Dear Colleagues,

Currently, research carried out in the field of electric machines and motor drives includes measurements of various types of electrical, mechanical, electromagnetic and kinetic quantities. Basic tests of electric machines include measurements of voltages and currents, performed both during their start-up and in the range of normal operation.

From the point of view of diagnostic tests, it is important to correctly interpret the parameters and symptoms that can be obtained on the basis of the measured values related to electric machines and motor drives. This is possible only by using modern measurement signal processing procedures, often supported by artificial intelligence tools, e.g., genetic methods or neural networks. Quick and correct interpretation of the above parameters may contribute to the detection of the deepening damage to machines and, as a result, protect the user from costly failures that result in the necessity of a partial or comprehensive shutdown of technological processes.

In order to carry out measurements in the area of electric machines and motor drives, it is necessary to correctly apply individual measuring instruments, and, above all, complex measurement systems, most often controlled by dedicated control and measurement software, such as LabVIEW. Due to this, it is possible to quickly and effectively diagnose both single electrical machines and complex drive units used in various types of production lines. The correct application of the measuring equipment should be understood primarily as its selection in terms of the accuracy of the measurements carried out. In addition to hardware and software, it is also important to choose the method of performing measurements and the correct selection of personnel operating the measurement systems.

This Special Issue invites contributions on the topic of measurement systems intended for electric machines and motor drives. In particular, I encourage a wide group of scientists to present new solutions in the field of using computer-aided measurement systems to control the operation of electrical machines. The proposal of such solutions should include an analysis of the relevant measurement system in terms of the obtained measurement data. It will be necessary to indicate the current state of knowledge in the field of the proposed solution together with a detailed review of the relevant literature. It will also be desirable to validate the results, both experimental and simulated. An indication of the possibilities of practical applications of the proposed solutions and the possibility of their further development will be appreciated.

Prof. Dr. Krzysztof Kluszczyński
Prof. Dr. Krzysztof Tomczyk
Prof. Dr. Maciej Sułowicz
Dr. Marek Sieja
Guest Editors

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• artificial intelligence
• actuators
• computational algorithm
• control algorithm
• control system
• data analysis
• data acquisition
• decision algorithm
• devices for power systems
• digital signal processing
• distributed computing
• distributed system
• electric power quality
• electrical quantity
• electrical machines
• errors in power systems
• evolutionary algorithm
• fuzzy logic
• genetic algorithm
• measurement algorithm
• measurement system
• measurement system for unconventional electromechanical and mechatronic systems
• measurement technique
• measuring instrument
• mechatronic systems
• motor drives
• multi-degree systems
• nonelectrical quantity
• optimization of power systems
• precision measurement
• servo systems
• signal distortion
• signal reproduction
• special algorithms
• systems with SMART materials
• time-frequency analysis
• uncertainty analysis
• validation of computational algorithm
• wavelet analysis