Balancing optimization of a multiple speeds flexible rotor

Jianfei Yao, Fengyu Yang, Yongfei Su, Fabrizio Scarpa, Jinji Gao

Research output: Contribution to journalArticle (Academic Journal)peer-review

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The paper describes a method to perform the dynamic balancing of multiple speeds flexible rotors. The method is integrated with a dual-objective optimization method (DOM) to overcome the shortcomings that classical least squares influence coefficient method (LSM) may induce by generating excessive residual vibrations at specific rotor speeds when a flexible rotor is dynamically balanced. The technique here described involves two consecutive optimization steps. During the first step an optimal correction weight of the parameters population is identified by using a genetic algorithm(GA)applied to an objective function made from the sum of the squares of the residual vibrations. This first optimization step is performed multiple times to obtain a set of optimized correction weights. A second optimization process is then performed by minimizing the maximum value of the residual vibration of the rotor. Each correction weight belonging to the first optimization set is embedded into an equation that represents the residual vibration to obtain the final optimal correction weight. The validity of the proposed method is verified by simulations and experiments related to a double-disc rotor-bearing system. The results show the DOM provides a more effective balancing strategy than the one obtained from using GA and classical LSM.
Original languageEnglish
Article number115405
JournalJournal of Sound and Vibration
Early online date23 Apr 2020
Publication statusE-pub ahead of print - 23 Apr 2020


  • flexible rotor
  • rotor balancing
  • dual-objective optimization
  • genetic algorithm
  • least squares method


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