Broken Bar Fault Detection Using Taylor-Fourier Filters and Statistical Analysis

• Published in: Entropy (Basel, Switzerland) Vol. 25; no. 1; p. 44
• Main Authors: Aguayo-Tapia, Sarahi, Avalos-Almazan, Gerardo, Rangel-Magdaleno, Jose de Jesus, Paternina, Mario R A
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.12.2022; MDPI
• Subjects: Algorithms; Amplitudes; broken bar; Damage detection; digital Taylor–Fourier transform; Electricity consumption; Fault detection; Fourier transforms; Full load; induction motor; Induction motors; Neural networks; Rotors; Signal analysis; Signal processing; Statistical analysis; stator current; Variance analysis; broken bar; stator current; statistical analysis; induction motor; fault detection; digital Taylor–Fourier transform

Broken rotor bars in induction motors make up one of the typical fault types that are challenging to detect. This type of damage can provoke adverse effects on the motors, such as mechanical and electrical stresses, together with an increase in electricity consumption, causing higher operative costs...