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...
Autores principales: | , , , |
---|---|
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 |