scholarly journals Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

Sensors ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 146 ◽  
Author(s):  
◽  
◽  
◽  
◽  
Keyword(s):  
Fault Diagnosis ◽  
Induction Machines ◽  
Transient Regime ◽  
Current Sensors

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

scholarly journals Fault Diagnosis of Induction Machines in Transient Regime Using Current Sensors with an Optimized Slepian Window

2017 ◽  
Author(s):  
Jordi Burriel-Valencia ◽  
Ruben Puche-Panadero ◽  
Javier Martinez-Roman ◽  
Angel Sapena-Baño ◽  
Manuel Pineda-Sanchez
Keyword(s):  
Fault Diagnosis ◽  
Induction Machines ◽  
Transient Regime ◽  
Sequence Length ◽  
Time Frequency ◽  
Stator Current ◽  
Start Up ◽  
Analysis Window ◽  
Computational Resources ◽  
Short Time

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as analysis window. In this paper the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15 MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

scholarly journals Fault Diagnosis of Induction Machines in Transient Regime Using Current Sensors with an Optimized Slepian Window

2017 ◽  
Author(s):  
Jordi Burriel-Valencia ◽  
Ruben Puche-Panadero ◽  
Javier Martinez-Roman ◽  
Angel Sapena-Bañó ◽  
Manuel Pineda-Sanchez
Keyword(s):  
Fault Diagnosis ◽  
Induction Machines ◽  
Transient Regime ◽  
Sequence Length ◽  
Time Frequency ◽  
Stator Current ◽  
Start Up ◽  
Analysis Window ◽  
Computational Resources ◽  
Short Time

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as analysis window. In this paper the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15 MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

scholarly journals Fault Diagnosis in the Slip–Frequency Plane of Induction Machines Working in Time-Varying Conditions

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3398 ◽  
Author(s):  
Ruben Puche-Panadero ◽  
Javier Martinez-Roman ◽  
Angel Sapena-Bano ◽  
Jordi Burriel-Valencia ◽  
Martin Riera-Guasp
Keyword(s):  
Fault Diagnosis ◽  
Single Point ◽  
General Scheme ◽  
Induction Machine ◽  
Induction Machines ◽  
Transient Conditions ◽  
Time Frequency ◽  
Bearing Defects ◽  
Motor Current Signature Analysis ◽  
The Hilbert Transform

Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unfortunately, the MCSA method in its basic formulation can only be applied in steady state functioning. Nevertheless, every day increases the importance of inductions machines in applications such as wind generation, electric vehicles, or automated processes in which the machine works most of time under transient conditions. For these cases, new diagnostic methodologies have been proposed, based on the use of advanced time-frequency transforms—as, for example, the continuous wavelet transform, the Wigner Ville distribution, or the analytic function based on the Hilbert transform—which enables to track the fault components evolution along time. All these transforms have high computational costs and, furthermore, generate as results complex spectrograms, which require to be interpreted for qualified technical staff. This paper introduces a new methodology for the diagnosis of faults of IM working in transient conditions, which, unlike the methods developed up to today, analyzes the current signal in the slip-instantaneous frequency plane (s-IF), instead of the time-frequency (t-f) plane. It is shown that, in the s-IF plane, the fault components follow patterns that that are simple and unique for each type of fault, and thus does not depend on the way in which load and speed vary during the transient functioning; this characteristic makes the diagnostic task easier and more reliable. This work introduces a general scheme for the IMs diagnostic under transient conditions, through the analysis of the stator current in the s-IF plane. Another contribution of this paper is the introduction of the specific s-IF patterns associated with three different types of faults (rotor asymmetry fault, mixed eccentricity fault, and single-point bearing defects) that are theoretically justified and experimentally tested. As the calculation of the IF of the fault component is a key issue of the proposed diagnostic method, this paper also includes a comparative analysis of three different mathematical tools for calculating the IF, which are compared not only theoretically but also experimentally, comparing their performance when are applied to the tested diagnostic signals.

Harmonic Order Tracking Analysis: A Novel Method for Fault Diagnosis in Induction Machines

2015 ◽  
Vol 30 (3) ◽  
pp. 833-841 ◽  
Author(s):  
Angel Sapena-Bano ◽  
Manuel Pineda-Sanchez ◽  
Ruben Puche-Panadero ◽  
Juan Perez-Cruz ◽  
Jose Roger-Folch ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Induction Machines ◽  
Harmonic Order ◽  
Order Tracking ◽  
Novel Method

scholarly journals A Novel Structure for Vector Control of Symmetrical Six-Phase Induction Machines with Three Current Sensors

2011 ◽  
Vol 1 (2) ◽  
pp. 23-29
Author(s):  
H. P. Nabi ◽  
P. Dadashi ◽  
A. Shoulaie
Keyword(s):  
Vector Control ◽  
Dynamic Performance ◽  
Induction Machine ◽  
Induction Machines ◽  
Experimental Results ◽  
Machine Drive ◽  
Novel Structure ◽  
Current Sensors ◽  
Machine Drives ◽  
Multiphase Machine

Vector control is one of the most popular multiphase induction machine drive methods due to its dynamic performance. Since all phase currents are needed in vector control drive, by increasing phase numbers, the number of required current sensors increases which is one of the disadvantages of vector control in multiphase machine drives. In this paper vector control of a symmetrical six-phase induction machine with a novel configuration is presented. The aforementioned configuration is designed in a simple way that only three current sensors will be needed. Analytical equations are extracted in this paper to show that some of current components which do not contribute in torque production will be eliminated due to the proposed scheme. Simulation and experimental results are provided to verify the benefits of the proposed configuration.

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
Sign in / Sign up

Export Citation Format

Share Document