Characteristic Features of Rotor Bar Current Frequency Spectrum in Cage Induction Machine with Inner Faults

Sobczyk, Tadeusz; Tulicki, Jarosław; Weinreb, Konrad; Mielnik, Ryszard; Sułowicz, Maciej

doi:10.1109/demped.2019.8864907

Cited by 8 publications

(4 citation statements)

References 23 publications

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“…In addition, this can allow both spatial harmonic impacts and an alternating winding pattern when calculating machine parameters like magnetic flux density, inductances, and electromagnetic torque. Most IM shortcomings may be reconstituted by measuring the magnetic fields [24,25]. Faulty IM designs are typically created in 2D, which has the benefit of being quite precise concerning magnetic phenomena.…”

Section: Models Based On Finite Element Modeling (Fea)mentioning

confidence: 99%

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

Akbar,

Vaimann,

Asad

et al. 2023

Energies

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Electrical machines are prone to various faults and require constant monitoring to ensure safe and dependable functioning. A potential fault in electrical machinery results in unscheduled downtime, necessitating the prompt assessment of any abnormal circumstances in rotating electrical machines. This paper provides an in-depth analysis as well as the most recent trends in the application of condition monitoring and fault detection techniques in the disciplines of electrical machinery. It first investigates the evolution of traditional monitoring techniques, followed by signal-based techniques such as spectrum, vibration, and temperature analysis, and the most recent trends in its signal processing techniques for assessing faults. Then, it investigates and details the implementation and evolution of modern approaches that employ intelligence-based techniques such as neural networks and support vector machines. All these applicable and state-of-art techniques in condition monitoring and fault diagnosis aid in predictive maintenance and identification and have the highly reliable operation of a motor drive system. Furthermore, this paper focuses on the possible transformational impact of electrical machine condition monitoring by thoroughly analyzing each of the monitoring techniques, their corresponding pros and cons, their approaches, and their applicability. It offers strong and useful insights into proactive maintenance measures, improved operating efficiency, and specific recommendations for future applications in the field of diagnostics.

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Section: Models Based On Finite Element Modeling (Fea)mentioning

confidence: 99%

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

Akbar,

Vaimann,

Asad

et al. 2023

Energies

View full text Add to dashboard Cite

show abstract

“…Moreover, it allows to calculate the machine parameters such as the magnetic flux density, inductances and electromagnetic torque including spacial harmonic effects and split winding pattern. Therefore, mostly IM faults can be reproduced by the monitoring the magnetic fields [ 81 , 82 ]. Faulty IM models are usually developed in 2D, which has the advantage of being very accurate in terms of magnetic phenomena.…”

Section: Models Based On Femmentioning

confidence: 99%

A Review of Techniques Used for Induction Machine Fault Modelling

Terron-Santiago

Martínez-Román

Puche-Panadero

2021

Sensors

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Over the years, induction machines (IMs) have become key components in industry applications as mechanical power sources (working as motors) as well as electrical power sources (working as generators). Unexpected breakdowns in these components can lead to unscheduled down time and consequently to large economic losses. As breakdown of IMs for failure study is not economically feasible, several IM computer models under faulty conditions have been developed to investigate the characteristics of faulty machines and have allowed reducing the number of destructive tests. This paper provides a review of the available techniques for faulty IMs modelling. These models can be categorised as models based on electrical circuits, on magnetic circuits, models based on numerical methods and the recently proposed in the technical literature hybrid models or models based on finite element method (FEM) analytical techniques. A general description of each type of model is given with its main benefits and drawbacks in terms of accuracy, running times and ability to reproduce a given fault.

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“…Among IM machines, cage IMs are considered to be the most rugged and reliable ones, due to the robustness of the cage assembly. Nevertheless, in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, or in case of poorly manufactured cage windings [ 3 , 4 ], bars or end rings can have failures, due to high mechanical and thermal stresses of the rotor cage, especially during the start-up process of line fed IMs [ 5 , 6 ]. These faults must be detected as early and fast as possible, because they can produce heat damage to the rotor core, an increase of the current for a given load, and a reduction of the torque and efficiency [ 3 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach

Martínez-Román

Puche-Panadero

Sapena-Bañó

et al. 2021

Sensors

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Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segment breakages), especially in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, and in case of poorly manufactured cage windings. A continuous monitoring of IMs is needed to reduce this risk, integrated in plant-wide condition based maintenance (CBM) systems. Diverse diagnostic techniques have been proposed in the technical literature, either data-based, detecting fault-characteristic perturbations in the data collected from the IM, and model-based, observing the differences between the data collected from the actual IM and from its digital twin model. In both cases, fast and accurate IM models are needed to develop and optimize the fault diagnosis techniques. On the one hand, the finite elements approach can provide highly accurate models, but its computational cost and processing requirements are very high to be used in on-line fault diagnostic systems. On the other hand, analytical models can be much faster, but they can be very complex in case of highly asymmetrical machines, such as IMs with multiple cage faults. In this work, a new method is proposed for the analytical modelling of IMs with asymmetrical cage windings using a tensor based approach, which greatly reduces this complexity by applying routine tensor algebra to obtain the parameters of the faulty IM model from the healthy one. This winding tensor approach is explained theoretically and validated with the diagnosis of a commercial IM with multiple cage faults.

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Characteristic Features of Rotor Bar Current Frequency Spectrum in Cage Induction Machine with Inner Faults

Cited by 8 publications

References 23 publications

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

State-of-the-Art Techniques for Fault Diagnosis in Electrical Machines: Advancements and Future Directions

A Review of Techniques Used for Induction Machine Fault Modelling

Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach

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