Simultaneous faults diagnosis and prognostic in induction motor drives under nonstationary conditions

Ameur Fethi Aimer (University Tahar Moulay of Saida)
Ahmed Hamida Boudinar (University of Sciences and Technology of Oran)
Mohamed El-Amine Khodja (University of Sciences and Technology of Oran)
Azeddine Bendiabdellah (University of Sciences and Technology of Oran)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 24, No 2: April 2026

In this paper, an auto regressive (AR) model-based approach is applied in the stator current analysis under non-stationary conditions (case of frequency variation due to variable speed operation). Under these conditions, the identification of fault signatures is almost impossible due the variation of the fundamental frequency using conventional analysis methods. Moreover, this approach is used in the diagnosis of multiple faults occurring simultaneously in induction motor drives. In this aim, the stator current signal is decomposed into short segments then the AR modeling approach is applied on each segment. This approach called short-time ROOT-AR is then applied to solve the problem of the non-stationarity of the stator current signal under variable speed operation. The efficiency of the short-time ROOT-AR approach is evaluated through experimental tests in the diagnosis of multiple faults occurring simultaneously in induction motor drive. Finally, the superiority of the proposed approach is highlighted in comparison with conventional techniques in terms of accuracy, computational time and robustness against the noise.