A Review of the Monitoring and Damping Unbalanced Magnetic Pull in Induction Machines Due to Rotor Eccentricity

Salah, Ahmad A.; Dorrell, David G.; Guo, Youguang

doi:10.1109/tia.2019.2892359

Cited by 42 publications

(36 citation statements)

References 92 publications

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“…which is known as the lower side-band harmonic (LSH), is commonly tracked for the diagnosis of rotor asymmetries. During a start-up transient, the trajectory of the LSH in the TF plane given by (20) generates a typical V-shaped fault signature [46], with a frequency that initially (s = 1) is equal to the fundamental frequency f 1 , decreases to 0 (s = 0.5) and then increases again until its steady-state regime value of f 1 (1 − 2s) ≈ f 1 , according to (20). The ability to detect this fault harmonic using the proposed method is to be assessed in this section.…”

Section: Experimental Validationmentioning

confidence: 99%

“…• first, the bandwidth of diagnostic interest is established. In this case, from (20), the frequency band of interest is the [0-50 Hz] band. Due to the presence of higher order harmonics in the current spectrum, apart form the LSH, a wider band [0-125 Hz] has been selected, in order to better assess the strength of the LSH compared with them.…”

Section: The Analysis Window (15) Is Builtmentioning

confidence: 99%

“…Diverse quantities have been proposed in the technical literature for implementing condition based maintenance systems (CBMS) [1,2], such as the analysis of the stator currents [3][4][5][6][7], machine vibrations [8][9][10], fluxes [11,12], thermal images [13] or acoustic signals [14,15]. These techniques have been applied to detect different types of faults not only of the IM, such as stator inter-turn short circuits [11,16], broken bars [17,18], rotor asymmetries [19], eccentricity [20], bearing faults [6,21], but also of the inverter drive [3] or the mechanical coupling to the load, as gearboxes and pulleys [3,22].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines

et al. 2019

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Induction machines drive many industrial processes and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not the case for wind generators, motors driving varying loads, and so forth. In these cases, an analysis in the time-frequency domain-such as a spectrogram-is required for detecting faults signatures. The spectrogram is built using the short time Fourier transform, but its resolution depends critically on the time window used to generate it-short windows provide good time resolution but poor frequency resolution, just the opposite than long windows. Therefore, the window must be adapted at each time to the shape of the expected fault harmonics, by highly skilled maintenance personnel. In this paper this problem is solved with the design of a new multi-band window, which generates simultaneously many different narrow-band current spectrograms and combines them into as single, high resolution one, without the need of manual adjustments. The proposed method is validated with the diagnosis of bar breakages during the start-up of a commercial induction motor.

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Section: Experimental Validationmentioning

confidence: 99%

Section: The Analysis Window (15) Is Builtmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines

et al. 2019

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“…Besides, in case of a faulty machine, the air gap length or the configuration of the windings may become asymmetrical, making it difficult to use labour-saving procedures that are valid only for symmetrical conditions. In particular, the eccentricity fault [32,33] gives rise to a non-uniform air gap length, which becomes a function of the angular coordinate. Moreover, this function can be different for each rotor position [34].…”

Section: Introductionmentioning

confidence: 99%

Winding Tensor Approach for the Analytical Computation of the Inductance Matrix in Eccentric Induction Machines

Martínez-Román

Puche-Panadero

Sapena-Bañó

et al. 2020

Sensors

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Induction machines (IMs) are critical components of many industrial processes, what justifies the use of condition-based maintenance (CBM) systems for detecting their faults at an early stage, in order to avoid costly breakdowns of production lines. The development of CBM systems for IMs relies on the use of fast models that can accurately simulate the machine in faulty conditions. In particular, IM models must be able to reproduce the characteristic harmonics that the IM faults impress in the spatial waves of the air gap magneto-motive force (MMF), due to the complex interactions between spatial and time harmonics. A common type of fault is the eccentricity of the rotor core, which provokes an unbalanced magnetic pull, and can lead to destructive rotor-stator rub. Models developed using the finite element method (FEM) can achieve the required accuracy, but their high computational costs hinder their use in online CBM systems. Analytical models are much faster, but they need an inductance matrix that takes into account the asymmetries generated by the eccentricity fault. Building the inductance matrix for eccentric IMs using traditional techniques, such as the winding function approach (WFA), is a highly complex task, because these functions depend on the combined effect of the winding layout and of the air gap asymmetry. In this paper, a novel method for the fast and simple computation of the inductance matrix for eccentric IMs is presented, which decouples the influence of the air gap asymmetry and of the winding configuration using two independent tensors. It is based on the construction of a primitive inductance tensor, which formulates the eccentricity fault using single conductors as the simplest reference frame; and a winding tensor that converts it into the inductance matrix of a particular machine, taking into account the configuration of the windings. The proposed approach applies routine procedures from tensor algebra for performing such transformation in a simple way. It is theoretically explained and experimentally validated with a commercial induction motor with a mixed eccentricity fault.

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“…Eccentricity is a common type of IM fault [21,28,29,[50][51][52][53][54][55], which is caused primarily because of maladjustment of bearings, load imbalance, shaft flexibility, thermal deformations, or misalignments [56]. The asymmetry of the magnetic field in the non-uniform air gap of the eccentric IM produces radial forces [53], that is, an unbalanced magnetic pull (UMP) [57][58][59][60][61], which generates abnormal vibrations, damages in the shaft bearings, destructive rotor-stator rub [62] or even sparks during the starting of the motor [63].…”

Section: Introductionmentioning

confidence: 99%

Induction machine model with space harmonics for fault diagnosis based on the convolution theorem

Sapena-Bañó

Martínez-Román

Puche-Panadero

et al. 2018

International Journal of Electrical Power & Energy Systems

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Condition based maintenance systems (CBM) of induction machines (IMs) require fast and accurate models that can reproduce the fault related harmonics generated by different kinds of faults, in order to help in developing new diagnostic algorithms for detecting the faults at an early stage, to analyse the physical interactions between simultaneous faults of different types, or to train expert systems that can supervise and identify these faults in an autonomous way. To achieve these goals, such models must take into account the space harmonics of the air gap magnetomotive force (MMF) generated by the machine windings under fault conditions, due to the complex interactions between spatial and time harmonics in a faulty machine. One of the most common faults in induction machines is the rotor eccentricity, which can cause significant radial forces and, in extreme cases, produce destructive rotor-stator rub. But the development of a fast, analytic model of the eccentric IM is a challenging task, due to the nonuniformity of the air gap. In this paper, a new method is proposed to obtain such a fast model. This method, which is theoretically justified, enables a fast calculation of the self and mutual inductances of the stator and rotor phases for every rotor position. The proposed method is validated first using a finite elements method (FEM) model, and then, through an experimental test-bed using commercial induction motors with a forced mixed eccentricity fault.

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A Review of the Monitoring and Damping Unbalanced Magnetic Pull in Induction Machines Due to Rotor Eccentricity

Cited by 42 publications

References 92 publications

Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines

Multi-Band Frequency Window for Time-Frequency Fault Diagnosis of Induction Machines

Winding Tensor Approach for the Analytical Computation of the Inductance Matrix in Eccentric Induction Machines

Induction machine model with space harmonics for fault diagnosis based on the convolution theorem

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