Reliable Detection of Rotor Winding Asymmetries in Wound Rotor Induction Motors via Integral Current Analysis

Antonino-Daviu, José A.; Quijano-López, Alfredo; Climente-Alarcón, Vicente; Garin-Abellan, Carlos

doi:10.1109/tia.2017.2672524

Cited by 44 publications

(11 citation statements)

References 34 publications

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“…The detection of some of the previous faults in WRIM has been mainly based on methodologies that rely on the analysis of electrical signals. One of the most recurrent techniques is the well-known spectral analysis of the steady state current using the Fourier transform (Motor Current Signature Analysis, MCSA); the idea is to evaluate the amplitude of the amplified components in case of failure [7][8][9][10]. Other works in the literature have proposed alternative methodologies by analyzing vibration signals [11], or other quantities such as speed and current [12] to diagnose failures in WRIM.…”

Section: Introductionmentioning

confidence: 99%

Detection of Winding Asymmetries in Wound-Rotor Induction Motors via Transient Analysis of the External Magnetic Field

Zamudio-Ramírez

Antonino-Daviu

Osornio-Ríos

et al. 2020

IEEE Trans. Ind. Electron.

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Over recent decades, the detection of faults in induction motors has been mainly focused in cage motors due to their extensive use. However, in recent years wound-rotor motors have received special attention because of their broad use as generators in wind turbine units as well as in some large power applications in industrial plants. Some classical approaches perform the detection of certain faults based on the FFT analysis of the steady state current (MCSA); they have been lately complemented with new transient time-frequency-based techniques to avoid false alarms. Nonetheless, there is still a need to improve the already existing methods to overcome some of their remaining drawbacks and increase the reliability of the diagnostic. In this regard, emergent technologies are being explored, such as the analysis of stray flux at the vicinity of the motor, which has been proven to be a promising option to diagnose the motor condition. Recently, this technique has been applied to detect broken rotor bar failures and misalignments in cage motors, offering the advantage of being a non-invasive tool with simple implementation and even avoiding some drawbacks of well-established tools. However, the application of these techniques to wound rotor induction motors (WRIM) has not been studied. This work explores the analysis of the external magnetic field under the starting to detect rotor winding asymmetry defects in WRIM by using advanced signal processing techniques. Moreover, a new fault indicator based on this quantity is introduced, comparing different levels of fault and demonstrating the potential of this technique to quantify and monitor rotor winding asymmetries in WRIM. Index Terms-Stray flux, time-frequency transforms, transient analysis, wound rotor induction motor.

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Section: Introductionmentioning

confidence: 99%

Detection of Winding Asymmetries in Wound-Rotor Induction Motors via Transient Analysis of the External Magnetic Field

Zamudio-Ramírez

Antonino-Daviu

Osornio-Ríos

et al. 2020

IEEE Trans. Ind. Electron.

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“…Figure 10 shows the time-frequency analyses (two graphs with different frequency ranges are shown in the y-axis for a better fault harmonic identification) corresponding to a H.V. wound rotor induction motor that was driving a ball mill in a cement production factory [42]. The motor was suspected to have a certain level of rotor winding asymmetry.…”

Section: Cage Motor In a Sewage Treatment Plant (30 Kw 400 V)mentioning

confidence: 99%

“…All these evidences led to diagnosing a severe level of rotor winding asymmetry. As a consequence, the rotor winding was inspected, and a deficient contact was found between the slip rings/brushes system of one phase [42], which was causing the asymmetry. This problem, which could have had very negative repercussions for the company, was properly detected and corrected thanks to the application of the starting current analysis.…”

Section: Cage Motor In a Sewage Treatment Plant (30 Kw 400 V)mentioning

confidence: 99%

Electrical Monitoring under Transient Conditions: A New Paradigm in Electric Motors Predictive Maintenance

Antonino-Daviu

2020

Applied Sciences

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Electric motors condition monitoring is a field of paramount importance for industry. In recent decades, there has been a continuous effort to investigate new techniques and methods that are able to determine the health of these machines with high accuracy and reliability. Classical methods based on the analysis of diverse machine quantities under stationary conditions are being replaced by modern methodologies that are adapted to any operation regime of the machine (including transients). These new methods (especially those based on motor startup signal monitoring), which imply the use of advanced signal processing tools, have shown great potential and have provided spectacular advantages versus conventional approaches enabling, among other facts, a much more reliable determination of the machine health. This paper reviews the background of this recent condition monitoring trend and shows the advantages of this new approach with regard to its application to the analysis of electrical quantities. Examples referred to its application to real motors operating in industry are included, proving the huge potential of the transient-based approach and its benefits versus conventional methods.

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“…As is known, many fault diagnosis methods are proposed for the PMSM drive system, mainly focusing on short-circuit fault [6]- [9], static/dynamic eccentricity [10]- [14], partial/ uniform demagnetization [15]- [18], and open phase fault [19]- [21], while the HRC is rarely researched for the PMSM. The studies on the HRC firstly started with induction machine (IM), and they were mainly dependent on voltage drop survey [22], upstream impedance measurement [23], infrared thermograph [24], multi-reference frame controller [25], inverse negative sequence regulator [26], current [27], [28] and voltage [29], [30]. Nowadays, a few literatures begin to focus on the HRC fault diagnosis in the PMSM drive system.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Fault Severity Estimation for High-Resistance Connection in PMSM Drive System

et al. 2019

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In this paper, a fault severity estimation method is presented for high-resistance connection (HRC) in a permanent magnet synchronous machine drive system, being dependent upon the zero sequence voltage component (ZSVC) and stator currents. According to the relationship between the stator current, ZSVC and resistance deviations, a bivariate quadratic equation group is established with regard to the resistance deviations caused by HRC. The resistance deviations are obtained by solving the equation group. Based on the obtained resistance deviations, not only the fault is diagnosed and the faulty phase is identified, but also the HRC fault severity is estimated. Both the simulation and experiment are studied to validate the fault severity estimation method. The results verify the effectiveness and robustness of the proposed fault severity estimation method. INDEX TERMS High-resistance connection, permanent magnet synchronous machine, fault severity estimation, zero sequence voltage component. NOMENCLATURE u a , u b , u c Three-phase stator voltages u 0,m ZSVC between the artificial neutral point and the neutral center of the stator windings i a , i b , i c Three-phase stator currents R a , R b , R c Three-phase stator resistances R s Stator resistance as the PMSM is healthy R m Mean value of three-phase stator resistances. R n Resistance in three-phase balanced resistor network. R Resistance deviation δR j Processed resistance deviation L Stator phase self-inductance M Mutual-inductance between the stator phases d x Angle differences θ Rotor electrical position θ v Angle between the fundamental component and vth harmonic component The associate editor coordinating the review of this manuscript and approving it for publication was Baoping Cai.

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Reliable Detection of Rotor Winding Asymmetries in Wound Rotor Induction Motors via Integral Current Analysis

Cited by 44 publications

References 34 publications

Detection of Winding Asymmetries in Wound-Rotor Induction Motors via Transient Analysis of the External Magnetic Field

Detection of Winding Asymmetries in Wound-Rotor Induction Motors via Transient Analysis of the External Magnetic Field

Electrical Monitoring under Transient Conditions: A New Paradigm in Electric Motors Predictive Maintenance

Quantitative Fault Severity Estimation for High-Resistance Connection in PMSM Drive System

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