Identification of unbalance characteristics of rotating machinery using a novel optimization-based methodology

• Published in: Soft computing (Berlin, Germany) Vol. 26; no. 10; pp. 4831 - 4862
• Main Authors: Abbasi, Ahmad, Firouzi, Behnam, Sendur, Polat, Ranjan, Gyan, Tiwari, Rajiv
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2022
• Subjects: Artificial Intelligence; Computational Intelligence; Control; Engineering; Mathematical Logic and Foundations; Mechatronics; Optimization; Robotics; SSA–NM; Rotational unbalance; Rotor-bearing systems; Optimization; Taguchi design; FEM
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-022-06872-9

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.