Shows improved fault detection in low-voltage induction motors, indicating early intervention benefits.
Low-voltage induction motors are widely used in industry and commercial settings, where reliable operation and early fault detection are crucial to prevent downtime. Past detection methods often rely only on electrical signals, overlooking complex electromechanical interactions that affect fault signatures, especially in vibration signals. This paper introduces a fully coupled electromechanical interaction (F-EMI) model designed for fault detection in low-voltage three-phase squirrel cage induction motors. The model integrates electromagnetic forces, bearing dynamics, and structural deformation to simulate motor behavior under healthy and faulty conditions. The model captures ten key interaction pathways between mechanical and electrical parts and generates realistic fault vibration signals. Validation experiments cover four conditions: healthy, mechanical looseness, stator open-circuit, and bearing outer-race faults. Comparisons of simulated and measured vibration spectra show that the F-EMI model accurately reproduces fault-specific frequencies and broadband levels. These results demonstrate the model’s value for predictive maintenance and fault diagnosis in low-voltage motor applications requiring accurate, system-level interaction modeling.
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Joe et al. (2026) studied this question.
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