Розробка штучної нейронної мережі для інформаційно-вимірювальної системи контролю геометричних розмірів енергетичного обладнання
The paper deals with the development of an artificial neural network for compensating for nonkinematic errors of an information and measurement system (IMS) based on a coordinate measuring arm (CMA). After compensating for kinematic errors using a mathematical model, the proposed back-propagation ne...
Збережено в:
| Дата: | 2025 |
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| Автори: | , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
General Energy Institute of the National Academy of Sciences of Ukraine
2025
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| Теми: | |
| Онлайн доступ: | https://systemre.org/index.php/journal/article/view/887 |
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| Назва журналу: | System Research in Energy |
Репозитарії
System Research in Energy| Резюме: | The paper deals with the development of an artificial neural network for compensating for nonkinematic errors of an information and measurement system (IMS) based on a coordinate measuring arm (CMA). After compensating for kinematic errors using a mathematical model, the proposed back-propagation neural network corrects non-kinematic errors arising from thermal deformations, noise, and element deformation inaccuracies. Experimental studies conducted on synthetic data demonstrated a significant reduction in the mean square error (MSE) of the coordinates of the measured points and a decrease in measurement uncertainty. The model exhibited high accuracy and stability, which confirms its effectiveness for controlling the geometric parameters of energy equipment. |
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