Rotating Electrical Machines: Types, Applications and Recent Advances

The Rotating Electrical Machines (REMs) are classified into Motors and Generators. They powered the industrial, domestic and commercial loads. Because of their importance. This paper discussed different types of REMs, their applications and recent advances. REMs are applied in Teaching, Domestic, Mechatronics, Motorcycle, Three-wheelers, Electric Vehicle, Healthcare, Flywheel Energy Storage and Wind Energy Conversion Systems. It periscopes the advances of REMs in design, Fault diagnostic, control and condition monitoring. Its significance is to shed light on some advances made in REM

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

The Use of Scilab-Cloud for Teaching Digital Signal Processing Concepts in Electrical Engineering Curricula

The digital signal processing (DSP) is a relevant area in the electrical/computer engineering field, since several applications have been observed during the past decades. On the other hand, students have demonstrated difficulties to understand not only the eventual applications, but also its mathematical concepts and theory. Actually, open source packages are available and increasing, but the use of these tools are not very widespread in electrical engineering curriculum. This paper presents the use of Scilab-Cloud software platform for teaching some fundamentals of digital signal processing in undergraduate level, particularly for electrical engineering curriculum. Therefore, some experiments have carried out with undergraduate electrical engineering students and a questionnaire answered by them evidenced the potential of Scilab-Cloud as an interesting alternative tool to foster and motivate students for learning DSP skills

Virtual Reality Training Application for the Condition-Based Maintenance of Induction Motors

The incorporation of new technologies as training methods, such as virtual reality (VR), facilitates instruction when compared to traditional approaches, which have shown strong limitations in their ability to engage young students who have grown up in the smartphone culture of continuous entertainment. Moreover, not all educational centers or organizations are able to incorporate specialized labs or equipment for training and instruction. Using VR applications, it is possible to reproduce training programs with a high rate of similarity to real programs, filling the gap in traditional training. In addition, it reduces unnecessary investment and prevents economic losses, avoiding unnecessary damage to laboratory equipment. The contribution of this work focuses on the development of a VR-based teaching and training application for the condition-based maintenance of induction motors. The novelty of this research relies mainly on the use of natural interactions with the VR environment and the design’s optimization of the VR application in terms of the proposed teaching topics. The application is comprised of two training modules. The first module is focused on the main components of induction motors, the assembly of workbenches and familiarization with induction motor components. The second module employs motor current signature analysis (MCSA) to detect induction motor failures, such as broken rotor bars, misalignments, unbalances, and gradual wear on gear case teeth. Finally, the usability of this VR tool has been validated with both graduate and undergraduate students, assuring the suitability of this tool for: (1) learning basic knowledge and (2) training in practical skills related to the condition-based maintenance of induction motors.This research has been partially supported by Banco Santander under the scholarship program Santander Iberoamérica Research 2019/20. This investigation was partially supported by the ACIS project (Reference Number INVESTUN/21/BU/0002) of the Consejeria de Empleo of the Junta de Castilla y León (Spain)

The application of expert system:a review of research and applications

The development of Artificial Intelligent (AI) technology system can be a wide scope; for an instant, there are rule-based expert system, frame-based expert system, fuzzy logic, neural network, genetic algorithm, etc. The remarkable achievement applications of AI has been reported in different disciplines including field of medicals, militaries, chemistry, engineering, manufacturing, management, and others. Its' discoveries and contributions through of AI study since the early 1970s were be significant step to enhance better performance of human work activities and probably replaced by these technologies. Today, there a lot of intelligent machine is available in everywhere such as airport gate scanner, movie theater counter ticket, vending machine, ATM machine, washing machine, etc. Expert system has been used widely in many areas and industries. This paper is described the current research and development of expert system.</p