25-08-2017, 09:32 PM
A new algorithm for transient motor current signature analysis using wavelets
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INTRODUCTION
THE induction machine is essential in many industrial
applications. It is therefore desirable to reduce downtime
by employing methods of machine condition monitoring. A
widely used method of induction machine condition
monitoring utilizes the steady-state spectral components of
stator quantities. These spectral components can include
voltage, current and power and can be used to detect broken
rotor bars, bearing failures, air gap eccentricity etc.
Traditionally these techniques have focused on the detection
of faults during steady-state machine operation. [1-2]
The accuracy of these techniques depend on the loading of
the machine, the assumption that the machine speed is
constant, as well as the signal to noise ratio of the spectral
components being examined.
APPLICATION OF THE ALGORITHM
The measured startup current transient of an 11kW
induction motor is shown in Figure 5. Before implementing
the algorithm, the individual measured line currents are
transformed into a single rotating current vector as shown in
Figure 6. This vector is then transformed into the time domain
and used as an input to the extraction algorithm. The algorithm
estimates the frequency, amplitude and phase of the
nonstationary fundamental as shown in Figures 7,8,9. The
fundamental component (which varies with magnitude,
frequency and phase) can be extracted with this algorithm.
This estimate is then subtracted from the input. The resulting
waveform shown in Figure 10 has information relating to the
health of the machine including bad bearings, broken rotor
bars etc.
DETECTION OF BROKEN ROTOR BARS
The algorithm was used to detect broken rotor bars in a ½ hp
induction motor. Two identical rotors were used in this
experiment except that one had a broken rotor bar. The same
bearings and stator was used in order to minimize their
influences on the startup transients. The machine was tested
under loading conditions varying from 30% to 100% to
determine if this method of detection could be successful and
independent of the loading conditions.