The application of modern signal processing techniques to rotor fault detection and location within three phase induction motors

2002 ◽  
Author(s):  
R. Burnett ◽  
J. F. Watson ◽  
S. Elder
Keyword(s):  
Signal Processing ◽  
Fault Detection ◽  
Induction Motors ◽  
Three Phase ◽  
Processing Techniques ◽  
Signal Processing Techniques

scholarly journals Comparative Analysis of Signal Processing Techniques for Fault Detection in Three Phase Induction Motor

2021 ◽  
Vol 3 (1) ◽  
pp. 61-76
Author(s):  
Thomas Amanuel ◽  
Amanuel Ghirmay ◽  
Huruy Ghebremeskel ◽  
Robel Ghebrehiwet ◽  
Weldekidan Bahlibi
Keyword(s):  
Signal Processing ◽  
Fault Detection ◽  
Induction Motor ◽  
Induction Motors ◽  
Research Work ◽  
Detection Accuracy ◽  
Frequency Information ◽  
Three Phase ◽  
Processing Techniques ◽  
Signal Processing Techniques

Signal processing is considered as an efficient technique to detect the faults in three-phase induction motors. Detection of different varieties of faults in the rotor of the motor are widely studied at the industrial level. To extend further, this research article presents the analysis on various signal processing techniques for fault detection in three-phase induction motor due to the damages in rotor bar. Usually, Fast Fourier Transform (FFT) and STFT are used to analyze the healthy and faulty motor conditions based on the signal characteristics. The proposed study covers the advantages and limitations of the proposed wavelet transform (WT) and each technique for detecting the broken bar of induction motors. The good frequency information can be collected from FFT techniques for handling multiple faults identification in three-phase induction motor. Despite the hype, the detection accuracy gets reduced during the dynamic condition of the machine because the frequency information on sudden time changes cannot be employed by FFT. The WT method signal analysis is compared with FFT to propose fault detection method for induction motor. The WT method is proving better accuracy when compared to all existing methods for signal information analysis. The proposed research work has simulated the proposed method with MATLAB / SIMULINK and it helps to effectively detect the healthy and faulty conditions of the motor.

Local Sensor Validation

1989 ◽  
Vol 22 (5) ◽  
pp. 132-141 ◽  
Author(s):  
S K Yung ◽  
D W Clarke
Keyword(s):  
Time Series ◽  
Signal Processing ◽  
Fault Detection ◽  
Process Model ◽  
Time Series Models ◽  
Standard Time ◽  
Sensor Validation ◽  
Processing Techniques ◽  
Signal Processing Techniques ◽  
Hierarchical Scheme

Current approaches to plant fault detection require an overall process model. This paper argues that a hierarchical scheme is more efficient in which the lowest level concentrates on validating the signals transmitted by individual sensors. Signals are described in terms of standard time-series models. A fault is defined by the signal's deviation from its expected behaviour and various signal processing techniques are described which detect these aberrations.

Sign in / Sign up

Export Citation Format

Share Document