Methods and Techniques of Signal Processing in Physical Measurements (eBook, PDF)

Redaktion: Hanus, Robert; Kreischer, Christian; Mazur, Damian

• Format: PDF

Produktbeschreibung

This book discusses selected issues of modern electrical metrology in the fields of sensor technology, signal processing and measurement systems, addressing theoretical problems and applications regarding measurements in electrical engineering, mechanics, telecommunications, medicine and geology, as well as in the aviation and transport industries.

It presents selected papers from the XXII International Seminar of Metrology "Methods and Techniques of Signal Processing in Physical Measurements" (MSM2018) held in Rzeszów-Arlamów, Poland on September 17-20, 2018. The conference was organized by the Rzeszow University of Technology, Department of Metrology and Diagnostic Systems (Poland) and Lviv Polytechnic National University, Department of Information Measuring Technology (Ukraine).

The book provides researchers and practitioners with insights into the state of the art in these areas, and also serves as a source of new ideas for further development and cooperation.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 424
• Erscheinungstermin: 7. Januar 2019
• Englisch
• ISBN-13: 9783030111878
• Artikelnr.: 54889466

Inhaltsangabe

Artur Andruszkiewicz, Kerstin Eckert - Measurements of Gas Phase Velocity in Liquid Metal by Means of Ultrasonic Pulse-echo Method.- Lukas Böhler, Mateusz Daniol, Anton Keller, Ryszard Sroka - Heat Resistant Monitoring and Tracking System for Medical Sterile Containers.- Mateusz Daniol, Lukas Böhler, Anton Keller, Ryszard Sroka - Autoclave Sterilization Powered Medical IoT Sensor Systems.- Bartosz Dominikowski, Krzysztof Pacholski, Piotr Wozniak - Using an Input Data Segregation Algorithm to Minimize the Error of the Fuzzy Controller in the Metrological Correction System of Electric Energy Meters.- Mykhaylo Dorozhovets, Ivanna Bubela, Anna Szlachta - Investigation of the Instrumental Components in Uncertainty of Extreme Random Observations.