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Purpose <p>To mitigate the adverse effects of vibration response localization in mistuned blade-disk systems, this study aims to develop an efficient optimization and verification framework that improves blade arrangement through advanced algorithms and predictive modeling.</p> Methods <p>A lumped parameter model of a mistuned blade-disk system was established to analyze its vibration response under micro-mistuning conditions. Building upon blade desensitization and elite preservation strategies, an Elite Genetic Desensitization Vibration Reduction Optimization Algorithm (EGD-VROA) was proposed to optimize blade arrangements across various mistuning patterns. The performance of EGD-VROA was benchmarked against the Ant Colony Optimization (ACO) algorithm. To validate the optimization results and assess statistical reliability, an Adaptive Weight Particle Swarm Optimization–Artificial Neural Network (AWPSO-ANN) surrogate model was developed to perform Monte Carlo simulations on the blade-disk's dynamic responses.</p> Results and Conclusions <p>The EGD-VROA effectively suppressed vibration localization in mistuned blade-disk systems and achieved superior blade arrangements compared to the ACO algorithm. The proposed algorithm demonstrated faster convergence and greater robustness in optimization. Additionally, the AWPSO-ANN model significantly improved the efficiency of vibration response analysis while maintaining high prediction accuracy. Statistical analysis further confirmed the effectiveness of the proposed framework in reducing amplitude caused by mistuning. The integration of EGD-VROA and AWPSO-ANN offers a reliable and computationally efficient solution for vibration reduction and optimal blade arrangement, contributing valuable insights to the theoretical and engineering practices of aeroengine rotor system design.</p>

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Study on Localized Vibration and Vibration Reduction Optimization of Micro-mistuned Blade-disk

  • 期刊论文

  • 发表日期：

    2025年9月29日

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  • Hongyun Sun,
  • Hongyuan Zhang,
  • Xinqi Li,
  • Huiqun Yuan

摘要

Purpose

To mitigate the adverse effects of vibration response localization in mistuned blade-disk systems, this study aims to develop an efficient optimization and verification framework that improves blade arrangement through advanced algorithms and predictive modeling.

Methods

A lumped parameter model of a mistuned blade-disk system was established to analyze its vibration response under micro-mistuning conditions. Building upon blade desensitization and elite preservation strategies, an Elite Genetic Desensitization Vibration Reduction Optimization Algorithm (EGD-VROA) was proposed to optimize blade arrangements across various mistuning patterns. The performance of EGD-VROA was benchmarked against the Ant Colony Optimization (ACO) algorithm. To validate the optimization results and assess statistical reliability, an Adaptive Weight Particle Swarm Optimization–Artificial Neural Network (AWPSO-ANN) surrogate model was developed to perform Monte Carlo simulations on the blade-disk's dynamic responses.

Results and Conclusions

The EGD-VROA effectively suppressed vibration localization in mistuned blade-disk systems and achieved superior blade arrangements compared to the ACO algorithm. The proposed algorithm demonstrated faster convergence and greater robustness in optimization. Additionally, the AWPSO-ANN model significantly improved the efficiency of vibration response analysis while maintaining high prediction accuracy. Statistical analysis further confirmed the effectiveness of the proposed framework in reducing amplitude caused by mistuning. The integration of EGD-VROA and AWPSO-ANN offers a reliable and computationally efficient solution for vibration reduction and optimal blade arrangement, contributing valuable insights to the theoretical and engineering practices of aeroengine rotor system design.