to the stator winding breakdown and rotor failures, respectively. Most induction motors have a long service life regardless of types and ratings and warrant minimum maintenance to ensure they work properly. Regular maintenance is recommended to check for signs of insulation damage or other parts that may derate the motor. This reduces motor repair costs, minimizes unscheduled downtime, and enhances industrial processes' reliability [7]. Stator winding faults include inter-turn fault, phase to phase fault, coil to coil fault, and phase to ground fault. The stator winding insulation usually begins with inter-turn faults comprising of a small number of winding turns which makes it more probable than other faults. Manufacturing defects and excessive start-stop cycles or frequent speed changes are mainly the causes of broken rotor bar and end-ring among different rotor fault types [8], but our focus in this study will be on broken rotor bar. Hence, early detection of these faults, both during the manufacturing and operation stages, is essential. Different techniques have been used for assessing the operating conditions of a rotating machine. One of the more popular techniques is motor current signature analysis (MCSA) [9]- [10], which analyses the spectral content of the stator current in determining the state of health. A popular technique for assessing the stator winding insulation is the DC Hipot test, which involves applying a dc voltage higher than that of the peak ac voltage [11]. Unfortunately, this procedure may lead to winding failure and replacement of the affected coil or winding. The sweep frequency response analysis (SFRA) approach, developed by Dick and Erven [12], allows for the detection of small changes in the windings due to the effect of short-circuits by analysing the winding impedance over its bandwidth. This technique is mostly used for transformers and very sensitive to inductance and capacitance between winding turns; therefore, any change in the winding geometrical structure can affect frequency response. Therefore, this project aims to model two devices (inductor to understand better the impedance behaviour of a coil and stator winding) analytically using the impedance transfer function approach. SFRA and locked-rotor test are carried out experimentally on the device under test (DUT) using the impedance transfer function measurement to detect the inter-turn and broken rotor bar fault, respectively. The SFRA technique relies on comparing two measurement results under normal and faults conditions over a wide frequency bandwidth while locked-rotor test relies on a higher excitation current for stator winding impedance extraction as a function of rotor angle to diagnose the SCIM rotor state properly. The results of this study show that SFRA and locked-rotor test are reliable techniques that enables the detection of damages to SCIM's winding and rotor at their incipient stage before a catastrophic failure occurs. It is observed that inter-turn fault mostly affects the inductive and capacitive region of the impedance response plot which in turns reduces the impedance peak and increases the resonant frequency. The appearance of the sinusoidal profile for the substituted impedance from the locked-rotor test indicates that SCIM rotor bar is faulty. Therefore, applying these two techniques for this study to diagnose SCIM will minimise unplanned outages, thereby reducing repair costs and improving the productivity of the system that uses it.
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