Registration Number
0224U031928,
(0123U104441)
, R & D reports
Title
Methods of measurement uncertainty research in intelligent information and measurement systems
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Методи досліджень невизначеності вимірювань в інтелектуальних інформаційно-вимірювальних системах
Head
Poliarus Olekcandr V., Доктор технічних наук
Registration Date
03-07-2024
Organization
Kharkiv National Automobile and Road University
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Assessment of measurement uncertainty in dynamic measurement information systems. Study of the accuracy of measuring the distance between two images in topological space for the recognition of ground landmarks during autonomous navigation of a mobile robot. Research on methods of optimizing the construction of intelligent pressure sensors.
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The object of research is measuring information systems and devices, their metrological characteristics, processes inherent in various methods of machine diagnostics.
The purpose of the work is to substantiate proposals for improvement, development and research of measuring information systems and devices, their metrological characteristics when working in the machine-building and road-building industries.
Research methods – mathematical modeling, methods of developing and evaluating strategies for the development of measurement information systems.
Chapter 1 shows the relevance of using autonomous navigation of mobile robots in complex environmental conditions. Such robots are able to independently solve navigation tasks in unfamiliar terrain, and any well-known territory can become unfamiliar after military operations, fires, accidents or the influence of abnormal natural factors.
Chapter 2 substantiates the limitations and assumptions when using methods for determining the dynamic characteristics of pressure measurement channels that are part of modern information and measurement systems.
Chapter 3 shows the advantages of using modern computer information technology with the use of artificial intelligence for execution
computing processes. It is emphasized that such intelligent systems based on artificial neural networks allow to successfully solve the problems of pattern recognition, forecasting, optimization, associative memory and control.
Chapter 4 discusses modern methods of optimizing the structural diagram of an intelligent pressure sensor. Requirements for optimization methods to ensure efficiency, reliability and accuracy are put forward.
Chapter 5 shows the problem of uncertainty assessment for certain industries and the solution of this issue in the works of scientists.
Product Description
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Ibrahimov Shakh H.
Koval Andrii O.
Koval Oleksandr A.
Medvedovska Yana S.
Petrukovych Dmytro Ye.
Serikova Iryna O.
Khomenko Yurii S.
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2024-07-03
