Diagnosis of ITSC fault in the electrical vehicle powertrain system through signal processing analysis

Ouamara, Dehbia; Boukhnifer, Moussa; Chaibet, Ahmed; Maidi, Ahmed

doi:10.29354/diag/161309

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…These techniques are characterized by their simplicity and do not necessitate supplementary sensors and computational power [30], they are, however, less effective for transient signals and are better suited for stationary signals or those with minimal noise.…”

Section: First Simulation: Absence Of Faults For the First And The Se...mentioning

confidence: 99%

Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy

Ouarhlent,

Terki,

Hamiane

et al. 2023

Diagnostyka

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This article addresses the problem of fault detection in robot manipulator systems. In the production field, online detection and prevention of unexpected robot stops avoids disruption to the entire manufacturing line. A number of researchers have proposed fault diagnosis architectures for electrical systems such as induction motor, DC motor, etc..., utilising the technique of discrete wavelet transform. The results obtained from the use of this technique in the field of diagnosis are very encouraging. Inspired by previous work, The objective of this paper is to present a methodology that enables accurate fault detection in the actuator of a two-degree of freedom robot arm to avoid system performance degradation. A partial reduction in joint torque constitutes the actuator fault, resulting in a deviation from the desired end-effector motion. The actuator fault detection is carried out by analysing the torques signals using the wavelet transform. The stored energy at each level of the transform contains information which can be used as a fault indicator. A Matlab/Simulink simulation of the manipulator robot demonstrates the effectiveness of the proposed technique.

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Section: First Simulation: Absence Of Faults For the First And The Se...mentioning

confidence: 99%

Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy

Ouarhlent,

Terki,

Hamiane

et al. 2023

Diagnostyka

View full text Add to dashboard Cite

show abstract

“…Recently, authors in [29] carried out a study about the detection and identification of ITSC in stator windings in induction motors by applying FFT and STFT analysis using the residual current between the actual stator current and the estimated one by EKF. This study confirms the effectiveness of the STFT analysis compared to the FFT analysis.…”

Section: Introductionmentioning

confidence: 99%

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Romdhane,

Naoui,

Mansouri

2023

Electronics

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To avoid damaging the motor and its surrounding equipment, detecting Inter-Turn Short Circuit (ITSC) faults in Permanent Magnet Synchronous Motors (PMSMs) applied in electric vehicles is a crucial task. In this paper, the detection of ITSC faults in stator winding for PMSMs is carried out by means of the Extended KALMAN Filter (EKF) algorithm combined with the Fuzzy Logic Estimator (FLE). To estimate the motor parameters, including the rotor position and speed, the EKF algorithm uses the measured stator currents and voltages beside the stator resistance, which is calculated in advance using fuzzy logic and fed to the EKF. The change behaviors of the estimated parameters were then used to detect short circuit faults in the PMSM. Using Matlab/Simulink, the proposed FL-EKF algorithm was implemented and tested on a faulty PMSM controlled by Field Oriented Control (FOC). The observation of a perfect estimation of the stator resistance through the simulation helps to precisely detect the failure, and that demonstrates the sensitivity and robustness of the proposed approach.

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The application of time-frequency methods of acoustic signal processing in the diagnostics of tram drive components

Mokrzan,

Nowakowski,

Szymański

2023

AoT

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The paper presents the course of investigations and the analysis of the possibility of applying selected methods of time-frequency processing of non-stationary acoustic signals in the assessment of the technical condition of tram drive components, as well as a new combined method proposed by the authors. An experiment was performed in the form of a pass-by test of the acoustic pressure generated by a Solaris Tramino S105p tram. A comparative analysis has been carried out for an efficient case and a case with damage to the traction gear of the third bogie in the form of broken gear teeth. The recorded signal was analyzed using short-time Fourier transform (STFT) and continuous wavelet transform (CWT). It was found that the gear failure causes an increase in the sound level generated by a given bogie for frequencies within the range of characteristic frequencies of the tested device. Due to the limitations associated with the fixed window resolution in STFT and the inability to directly translate scales to frequencies in CWT, it was found that these methods can be helpful in determining suspected damage, but are too imprecise and prone to errors when the parameters of both transforms are poorly chosen. A new CWT-Cepstrum method was proposed as a solution, using the wavelet transform as a pre-filter before cepstrum signal processing. With a sampling rate of 8192 Hz, a db6 mother wavelet, and a scale range of 1:200, the new method was found to infer the occurrence of damage in an interpretation-free manner. The results were validated on an independent pair of trams of the same model with identical damage and as a reference on a pair of undamaged trams demonstrating that the method can be successfully replicated for different vehicles.

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Diagnosis of ITSC fault in the electrical vehicle powertrain system through signal processing analysis

Cited by 3 publications

References 21 publications

Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy

Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

The application of time-frequency methods of acoustic signal processing in the diagnostics of tram drive components

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