Abstract
This paper presents the use of a fuzzy-based statistical feature extraction from the air gap disturbances for diagnosing broken rotor bars in large induction motors fed by line or an inverter. The method is based on the analysis of the magnetic flux density variation in a Hall Effect Sensor, installed between two stator slots of the motor. The proposed method combines a fuzzy inference system and a support vector machine technique for time-domain assessment of the magnetic flux density, in order to detect a single fault or multiple broken bars in the rotor. In this approach, it is possible to detect not only the existence of failures, but also its severity. Moreover, it is not necessary to estimate the slip of the motor, usually required by other methods and the damaged rotor detection was also evaluated for oscillating load conditions. Thus, the present approach can overcome some drawbacks of the traditional MCSA method, particularly in operational cases where false positive and false negative indications are more frequently. The efficiency of this approach has been proven using some computational simulation results and experimental tests to detect fully broken rotor bars in a 7.5 kW squirrel cage induction machine fed by line and an inverter.
Highlights
The three-phase induction motors (IMs) are the main electrical rotating machine installed in many industrial environments
This paper proposes a fuzzy-based approach to extract features from a Hall effect sensor signal to detect air gap disturbances, in a large squirrel cage induction motor with fully broken bars
Some fuzzy statistical features were used as inputs for a support vector machine classifier to detect and classify the severity of rotor faults in an induction motor fed by a line and an inverter
Summary
The three-phase induction motors (IMs) are the main electrical rotating machine installed in many industrial environments. IMs have important advantages, such as robustness, simplicity and lower cost, when compared to other rotating machines (synchronous machines and DC motors, for example) [5], they are subjected to some mechanical and electrical faults, in stator windings, bearings and rotor cage [1,6]. Many researchers and engineers have investigated broken rotor bars and bearing failures in other applications, including commercial cases and industrial plants. Broken rotor bars and cracked end-ring faults share for 5–10% of induction machine failures, but, as cited in [7], these events are a key issue. A partial or a fully broken bar increases the machine vibration [9], the current in the rotor bars adjacent to the faulty one and the temperature rise in the motor [7]
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