Abstract
Broken rotor bars fault detection in inverter-fed squirrel cage induction motors is still as difficult as the dynamics introduced by the control system or the dynamically changing excitation (stator) frequency. This paper introduces a novel fault diagnosis techniques using motor current signature analysis (MCSA) to solve the problems. Switching function concept and frequency modulation theory are firstly used to model fault current signal. The competency of the amplitude of the sideband components at frequencies (1±2s)fsas indices for broken bars recognition is subsequently studied in the controlled motor via open-loop constant voltage/frequency control method. The proposed techniques are composed of five modules of anti-aliasing signal acquisition, optimal-slip-estimation based on torque-speed characteristic curve of squirrel cage motor with different load types, fault characteristic frequency determination, nonparametric spectrum estimation, and fault identification for achieving MCSA efficiently. Experimental and simulation results obtained on 3 kW three-phase squirrel-cage induction motors show that the model and the proposed techniques are effective and accurate.
Highlights
Squirrel-cage induction motors have dominated the field of electromechanical energy conversion
This paper introduces a novel fault diagnosis techniques using motor current signature analysis (MCSA) to solve the problems
Unlike the utility-driven case, the stator excitation frequency will dynamically change and the position of the current harmonics appearing on the stator-current spectrum due to electrical faults is highly dependent on the mechanical motor load and excitation frequency, which affects the slip frequency
Summary
Squirrel-cage induction motors have dominated the field of electromechanical energy conversion. They consume more than 60% of the electrical energy produced and are present in the main industrial applications [1, 2]. Broken rotor bars and cracked end-ring faults in the rotor cage are responsible for about 5–10% of all breakdowns and incipient detection of these events remains a key issue [4, 5]. The main reason why early detection is important is that broken rotor bars may not cause immediate failure, there can be serious secondary effects associated with their presence [6, 7]. Health-monitoring techniques to prevent the induction motor failures are of great concern in the industry and are gaining an increasing attention
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