Journal
CHINESE JOURNAL OF MECHANICAL ENGINEERING
Volume 30, Issue 6, Pages 1285-1295Publisher
EDITORIAL OFFICE CHINESE JOURNAL MECHANICAL ENGINEERING
DOI: 10.1007/s10033-017-0185-2
Keywords
Fault detection; Broken rotor bars; Minnorm; Least squares method; Induction motors
Categories
Funding
- National Natural Science Foundation of China [51607180]
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Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.
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