Cargando…

Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum

To solve the problem of nonlinear characteristics neglecting and fault mechanism analysis lacking in fault diagnosis research, a new method of fault mechanism analysis and diagnosis based on nonlinear spectrum is proposed. Firstly, based on the Permanent Magnet Synchronous Motor (PMSM) model of robo...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Lerui, Wen, Shengjun, Wang, Haiquan, Hu, Heyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626583/
https://www.ncbi.nlm.nih.gov/pubmed/36319639
http://dx.doi.org/10.1038/s41598-022-21691-6
_version_ 1784822767270494208
author Chen, Lerui
Wen, Shengjun
Wang, Haiquan
Hu, Heyu
author_facet Chen, Lerui
Wen, Shengjun
Wang, Haiquan
Hu, Heyu
author_sort Chen, Lerui
collection PubMed
description To solve the problem of nonlinear characteristics neglecting and fault mechanism analysis lacking in fault diagnosis research, a new method of fault mechanism analysis and diagnosis based on nonlinear spectrum is proposed. Firstly, based on the Permanent Magnet Synchronous Motor (PMSM) model of robot, the first 4-order spectrums based on nonlinear output frequency response function (NOFRF) in different states are obtained by batch calculation method. Secondly, the high-frequency spectrum distribution rule of NOFRF spectrum in different states are analyzed. Finally, in the closed-loop simulation environment of robot, the identification method based on data-driven is adopted for NOFRF spectrum calculation to verify power loss fault of PMSM. Meanwhile, the fault diagnosis experiment is also carried out. The experimental results indicate that the key characteristics distribution rule of NOFRF spectrums in the real environment is consistent with the theoretical analysis results, and compared with the traditional fault feature extraction methods by output signal, the diagnosis with fault feature of NOFRF spectrum for industrial robot closed-loop drive system has the highest accuracy, which verifies the validity of NOFRF spectrum as the fault feature.
format Online
Article
Text
id pubmed-9626583
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-96265832022-11-03 Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum Chen, Lerui Wen, Shengjun Wang, Haiquan Hu, Heyu Sci Rep Article To solve the problem of nonlinear characteristics neglecting and fault mechanism analysis lacking in fault diagnosis research, a new method of fault mechanism analysis and diagnosis based on nonlinear spectrum is proposed. Firstly, based on the Permanent Magnet Synchronous Motor (PMSM) model of robot, the first 4-order spectrums based on nonlinear output frequency response function (NOFRF) in different states are obtained by batch calculation method. Secondly, the high-frequency spectrum distribution rule of NOFRF spectrum in different states are analyzed. Finally, in the closed-loop simulation environment of robot, the identification method based on data-driven is adopted for NOFRF spectrum calculation to verify power loss fault of PMSM. Meanwhile, the fault diagnosis experiment is also carried out. The experimental results indicate that the key characteristics distribution rule of NOFRF spectrums in the real environment is consistent with the theoretical analysis results, and compared with the traditional fault feature extraction methods by output signal, the diagnosis with fault feature of NOFRF spectrum for industrial robot closed-loop drive system has the highest accuracy, which verifies the validity of NOFRF spectrum as the fault feature. Nature Publishing Group UK 2022-11-01 /pmc/articles/PMC9626583/ /pubmed/36319639 http://dx.doi.org/10.1038/s41598-022-21691-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Chen, Lerui
Wen, Shengjun
Wang, Haiquan
Hu, Heyu
Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title_full Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title_fullStr Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title_full_unstemmed Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title_short Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
title_sort fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9626583/
https://www.ncbi.nlm.nih.gov/pubmed/36319639
http://dx.doi.org/10.1038/s41598-022-21691-6
work_keys_str_mv AT chenlerui faultmechanismanalysisanddiagnosisforclosedloopdrivesystemofindustrialrobotbasedonnonlinearspectrum
AT wenshengjun faultmechanismanalysisanddiagnosisforclosedloopdrivesystemofindustrialrobotbasedonnonlinearspectrum
AT wanghaiquan faultmechanismanalysisanddiagnosisforclosedloopdrivesystemofindustrialrobotbasedonnonlinearspectrum
AT huheyu faultmechanismanalysisanddiagnosisforclosedloopdrivesystemofindustrialrobotbasedonnonlinearspectrum