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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (5): 524196-524196.doi: 10.7527/S1000-6893.2020.24196

• Article • Previous Articles     Next Articles

Identification of foreign object impact on aero-engine fan blades with variance analysis

ZHANG Shuai, ZHANG Qiangbo, ZHANG Xiamei   

  1. Power-Plant Institute, Chinese Flight Test Establishment, Xi'an 710089, China
  • Received:2020-05-08 Revised:2020-06-08 Online:2021-05-15 Published:2020-06-24
  • Supported by:
    Joint Foundation of AVIC (6141B05110404)

Abstract: The impact detection and identification of foreign objects on aero-engine fans are essential to the flight safety of aircraft. To simulate the impact process of foreign objects on the real engine fan blade, an impact test platform was constructed, and the rule and recognition method of impact on fan blades were studied. Aiming at the problems of high difficulty and low accuracy in identifying the impact of foreign objects on the fan by the airborne parameters and added vibration parameters, we conducted an impact detection experiment of the foreign objects based on the vibration measurement of the non-contact fan blade tip, subsequently proposing an automatic threshold detection system of the foreign object impact on the fan based on the maximum likelihood estimation of the vibration displacement variance. The threshold values of vibration displacement variance identification of the rotor blade tip impacted by foreign objects at different speeds were obtained. The vibration displacement data of the impact of the projectile with a diameter of 16 mm and mass of 2.9 g on the fan blade at the speed of 3 000 r/min was analyzed, with the reliability of the identification result verified by the high-speed camera system. The result shows that the method based on the analysis of non-contact tip vibration displacement variance can accurately identify the impact event, impact location and the number of impact blades.

Key words: aero-engines, foreign object impact, non-contact blade tip vibration, variance analysis, parameter estimation

CLC Number: