2026· IEEE Transactions on Instrumentation and Measurement· Vol 75, pp. 3520011-3520011· 0 citations· 75 references
Abstract
Induction machine fault diagnosis using current spectral analysis is a well-established diagnostic technique based on the identification of the characteristic harmonic components generated in the machine current by each type of fault. However, one of the main problems with the application of this technique to the diagnosis of rotor asymmetry faults in induction machines is that the fault components have much lower amplitudes than the fundamental component and can be very close to it, making their detection difficult, especially in transient regimes. To improve the detection of fault harmonics, this work proposes a new diagnostic current signal, the backward-rotating transient current signal, which is generated in the time domain using the Hilbert transform of the stator currents and is free of the strong influence of the fundamental component. The key novelty of this proposal is the combination of the analytical current signals and the symmetrical components method, which produces a purely backward-rotating transient current signal that cannot be obtained using the raw phase current signals. This proposal is presented theoretically and validated in transient regime using a commercial induction motor with rotor asymmetries.
Rotor faults are a prevalent failure mode in induction motors. In the stator current of induction motors, the fault characteristic frequency component is in close spectral proximity to the fundamental component, yet possesses an extremely low amplitude. This makes it prone to being overwhelmed by the leakage of the fun...
Wenbiao Hu, Zhaorui Lv· International Conference on...· 0 citations
Detecting stator winding Short-Circuit (SC) faults in Induction Motors (IMs) is essential to prevent severe damage at early stages of fault development. This work investigates SC fault detection in a laboratory IM under various load conditions, considering both direct grid connection and operation supplied by Variable...
M. Mansoori, Moein Abedini, M. Davarpanah· IEEE Access· 0 citations
Fault detection is one of the most common studies on wind turbines. In this case, the doubly fed induction generator (DFIG) is specifically analyzed. The fault cases analyzed are: inter-turn short circuit and open circuit, in addition to normal operating conditions. The K-means algorithm was used for analysis and class...
Anthony Molina, A. Romero, G. Suvire· Simposio Internacional sobre...· 0 citations
To enhance the harmonic current extraction and control capabilities of permanent magnet synchronous motors under non-stationary conditions, this paper proposes an improved harmonic current extraction method based on multiple virtual winding systems. This paper analyzes the limitations of harmonic current extraction met...
Shu-Guang Zuo, Yao-Hui Gao, Teng Ma· 2026 IEEE International Conf...· 0 citations
This paper presents a machine learning-based approach for the detection of interturn faults in inverter-fed induction motors (IM). An interturn fault in the stator winding is a severe fault that is hard to identify at an early stage because of the switching harmonics and non-sinusoidal excitation. This work proposes a...
Harini Muthusamy, N. S, N. Basha et al.· International Conference on...· 0 citations
Overall, the sample-level results are promising, indicating that the multi-signal, physics-based feature set and interpretability are useful, however, the configuration-level results suggest that the current 9-configuration simulation setup is not yet sufficient for definitive diagnostic accuracy.
Sghiouri Sara, Hamza Sabir, Mohamed Bezza et al.· Engineering Research Express· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.