A bearing outer raceway fault detection method in induction motors based on instantaneous frequency of the stator current

2018 ◽  
Vol 13 (3) ◽  
pp. 510-516 ◽  
Author(s):  
Xiangjin Song ◽  
Jingtao Hu ◽  
Hongyu Zhu ◽  
Jilong Zhang
Keyword(s):  
Fault Detection ◽  
Instantaneous Frequency ◽  
Induction Motors ◽  
Detection Method ◽  
Stator Current

Microcontroller Realization of an Induction Motors Fault Detection Method based on FFT and Statistics of Fractional Moments

2021 ◽  
Author(s):  
A. L. Morozov ◽  
R. R. Nigmatullin ◽  
G. Agrusti ◽  
P. Lino ◽  
G. Maione ◽  
...  
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Detection Method ◽  
Fractional Moments

Combined Vibration and Stator Current Techniques for Induction Motors Fault Detection – A Review

2021 ◽  
Author(s):  
Julio Ayala ◽  
Matias Meira ◽  
Carlos Verucchi ◽  
Guillermo Bossio ◽  
Gerardo Acosta
Keyword(s):  
Fault Detection ◽  
Induction Motors ◽  
Stator Current

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Teymoor Ghanbari ◽  
Haidar Samet
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
High Performance ◽  
Induction Motors ◽  
Simple Technique ◽  
Harmonic Distortion ◽  
Stator Current ◽  
Three Phase ◽  
Power Frequency ◽  
Faults Diagnosis

AbstractMonitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Sign in / Sign up

Export Citation Format

Share Document