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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (4): 628321-628321.doi: 10.7527/S1000-6893.2023.28321

• Special Topic: Vibration Identification and Suppression Technology of Aeroengine • Previous Articles     Next Articles

Fan rotor local balancing method based on real data inversion

Lifang CHEN1,2, Yabing SUN1,2(), Shuhua ZHOU1,2, Qiang GAO3, Baodong QIAO3, Dong LI1,2   

  1. 1.Ministry of Education Key Laboratory of Engine Health Monitoring-Control and Networking,Beijing University of Chemical Technology,Beijing 100029,China
    2.State Key Laboratory of High-End Compressor and System Technology,Beijing University of Chemical Technology,Beijing 100029,China
    3.AECC Shenyang Engine Research Institute,Shenyang 110015,China
  • Received:2022-11-28 Revised:2023-02-13 Accepted:2023-03-06 Online:2024-02-25 Published:2023-03-10
  • Contact: Yabing SUN E-mail:syb19943210@163.com
  • Supported by:
    National Natural Science Foundation of China(51775030)

Abstract:

A fan rotor local balancing method based on the model and real dynamic balancing data inversion is proposed to address the phenomena of difficult fan rotor phase monitoring, complex vibration transmission paths, large variability of dynamic characteristics of different machines, and low dynamic balancing efficiency. The data inversion model is first constructed and the inversion characteristic parameters determined by decomposing the fan rotor vibration transmission path. The real dynamic balance data is then used to invert the performance to match the key characteristic parameter Kcs(casing to pivot point 1 dynamic stiffness) of each machine. Finally, the linear matrix equation of casing vibration response, characteristic parameter Kcsand rotor unbalance is established based on the inversion theory to realize the inverse operation of rotor unbalance. This method is verified by the field dynamic balancing of fan rotors, which can achieve 100% vibration suppression in the given speed range, and the vibration suppression ratio reaches 43%—68%, significantly improving the dynamic balancing efficiency.

Key words: aeroengine, fan rotor, local balance, data inversion, without OPR sensor

CLC Number: