Identification of unbalance characteristics of rotating machinery using a novel optimization-based methodology
In this study, a novel optimization-based method is proposed to determine the parameters of a rotating unbalance in a rotor-bearing system. For that purpose, the weighted sum of squared difference between the analytical and predicted unbalance response due to rotational unbalance is considered as th...
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| Published in | Soft computing (Berlin, Germany) Vol. 26; no. 10; pp. 4831 - 4862 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1432-7643 1433-7479 |
| DOI | 10.1007/s00500-022-06872-9 |
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| Abstract | In this study, a novel optimization-based method is proposed to determine the parameters of a rotating unbalance in a rotor-bearing system. For that purpose, the weighted sum of squared difference between the analytical and predicted unbalance response due to rotational unbalance is considered as the objective function. A hybrid algorithm integrating salp swarm algorithm and Nelder–Mead algorithms is presented for detecting unbalance magnitude and phase as the unbalance parameters. Parameters of the aforementioned optimization algorithm are determined systematically using the Taguchi design of experiments method. The efficiency of the proposed method is compared with various optimization algorithms in the literature. The optimization method is validated with different unbalances experimentally to consider the real-world conditions. The results show the superiority of the proposed hybrid algorithm in terms of the accuracy of the unbalance parameters and computational efficiency. |
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| AbstractList | In this study, a novel optimization-based method is proposed to determine the parameters of a rotating unbalance in a rotor-bearing system. For that purpose, the weighted sum of squared difference between the analytical and predicted unbalance response due to rotational unbalance is considered as the objective function. A hybrid algorithm integrating salp swarm algorithm and Nelder–Mead algorithms is presented for detecting unbalance magnitude and phase as the unbalance parameters. Parameters of the aforementioned optimization algorithm are determined systematically using the Taguchi design of experiments method. The efficiency of the proposed method is compared with various optimization algorithms in the literature. The optimization method is validated with different unbalances experimentally to consider the real-world conditions. The results show the superiority of the proposed hybrid algorithm in terms of the accuracy of the unbalance parameters and computational efficiency. |
| Author | Sendur, Polat Firouzi, Behnam Abbasi, Ahmad Ranjan, Gyan Tiwari, Rajiv |
| Author_xml | – sequence: 1 givenname: Ahmad orcidid: 0000-0002-1499-2413 surname: Abbasi fullname: Abbasi, Ahmad organization: Vibrations and Acoustics Laboratory (VAL), Mechanical Engineering Department, Ozyegin University – sequence: 2 givenname: Behnam orcidid: 0000-0002-6947-6600 surname: Firouzi fullname: Firouzi, Behnam organization: Vibrations and Acoustics Laboratory (VAL), Mechanical Engineering Department, Ozyegin University – sequence: 3 givenname: Polat orcidid: 0000-0003-2212-7419 surname: Sendur fullname: Sendur, Polat email: polat.sendur@ozyegin.edu.tr organization: Vibrations and Acoustics Laboratory (VAL), Mechanical Engineering Department, Ozyegin University – sequence: 4 givenname: Gyan surname: Ranjan fullname: Ranjan, Gyan organization: Department of Mechanical Engineering, Indian Institute of Technology Guwahati – sequence: 5 givenname: Rajiv orcidid: 0000-0003-2111-5918 surname: Tiwari fullname: Tiwari, Rajiv organization: Department of Mechanical Engineering, Indian Institute of Technology Guwahati |
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| Keywords | SSA–NM Rotational unbalance Rotor-bearing systems Optimization Taguchi design FEM |
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| Title | Identification of unbalance characteristics of rotating machinery using a novel optimization-based methodology |
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