Advanced diagnosis of rotor faults in large induction motors based on internal flux measurement

Saad, Khalid; Mirzaeva, Galina

doi:10.1109/ias.2016.7731935

Cited by 10 publications

(7 citation statements)

References 31 publications

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“…It goes without saying that multisensory methods require more complex algorithms for fault diagnosis. The following is the list of sensor positions for multisensory approaches (see Figure 5): � IPM1: concentrated [59,60] or pole-specific SC systems in stator slots, � IPM2: a system of SCs around all stator teeth or alternative teeth � IPM3: an array of miniature HEFSs around the circumference of the stator inside the airgap [23,[61][62][63][64].…”

Section: Internal Magnetic Fluxmentioning

confidence: 99%

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Airgap and stray magnetic flux monitoring techniques for fault diagnosis of electrical machines: An overview

Mazaheri‐Tehrani

Faiz

2021

IET Electric Power Appl

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Flux-based fault diagnosis methods have attracted ever-increasing attention from technical communities because of their potential diagnostic capabilities and ability to overcome weaknesses of the traditional methods such as motor current signature analysis (MCSA). This study reviews recent literature on these methods and addresses their strengths and limitations. Different types of flux sensors that can be used for fault diagnosis applications are also discussed. Flux-based approaches are classified based on the type of utilised flux into internal (airgap flux) and external (stray flux) methods and compared with each other. The most common faults in both induction machines (IMs) and permanent magnet machines (PMMs), including inter-turn short-circuit (ITSC), airgap eccentricity (AGE), rotor broken bars (BRB), and irreversible demagnetisation (IDM) faults, are considered in this review. Finally, research gaps are identified, and some suggestions for future research in this area are provided.

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Section: Internal Magnetic Fluxmentioning

confidence: 99%

“…IPM3 : an array of miniature HEFSs around the circumference of the stator inside the airgap [23, 61–64].…”

Section: Magnetic Flux Monitoring Techniquesmentioning

confidence: 99%

Airgap and stray magnetic flux monitoring techniques for fault diagnosis of electrical machines: An overview

Mazaheri‐Tehrani

Faiz

2021

IET Electric Power Appl

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“…These appear in the spectrum of stator-related quantities (stator current or stray flux), modulated by the component (1 − ) because of the continuous induction from the rotor to the stator and vice-versa. The equation for these fault related sideband signatures is the following [36], [37]:…”

Section: A Radial Sfsa and Broken Bar Fault Signaturesmentioning

confidence: 99%

A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals

Panagiotou

Arvanitakis

Lophitis

et al. 2019

IEEE Trans. on Ind. Applicat.

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This work offers a reliable solution to the detection of broken rotor bars in induction machines with a novel methodology, which is based on the fact that the fault related harmonics will have oscillating amplitudes due to the speed ripple effect. The method consists of two main steps: Initially, a timefrequency transformation is used and the focus is given on the steady-state regime; thereupon, the fault related frequencies are handled as periodical signals over time and the classical Fast Fourier Transform is used for the evaluation of their own spectral content. This leads to the discrimination of sub-components related to the fault and evaluation of their amplitudes. The versatility of the proposed method relies on the fact that it reveals the aforementioned signatures to detect the fault, regardless of the spatial location of the broken rotor bars. Extensive finite element simulations on a 1.1MW induction motor and experimental testing on a 1.1kW induction motor lead to the conclusion that, the method can be generalized on any type of induction motor independently from the size, power, number of poles and rotor slot numbers.

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“…These appear in the spectrum of stator-related quantities (stator current or stray flux), modulated by the component (1-s)fs because of induction from the rotor to the stator and viceversa. The equation for these fault related sideband signatures is the following [36], [37]:…”

Section: A Radial Sfsa and Broken Bar Fault Signaturesmentioning

confidence: 99%

Analysis of Stray Flux Spectral Components in Induction Machines under Rotor Bar Breakages at Various Locations

Panagiotou

Arvanitakis

Lophitis

et al. 2018

2018 XIII International Conference on Electrical Machines (ICEM)

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Advanced diagnosis of rotor faults in large induction motors based on internal flux measurement

Cited by 10 publications

References 31 publications

Airgap and stray magnetic flux monitoring techniques for fault diagnosis of electrical machines: An overview

Airgap and stray magnetic flux monitoring techniques for fault diagnosis of electrical machines: An overview

A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals

Analysis of Stray Flux Spectral Components in Induction Machines under Rotor Bar Breakages at Various Locations

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