Automated anomalies detection in the work of industrial robots

A. Goncharov, A. Savelev, N. Krinitsyn, S. Mikhalevich

Research output: Contribution to journalConference articlepeer-review

Abstract

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.

Original languageEnglish
Article number012095
JournalIOP Conference Series: Materials Science and Engineering
Volume1019
Issue number1
DOIs
Publication statusPublished - 20 Jan 2021
Event14th International Forum on Strategic Technology, IFOST 2019 - Tomsk, Russian Federation
Duration: 14 Oct 201917 Oct 2019

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)

Fingerprint Dive into the research topics of 'Automated anomalies detection in the work of industrial robots'. Together they form a unique fingerprint.

Cite this