Automated anomalies detection in the work of industrial robots; IOP Conference Series: Materials Science and Engineering; Vol. 1019 : 14th International Forum on Strategic Technology (IFOST 2019)

Библиографические подробности
Источник:IOP Conference Series: Materials Science and Engineering
Vol. 1019 : 14th International Forum on Strategic Technology (IFOST 2019).— 2021.— [012095, 6 p.]
Корпоративные авторы: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Научно-образовательный центр "Автоматизация и информационные технологии", Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Другие авторы: Goncharov A. S. Arkady Sergeevich, Savelyev A. O. Aleksey Olegovich, Krinitsyn N., Mikhalevich S. S. Sergey Sergeevich
Примечания:Title screen
This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyse this data to solve problems such as forecasting and modelling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator.
Язык:английский
Опубликовано: 2021
Предметы:
Online-ссылка:http://earchive.tpu.ru/handle/11683/64584
https://doi.org/10.1088/1757-899X/1019/1/012095
Формат: Электронный ресурс Статья
Запись в KOHA:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663606

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330 |a This article describes the results of the anomalies automated detection algorithm development in the operation of industrial robots. The development of robotic systems, in particular, industrial robots, and software for them is ahead of the tracking and managing technologies development. The operation of the digital production system involves the generation of a large amount of various data characterizing the state of both the specific equipment and the industrial system as a whole. Such a system produces a sufficient amount of data to develop machine learning models to analyse this data to solve problems such as forecasting and modelling. As part of the study, an experiment was conducted based on the equipment of the laboratory of industrial robots of Tomsk Polytechnic University. In the course of the research, the industrial manipulator moved loads belonging to different classes by weight. An algorithm was developed for the automated analysis of the values of the parameters of the consumed current and the position of the manipulator. 
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