Diagnosis of Three-Phase Electrical Machines Using Multidimensional Demodulation Techniques

Abstract

Abstract-This paper deals with the diagnosis of three-phase electrical machines and focuses on failures that lead to stator-current modulation. To detect a failure, we propose a new method based on stator-current demodulation. By exploiting the configuration of three-phase machines, we demonstrate that the demodulation can be efficiently performed with low-complexity multidimensional transforms such as the Concordia transform (CT) or the principal component analysis (PCA). From a practical point of view, we also prove that PCA-based demodulation is more attractive than CT. After demodulation, we propose two statistical criteria aiming at measuring the failure severity from the demodulated signals. Simulations and experimental results highlight the good performance of the proposed approach for condition monitoring.

Condition Monitoring of Induction Motors Based on Stator Currents Demodulation

“…Most of the methods for induction machine monitoring could be classified into several categories: vibration monitoring, torque monitoring, temperature monitoring, oil/debris analysis, acoustic emission monitoring, optical fiber monitoring, and current/power monitoring [1][2][3][4][5][6]. MCSA has several advantages since it is a non-invasive technique that avoids the use of extra sensors [6][7][8][9]. Moreover, the stator currents are usually measured for other purposes such as control and protection.…”

“…Hence, current demodulation has been investigated for faults detection and diagnosis. Typical examples include broken rotor bars [18][19][20][21][22], gearbox faults [23] and bearing faults [7], [14], [17], [24]. In order to perform currents demodulation, several authors have employed classical demodulation techniques such as the synchronous demodulator [22], [25][26], the Hilbert transform [18][19][20], [22], [27], timefrequency distributions [14], [17], [28][29][30] or adaptive tracking of sine waves [31].…”

“…In order to perform currents demodulation, several authors have employed classical demodulation techniques such as the synchronous demodulator [22], [25][26], the Hilbert transform [18][19][20], [22], [27], timefrequency distributions [14], [17], [28][29][30] or adaptive tracking of sine waves [31]. Joint IA-IF estimation based on the Concordia transform is investigated in [7], [21], [32]. One advantage of this transform relies on its low computational cost; however, its domain of validity is restricted to balanced three-phase systems.…”

“…One advantage of this transform relies on its low computational cost; however, its domain of validity is restricted to balanced three-phase systems. In [7], a technique based on PCA is presented for joint IA-IF estimation. Moreover, the Teager-Kaiser energy operator has been investigated in [33] for faults detection in induction machine with broken rotor bars, mixed eccentricity, and single-point bearing faults based on stator currents.…”

Induction machine fault detection enhancement using a stator current high resolution spectrum

“…A cost-effective alter native is stator current supervision since current measurement requires limited number of sensors and it is already available for control and protection purposes. A literature survey showed the interest of the approach for mechanical and electrical faults detection [8]- [ lO]. Most authors perform the fault detection by monitoring the additional frequency components introduced by the fault but no precise stator current model is given.…”