Induction motors are widely used at industrial level and many researches have been conducted to predict faults and ensure their continuous operation. The present study shows a fault detection system based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method, and the Fast Fourier Transform (FFT) algorithm to perform spectral analysis on the current to detect specific components that characterize faults in different conditions such as damaged bearings, shorted winding in turns, and broken bars. The tests were conducted using a motor test bench and the results show a spectral value obtained by FFT in the frequency of 300 Hz for faults in bearings of the motors 1 and 2. Results also reveal coincidence of 96.9% and 99.46% compared to the results obtained through the theoretical equations included in the MCSA technique, representing values that are within the fault frequency bands on 1x and 2x respectively.
|Title of host publication||Advances in Emerging Trends and Technologies - Volume 2|
|Editors||Miguel Botto-Tobar, Joffre León-Acurio, Angela Díaz Cadena, Práxedes Montiel Díaz|
|Number of pages||11|
|State||Published - 1 Jan 2020|
|Event||1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019 - quito, Ecuador|
Duration: 29 May 2019 → 31 May 2019
|Name||Advances in Intelligent Systems and Computing|
|Conference||1st International Conference on Advances in Emerging Trends and Technologies, ICAETT 2019|
|Period||29/05/19 → 31/05/19|
Bibliographical notePublisher Copyright:
© 2020, Springer Nature Switzerland AG.
- Incipient faults
- Three-phase motor