Toomas Vaimann

Tallinn University of Technology | TTU · Department of Electrical Power Engineering and Mechatronics

The industrial revolution has opened up more paths with the integration of information technology with industrial applications. Similarly, most industrial processes can be streamlined by combining the Internet of Things (IoT) and artificial intelligence. Artificial intelligence has a significant role in this development, whether it is related to re...

This paper introduces a sophisticated approach for identifying and categorizing broken rotor bars in direct torque-controlled (DTC) induction motors. DTC is implemented in industrial drive systems as a suitable control method to preserve torque control performance, which sometimes shows its impact on fault-representing frequencies. This is because...

The detection of faults during an operational process constitutes a crucial objective within the framework of developing a control system to monitor the structure of industrial mechanisms. Even minor faults can give rise to significant consequences that require swift resolution. This research investigates the impact of overtension in the tooth belt...

Bearing failures in electrical machines pose significant challenges, attracting attention in diagnostic research. The widespread adoption of variable-speed drives across various motor applications has increased the effects of bearing currents, necessitating thorough exploration in both academic and industrial contexts. The paper contributes valuabl...

This study introduces an innovative approach to diagnostics, employing a unique combination of techniques including a stratified group K-fold cross-validation method and a sparse stacked autoencoder (SSAE) alongside LightGBM. By examining signatures derived from motor current, voltage, speed, and torque, the framework aims to effectively detect and...

Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This article provides an overview of types of servomotors and their basic principles and control method...

Bearing failures in electrical machines present significant challenges, drawing attention in diagnostic research. The widespread use of variable-speed drives in various motor applications has intensified the impact of bearing currents, requiring comprehensive exploration in academic and industrial settings. This paper thoroughly investigates the is...

A Battery Energy Storage System (BESS) plays an important role in achieving energy transition and climate change mitigation, with charging management applications being a crucial topic to improve the build, design, and operation of renewable technologies. With the continuous development of Artificial Intelligence (AI), implementing accurate algorit...

The various types of high-voltage instrument transformers (HVITs) play a highly significant role in the power system. They are necessary for routine operations such as control and monitoring, protection, and metering. However, HVITs remain vulnerable to defects due to high voltage or current based electric, magnetic, and thermal stresses. The defec...

The Internet of Things has emerged as one of the most important components for fault diagnostics in industrial applications. The emergence of the digital twin has further enhanced the capability to develop and implement industrial applications more easily to simulate industrial environments. This article describes an alternate method to generate da...

The reliable operation of power transmission networks depends on the timely detection and localization of faults. Fault classification and localization in electricity transmission networks can be challenging because of the complicated and dynamic nature of the system. In recent years, a variety of machine learning (ML) and deep learning algorithms...

This article explores the transformative potential of digital twin (DT) technology in the automotive sector, focusing on its applications in enhancing propulsion drive systems. DT technology, a virtual representation of physical objects, has gained momentum due to its real-time monitoring and analysis capabilities. Within the automotive industry, w...

Keywords: Electrical power systems, Support vector machines, Random Forest, Machine learning, Wavelet transform, Transmission lines fault, Electrical power quality, Short circuit, Classification of faults, Localization of faults, Decision trees, Ensemble learning, K-nearest neighbors.

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 t...

Citation: Ibrahim, M.; Rassõlkin, A.; Vaimann, T.; Kallaste, A.; Zakis, J.; Hyunh, V.K.; Pomarnacki, R. Digital Twin as a Virtual Sensor for Wind Turbine Applications. Energies 2023, 16, 6246. https://doi.org/10.3390/ en16176246 Academic Editors: Dan-Cristian Popa and Emil Cazacu Abstract: Digital twins (DTs) have been implemented in various applic...

The increasing demand for intelligent machines, coupled with the drive for the more efficient utilization of these machines in various industries, and the emergence of Industry 4 [...]

Due to their efficiency and control capabilities, induction motors fed with inverters have become prevalent in various industrial applications. However, ensuring the reliable operation of the motor and diagnosing faults on time are crucial for preventing unexpected failures and minimizing downtime. This paper systematically analyzes condition monit...

Abstract This research work implements an initial methodology for the assessment of Battery Energy Storage Systems (BESSs) based on Remaining Useful Lifetime (RUL), and its main contribution is the modeling and estimation of Health and Charge indicators through regression algorithms and binary classifiers during the battery’s operation. Linear Regr...

The aim of the presented investigation is to explore the time gap between an anomaly appearance in continuously measured parameters of the device and a failure, related to the end of the remaining resource of the device-critical component. In this investigation, we propose a recurrent neural network to model the time series of the parameters of the...

The paper aims at methods for compliance testing of power-generating modules (PGMs) or their components. The methods discussion include power-hardware-in-loop (PHIL), controller-hardware-in-loop and novel simulated input PHIL (SI-PHIL) techniques. The advantages and disadvantages of the test techniques and their feasibility for laboratory or field...

Additive manufacturing (AM) or 3D printing has opened up new opportunities for researchers in the field of electrical machines, as it allows for more flexibility in design and faster prototyping, which can lead to more efficient and cost-effective production. An overview of the primary AM techniques utilized for designing electrical machines is pre...

Citation: Asad, B.; Raja, H.A.; Vaimann, T.; Kallaste, A.; Pomarnacki, R.; Hyunh, V.K. A Current Spectrum-Based Algorithm for Fault Detection of Electrical Machines Using Low-Power Data Acquisition Devices. Electronics 2023, 12, 1746. https://doi.org/10.3390/ electronics12071746 Academic Editors: Ryad Zemouri, Mélanie Lévesque and Arezki Merkhouf A...

Abstract The demand for energy is a relevant topic in the field of science and engineering, which has been discussed throughout the last years due to the challenges of climate change and environmental concerns around the world. Currently, electric vehicles (EVs) offer a source of mobility that emphasises the use of energy storage devices to reduce...

For several decades, the design and manufacture of electrical machines has been considered a technically mature area and, as a result, research and development in the area has been extremely limited, even though this is a crucial technology in the application of electrical energy. Electrical machines are used in over 80% of the world’s energy conve...

Electrical machines are prone to faults and failures and demand incessant monitoring for their confined and reliable operations. A failure in electrical machines may cause unexpected interruptions and require a timely inspection of abnormal conditions in rotating electric machines. This article aims to summarize an up-to-date overview of all types...

Industrial revolution 4.0 has enabled the advent of new technological advancements, including the introduction of information technology with physical devices. The implementation of information technology in industrial applications has helped streamline industrial processes and make them more cost-efficient. This combination of information technolo...

This paper presents a practical thermal model of a synchronous generator for high-power applications. This model couples the lumped parameter thermal network and coolant network together to utilize the impact of the coolant’s temperature rising over the machine. Furthermore, the advanced multi-planes technique provides a more precise and higher res...

The hairpin winding configuration has been attracting attention as a solution to increase the power density of electric vehicle motors by enhancing the slot-filling factor. However, this winding configuration brings high AC losses during high-speed operation and we require new approaches to tackle this challenge. This paper considers reducing AC lo...

In the electric automotive industry, manufacturers usually do not declare the electrical parameters of electric vehicle (EV) motors. In advanced control systems, accurate knowledge of motor parameters is essential in order to achieve high dynamic performance. Conventional tests for parameter estimation might be risky not only to the motor windings...

Internet of Things (IoT) has become the need of the hour with the recent advancement in technology. The emergence of new technologies has helped to communicate between different machines and it has become easier to interact with them. This has helped with the reduction of maintenance costs and the time needed to fix the machine. Furthermore, it is...

Cartesian robot is a complex industrial robot, which is designed to work in hard and dangerous human conditions. This kind of robot has some control modes that help transform it for different tasks, such as movement details, 3D-printing, accuracy cutting processes, and others. Hirata cartesian robot is chosen for research in the paper. Additional v...

In order to define the best design structure of the synchronous reluctance motor (SynRM) rotor, optimization must be carried out, implying the selection of the best alternative for each specific criterion. The optimization of an electrical machine is a complicated work involving meeting different criteria requirements while dealing with a range of...

Nowadays, electrical machines and drive systems are used in numerous domestic and industrial applications. Due to this fact, unexpected failures can lead to fatal consequences and are to be prevented. As the world is moving towards Industry 4.0 standards, sophisticated technologies and timely fault detection are becoming more popular. Using cloud c...

Cartesian robots framework is a complex mechanical structure that consists of gearboxes, joints, and moving parts. The main problem with this structure is the impossibility to monitor any faults in mechanical parts that have occurred during work operations. An example of such a system, the Hirata cartesian robot, is described in the paper. The faul...

Electrical machines play an essential role in numerous industrial applications. Modern energy systems, including wind turbines or electric vehicles, are prone to damage and failures. In those devices, unexpected failures often mean economic loss, environmental problems, and danger to human life in the worst case. For developing a system that is abl...

Nowadays, most domestic and industrial fields are moving toward Industry 4.0 standards and integration with information technology. To decrease shutdown costs and minimize downtime, manufacturers switch their production to predictive maintenance. Algorithms based on machine learning can be used to make predictions and detect timely potential faults...

Nowadays, electrical machines are used in various applications and industrial branches, where unexpected damages are undesired and to be prevented. The world is moving towards Industry 4.0 standards, and sophisticated technologies are becoming more customary. Big data of machines’ working conditions can be stored remotely using cloud computation. T...