Interface Development for Digital Twin of an Electric Motor Based on Empirical Performance Model

Rassõlkin, Anton; Rjabtšikov, Viktor; Kuts, Vladimir; Vaimann, Toomas; Kallaste, Ants; Partyshev, Andriy

doi:10.1109/access.2022.3148708

Cited by 22 publications

(9 citation statements)

References 20 publications

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“…Another trending technology is called digital twin (DT), which is the creating and sustaining of a digital representation of physical objects and supporting their performance through digital simulation and optimization tools that are continuously fed with real-time and updated data [71].…”

Section: Digital Twin-based Methodsmentioning

confidence: 99%

“…Normally, the digital twin architecture typically consists of five main components; the physical entity in the real world, the virtual entity, the services entity, the data, and the connections [71,72]. The virtual entity simulates the physical object from different approaches and provides multi-functions for the digital twin such as fault identification, optimization, simulation, and control strategies [72].…”

Section: Digital Twin-based Methodsmentioning

confidence: 99%

“…The DT term was used in the field of broken bar fault detection only in [74], but in a way represents a misconception of definitions in [71,72]. In [74], a 3-D finite element model was introduced to simulate a 5-hp motor.…”

Section: Digital Twin-based Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

2022

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Motors are the higher energy-conversion devices that consume around 40% of the global electrical generated energy. Induction motors are the most popular motor type due to their reliability, robustness, and low cost. Therefore, both condition monitoring and fault diagnosis of induction motor faults have motivated considerable research efforts. In this paper, a comprehensive review of the recent techniques proposed in the literature for broken bar faults detection and diagnosis is presented. This paper mainly investigates the fault detection methods in line-fed and inverter-fed motors proposed after 2015 and published in most relevant journals and conferences. The introduced review has deeply discussed the main features of the reported methods and compared them in many different aspects. Finally, the study has highlighted the main issues and the gaps that require more attention from researchers in this field.

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Section: Digital Twin-based Methodsmentioning

confidence: 99%

Section: Digital Twin-based Methodsmentioning

confidence: 99%

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Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

2022

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“…EMSs and energy conversion drives and devices are often integrated into DT-assisted systems as those employed in the areas mentioned in the last section. Moreover, energy conversion drives employment can be directly involved in different tasks utilizing the DT concept; see, e.g., [53][54][55][56][57][58]. Moreover, potential uses of the DT concept can be practiced in different fields involving EMSs and energy conversion such as, for example, wireless power transfer in electric vehicles [59,60] and actuation in image-guided therapeutics.…”

Section: Dt Concept and Emssmentioning

confidence: 99%

Coupled Models in Electromagnetic and Energy Conversion Systems from Smart Theories Paradigm to That of Complex Events: A Review

Razek

2022

Applied Sciences

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In this article, we evaluate the modeling of a real operation of a real system using the corresponding adequate theory. We show that the smart theories often used do not directly correspond to reality because these theories have been established in idealized frameworks. The need to adapt such frames to real landscape situations necessitates modifying the models used. This can be achieved by taking into account the different existing physical phenomena, which are normally overlooked in smart idealized models, in a revised coupled model. This contribution aims to analyze and illustrate the relationship between smart theories and coupled realistic models through a literature review. The strategy for constructing such models is discussed and highlighted. The understanding of this approach is illustrated by an application to the case of electromagnetic and energy conversion systems. In these systems, intelligent energy management, conversion and control involve the use of an accurate realistic coupled model in system design, optimization and control. It is a question of coupling and solving equations representing these systems by taking into account the real phenomena involved, which are electrical, magnetic, mechanical, thermal and material. The obvious advantage of using such realistic models in computer-aided design and optimization tools is illustrated. Moreover, the interest of using such models in the supervision of systems is assessed. These demonstrations are supported by a review of examples of work carried out in the field.

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“…The performance of digital twins in predicting the performance of machine tools was explored. In addition to this, digital twins have been widely used in some industrial production [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Research on Remaining Useful Life Prediction Method of Rolling Bearing Based on Digital Twin

Zhang

Zeng

et al. 2022

Entropy

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Bearing is a key part of rotating machinery. Accurate prediction of bearing life can avoid serious failures. To address the current problem of low accuracy and poor predictability of bearing life prediction, a bearing life prediction method based on digital twins is proposed. Firstly, the vibration signals of rolling bearings are collected, and the time-domain and frequency-domain features of the actual data set are extracted to construct the feature matrix. Then unsupervised classification and feature selection are carried out by improving the self-organizing feature mapping method. Using sensitive features to construct a twin dataset framework and using the integrated learning CatBoost method to supplement the missing data sets, a complete digital twin dataset is formed. Secondly, important information is extracted through macro and micro attention mechanisms to achieve weight amplification. The life prediction of rolling bearing is realized by using fusion features. Finally, the proposed method is verified by experiments. The experimental results show that this method can predict the bearing life with a limited amount of measured data, which is superior to other prediction methods and can provide a new idea for the health prediction and management of mechanical components.

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Interface Development for Digital Twin of an Electric Motor Based on Empirical Performance Model

Cited by 22 publications

References 20 publications

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art

Coupled Models in Electromagnetic and Energy Conversion Systems from Smart Theories Paradigm to That of Complex Events: A Review

Research on Remaining Useful Life Prediction Method of Rolling Bearing Based on Digital Twin

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