Open AccessAutomated anomalies detection in the work of industrial robots
Author(s) -
A E Goncharov,
Aleksei Savelev,
Nikolay Krinitsyn,
S Mikhalevich
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1019/1/012095
Subject(s) - robot , industrial robot , industrial production , software , computer science , industrial equipment , position (finance) , control engineering , industrial engineering , artificial intelligence , engineering , finance , keynesian economics , economics , programming language
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.