Fault Diagnosis of the Asynchronous Machines Through Magnetic Signature Analysis Using Finite-Element Method and Neural Networks

Barzegaran, M. R.; Mazloomzadeh, Ali; Mohammed, Osama A.

doi:10.1109/tec.2013.2281325

Cited by 49 publications

(18 citation statements)

References 19 publications

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“…For example, the characteristic frequencies of the fault harmonic components are, for bar breakages in squirrel cage induction machines [ 12 , 13 , 14 ] and rotor asymmetries in wound-rotor induction machines

[ 15 ]

for mixed eccentricity faults

[ 16 , 17 , 18 ]

for inter-turn short-circuits in the stator winding

[ 19 , 20 , 21 , 22 ]

and for mechanical looseness

[ 23 ]

where s is the slip,

is the frequency of the power supply and p is the pole pairs number. Other types of faults, such as bearing faults [ 24 , 25 , 26 ], or gearbox faults [ 27 ] generate components in the stator current with frequency expressions similar to Equations ( 1 )–( 4 ).…”

Section: Introductionmentioning

confidence: 99%

Partial Inductance Model of Induction Machines for Fault Diagnosis

Pineda-Sánchez

Puche-Panadero

Martínez-Román

et al. 2018

Sensors

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The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases’ coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases’ inductances. The proposed method is validated using a commercial induction motor with forced broken bars.

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[ 15 ]

for mixed eccentricity faults

[ 16 , 17 , 18 ]

for inter-turn short-circuits in the stator winding

[ 19 , 20 , 21 , 22 ]

and for mechanical looseness

[ 23 ]

where s is the slip,

Section: Introductionmentioning

confidence: 99%

Partial Inductance Model of Induction Machines for Fault Diagnosis

Pineda-Sánchez

Puche-Panadero

Martínez-Román

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…For uninterrupted operation, as well as to prevent machinery faults, the implementation of an online (real time) RA system is essential. Among the contemporary online technologies, a nonintrusive approach is the air gap flux signature method, in which the antenna or sensor is installed inside the machine shaft, and the stray magnetic field is measured to diagnose the fault (Barzegaran et al , 2013). Though it illustrates promising results in identifying inter-turn short circuit, the method has two restraints, which this paper overcomes.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive design analysis of a 3D printed sensor for readiness assessment applications

Agarwal

Rahmani

Zaman

et al. 2021

COMPEL

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Purpose This paper aims to develop a comprehensive model of a magnetic sensor array that will be operational for a multitude of electric components in continuous and nonintrusive condition monitoring (CM) or in readiness assessment (RA) applications. Design/methodology/approach A universal nonintrusive model of a flexible antenna array is introduced to monitor and identify failures in electric machine drives. An adjustable sensor is designed to serve as a RA for a vast range of electrical elements in a typical power system by capturing the low-frequency radiated magnetic fields. Findings The optimal placement of the most sensitive radiated fields from several components has been discovered in this case study, enabling the detection of healthy current flow throughout. Thereafter, the short-circuit investigation, representing faulty situations, is implemented and compared with healthy cases. Practical implications This sensing technique can be used for nonintrusive CM of components that are out of reach and cannot have the sensor to be held around it such as components in offshore winds, wind energy generation and power and chemical plants. Originality/value The results are provided for three commonly used machines with a single sensor array with numerous settings. The three dimensional (3 D) finite element analysis is applied in the structuring of the sensor, detection of the optimum location and recognition of faults in the machines. Finally, based on the setup design, 3 D printing is used for the construction of the sensor array. Thus, the sensor array with fault detection avoids major component failures and increases system reliability/resiliency.

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“…Along these lines, we attempted in this research to utilise an online method, which does not have this downside. This work is a completion of a work that was published in [5] with the focus on the sensor placement for inaccessible cases.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous beneficial researches were published about this method [6][7][8][9]. In [5,6], the broken bar and stator winding short circuit were analysed through data acquisition approaches and accordingly experiments in different range of frequencies, low as well as medium. Correspondingly, the authors in [10] demonstrated the reliability of fault recognition on machines by exploration of the magnetic flux signature.…”

Section: Introductionmentioning

confidence: 99%

Wide area condition monitoring of power electric drives in wind power generation system using radiated electromagnetic fields

Amrit

Barzegaran

Mohammed

2018

IET Power Electronics

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Electric components in numerous applications (particularly wind generation) are not straightforwardly accessible for monitoring. Therefore, the monitoring and protection through voltage/current measurement may not be dependable since the current value passes numerous segments to reach the observing element. Accordingly, finding an unusual phenomenon of a specific element is difficult. To resolve this issue, using transmitted electromagnetic field of an element for wide area condition monitoring is proposed. It is planned to diagnose and locate short-circuit in induction generator drive such as interturn, intercoil and terminal-to-turn failures. The frequency characteristics of the propagated field is then utilized for finding the short-circuit. The theoretical foundation that relate the behavior of each elements to their frequency response is analyzed and used. To utilize the derived technique for different practical circumstances, two distinctive methods are used for locating the short-circuit. As the experimental test of major fault cases could destruct the winding, the full three-dimensional finite element analysis is used in these cases and some are verified experimentally through the wide area communication. Identifying the areas of partial faults Prevents the whole winding failure prior to a massive destruction, which is costly especially for cases in inaccessible situations such as offshore wind towers.

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Fault Diagnosis of the Asynchronous Machines Through Magnetic Signature Analysis Using Finite-Element Method and Neural Networks

Cited by 49 publications

References 19 publications

Partial Inductance Model of Induction Machines for Fault Diagnosis

Partial Inductance Model of Induction Machines for Fault Diagnosis

Comprehensive design analysis of a 3D printed sensor for readiness assessment applications

Wide area condition monitoring of power electric drives in wind power generation system using radiated electromagnetic fields

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