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Method of Machining Centre Sliding System Fault Detection using Torque Signals and Autoencoder

Open Access
|Jul 2023

Abstract

The sliding system of machining centres often causes maintenance and process problems. Improper operation of the sliding system can result from wear of mechanical parts and drives faults. To detect the faulty operation of the sliding system, measurements of the torque of its servomotors can be used. Servomotor controllers can measure motor current, which can be used to calculate motor torque. For research purposes, the authors used a set of torque signals from the machining centre servomotors that were acquired over a long period. The signals were collected during a diagnostic test programmed in the machining centre controller and performed once per day. In this article, a method for detecting anomalies in torque signals was presented for the condition assessment of the machining centre sliding systems. During the research, an autoencoder was used to detect the anomaly, and the condition was assessed based on the value of the reconstruction error. The results indicate that the anomaly detection method using an autoencoder is an effective solution for detecting damage to the sliding system and can be easily used in a condition monitoring system.

DOI: https://doi.org/10.2478/ama-2023-0051 | Journal eISSN: 2300-5319 | Journal ISSN: 1898-4088
Language: English
Page range: 445 - 451
Submitted on: Dec 31, 2022
Accepted on: Apr 8, 2023
Published on: Jul 15, 2023
Published by: Bialystok University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2023 Damian Augustyn, Marek Fidali, published by Bialystok University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.