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Volume 49 Issue 10
Oct.  2023
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Journal of Beijing University of Aeronautics and Astronautics  > 2023  >  49(10): 2807-2816.
WU Y T，LU Z，SONG H J，et al. Operation risk assessment of civil aircraft for multiple wear-out failure modes[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（10）：2807-2816 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0739
Citation: WU Y T，LU Z，SONG H J，et al. Operation risk assessment of civil aircraft for multiple wear-out failure modes[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（10）：2807-2816 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0739
shu

Operation risk assessment of civil aircraft for multiple wear-out failure modes

doi: 10.13700/j.bh.1001-5965.2021.0739
  • 1.

    College of Civil Aviation，Nanjing University of Aeronautics and Astronautics，Nanjing 211106，China

  • 2.

    Reliability Research Center，Chinese Flight Test Establishment，Xi’ an 710089，China

  • 3.

    Department of Aircraft Maintenance，China Eastern Airlines Jiangsu Ltd，Nanjing 211106，China

Funds:

National Natural Science Foundation of China (U1733124); Aeronautical Science Foundation of China(20180252002); Funds for Civil Aviation Safety Capacity Building (2021-196) 

More Information
  • Corresponding author: E-mail：luzhong@nuaa.edu.cn
  • Received Date: 07 Dec 2021
  • Accepted Date: 31 May 2022
    • Available Online: 31 Oct 2023
  • Publish Date: 23 Jun 2022
    Abstract

  • An operation risk assessment method is proposed for aircraft components with multiple wear-out failure modes. A multiple failure model is constructed using the fleet operating failure data samples and the mixed Weibull distribution. And the parameter estimation method of the mixed Weibull distribution is proposed based on the expectation maximization (EM) algorithm, which has been optimized by using the particle swarm optimization (PSO) algorithm to improve the accuracy of the parameter estimation. In terms of the mixed Weibull distribution-based reliability model, the calculating method for the number of defect airplanes (DA), which is caused by the multiple failure modes, is given via the Monte Carlo simulation method. To determine the Conditional Probability (CP) of dangerous consequences emerging from a certain initial situation, the Bayesian network (BN) is designed. Finally, the total uncorrected fleet risk (RT) is calculated in terms of the injury ratio (IR), the Not Detected probability (ND), the DA value, and the CP value. A case study shows that the proposed risk assessment method can be directly applied in the evaluation of fleet risks caused by multiple failure modes.Furthermore, the root mean squared error of the suggested parameter estimation approach has been decreased by 85.7% and 80.6%, respectively, when compared to the maximum likelihood estimation (MLE) and the least-squares estimation (LSE).

     

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