Comparative analysis of harmonic sensitivity for stator fault diagnosis in induction motors

• Autor(a) principal: Abderrahim, Allal
• Data de Publicação: 2024
• Outros Autores: Zakaria, Lamouchi, Khechekhouche, Abderrahmane, Siqueira, Antonio Marcos de Oliveira, Campos, Julio César Costa, Lamamra, Kheireddine
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista de Engenharia Química e Química
• Texto Completo: https://periodicos.ufv.br/jcec/article/view/18212
• topic: Inter-Turns. Motor induction. FFT. Time harmonics. Slots rotor harmonics. Eccentricity fault harmonics. Rotor bar fault harmonics.

Induction motors play a vital role in various industrial applications due to their commendable efficiency and reliability. However, their susceptibility to faults, especially in challenging industrial environments, highlights the need for vigilant fault detection to prevent unforeseen downtimes and reduce subsequent repair costs. Early fault diagnosis is crucial in this context. A systematic approach to diagnosing faults in asynchronous motors involves the application of signal processing techniques, particularly utilizing the Fast Fourier Transform (FFT). The FFT, as a mathematical tool, enables a comprehensive analysis of signals, facilitating the identification and isolation of their frequency components. Monitoring the frequency components within a motor's signal provides a means to determine the existence and severity of faults. FFT analysis allows for the monitoring of four distinct categories of harmonics: time harmonics (TH), rotor slot harmonics (RSH), rotor bar fault harmonics (RBFH), and eccentricity fault harmonics (EFH). Each type of harmonic offers valuable insights into specific fault categories. Empirical evidence, drawn from experimental results, emphasizes the heightened sensitivity of rotor slot harmonics (RSH) in detecting stator faults. Continuous monitoring of the RSH frequency component enables the prompt detection and localization of stator faults, along with an assessment of their severity. Additionally, this diagnostic methodology proves effective in identifying micro short-circuits between stator coils, allowing for a proactive strategy in predictive maintenance. This proactive approach enables anticipatory part replacement before degradation progresses to the point of causing comprehensive failure in the production chain. The combination of FFT-based signal processing and harmonic analysis establishes a robust framework for the early detection and localization of faults in asynchronous motors within industrial settings. This contributes to enhanced operational reliability and efficiency, ultimately ensuring smoother industrial processes.