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As the use of electric motors increases in the aerospace and transportation industries where operating conditions continuously change with time, fault detection in electric motors has been gaining importance. Motor diagnostics in a nonstationary environment is difficult and often needs sophisticated signal processing techniques. In recent times, a plethora of new time-frequency distributions has appeared,...
Fault detection in electric motors operating under non-stationary operating conditions has been gaining importance, due to the fact that motors are used in many applications such as actuators in the aerospace and transportation industries operate under conditions that rapidly vary with time. In recent times, a plethora of new time-frequency distributions have appeared that are inherently suited to...
Electric motors often operate under operating conditions that are constantly changing with time. Most of such applications demand high reliability from the motor. Early detection of developing motor faults could help provide this needed reliability. While diagnostics of faults in motors operating under steady state conditions is straight forward due to the use of the well known Fourier transformation,...
Gears form a critical part of many electro-mechanical systems. Since gear faults cause vibrations, and vibration-based diagnostics is very reliable, this has traditionally been the most commonly used approach to detecting gear faults. However, it is expensive due to the use of high-priced accelerometers and sensor wiring. This paper proposes an alternative way of detecting faults in gears coupled...
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