کنفرانس بین المللی ماشین و محرکه های الکتریکی

صفحه اصلی / The 5th International Conference on Electrical Machines and Drives

Diagnosis of Broken Rotor Bars in Induction Machines Using a Current Signature-Based Adaptive Extended Kalman Filter

نویسندگان :

Saeed Hajnayeb¹ Seyyed Meysam Seyyed Barzegar² Mohammad Hoseintabar Marzebali³ Javad Keighobadi⁴

1- دانشگاه صنعتی شاهرود 2- دانشگاه صنعتی شاهرود 3- دانشگاه صنعتی شاهرود 4- دانشگاه صنعتی شاهرود

کلمات کلیدی :

Induction motor،Harmonic analysis،Fault diag nosis،Motor current signal analysis،Condition monitoring (CM)،Kalman filters،Spectral analysis

چکیده :

Induction machines (IMs) are extensively utilized in industrial and domestic applications owing to their high efficiency in electromechanical energy conversion. However, broken rotor bars (BRB) can significantly impair machine performance, typically manifesting as sideband harmonics around the fundamental frequency, which serve as reliable fault indicators. This paper introduces an innovative online detection and tracking method for BRB fault frequency characteristics in IMs using an adaptive Extended Kalman Filter (AEKF). Departing from conventional EKF techniques that rely on fixed noise covariance matrices, the proposed approach implements an adaptive mechanism that dynamically adjusts system noise covariance matrices based on residual averaging , enabling real-time updates and enhanced detection accuracy. By utilizing a current sensor, the method precisely identifies the amplitude and frequency of fault-related sideband harmonics while maintaining robust tracking capabilities, even under low-load conditions. Experimental validation conducted on both healthy and faulty rotors—with one, two, and three broken bars—demonstrates the method's superior accuracy and performance compared to traditional fault detection techniques, confirming its effectiveness for real-world industrial monitoring applications.