Locally optimized chirplet spectrogram for condition monitoring of induction machines in transient regime

Measurement ◽  
2022 ◽  
pp. 110690
Author(s):  
J. Martinez-Roman ◽  
R. Puche-Panadero ◽  
A. Sapena-Bano ◽  
J. Burriel-Valencia ◽  
M. Riera-Guasp ◽  
...  
Keyword(s):  
Condition Monitoring ◽  
Induction Machines ◽  
Transient Regime

scholarly journals Detection of Stator and Rotor Asymmetries Faults in Wound Rotor Induction Machines: Modeling, Test and Real-Time Implementation

2021 ◽  
Author(s):  
Shahin Hedayati Kia
Keyword(s):  
Real Time ◽  
Condition Monitoring ◽  
Classical Model ◽  
Induction Machine ◽  
Induction Machines ◽  
Time Data ◽  
Jules Verne ◽  
Three Phase ◽  
Experimental Test Bench ◽  
Different Levels

This chapter deals with detection of stator and rotor asymmetries faults in wound rotor induction machines using rotor and stator currents signatures analysis. This is proposed as the experimental part of fault diagnosis in electrical machines course for master’s degree students in electrical engineering at University of Picardie “Jules Verne”. The aim is to demonstrate the main steps of real-time condition monitoring development for wound rotor induction machines. In this regard, the related parameters of classical model of wound rotor induction machine under study are initially estimated. Then, the latter model is validated through experiments in both healthy and faulty conditions at different levels of the load. Finally, an algorithm is implemented in a real-time data acquisition system for online detection of stator and rotor asymmetries faults. An experimental test bench based on a three-phase 90 W wound rotor induction machine and a real-time platform for hardware-in-the-loop test are utilized for validation of the proposed condition monitoring techniques.

scholarly journals Bearing fault detection by four-band wavelet packet decomposition

2019 ◽  
Vol 23 (Suppl. 1) ◽  
pp. 91-98
Author(s):  
Yalcin Cekic
Keyword(s):  
Computational Complexity ◽  
Production Process ◽  
Condition Monitoring ◽  
Wavelet Packet ◽  
Induction Machines ◽  
Wavelet Packet Decomposition ◽  
Vibration Data ◽  
Monitoring Applications ◽  
Motor Condition ◽  
Motor Vibration

Bearing problems are by far the biggest cause of induction motor failures in the industry. Since induction machines are used heavily by the industry, their unexpected failure may disturb the production process. Motor condition monitoring is employed widely to avoid such unexpected failures. The data that can be obtained from induction machines are non-stationary by nature since the loading may vary during their operation. Wavelet packet decomposition seems to better handle non-stationary nature of induction machines, the use of this method in monitoring applications is limited, since the computational complexity is higher than other methods. In this work four-band wavelet packet decomposition of motor vibration data is proposed to reduce the computational complexity without compromising accuracy. The proposed method is very suitable for parallel computational processing by its nature, and as a result it is predicted that the calculation time will be shortened further if field-progammable gate array is used in design.

scholarly journals Short-Frequency Fourier Transform for Fault Diagnosis of Induction Machines Working in Transient Regime

2017 ◽  
Vol 66 (3) ◽  
pp. 432-440 ◽  
Author(s):  
Jordi Burriel-Valencia ◽  
Ruben Puche-Panadero ◽  
Javier Martinez-Roman ◽  
Angel Sapena-Bano ◽  
Manuel Pineda-Sanchez
Keyword(s):  
Fourier Transform ◽  
Fault Diagnosis ◽  
Induction Machines ◽  
Transient Regime
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