Volume 23 Issue 5
Oct.  2023
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2023  >  23(5): 143-151
LI Yao-hua, ZHANG Cheng. Prediction of engine performance degradation based on adaptive change points[J]. Journal of Traffic and Transportation Engineering, 2023, 23(5): 143-151. doi: 10.19818/j.cnki.1671-1637.2023.05.009
Citation: LI Yao-hua, ZHANG Cheng. Prediction of engine performance degradation based on adaptive change points[J]. Journal of Traffic and Transportation Engineering, 2023, 23(5): 143-151. doi: 10.19818/j.cnki.1671-1637.2023.05.009
shu

Prediction of engine performance degradation based on adaptive change points

doi: 10.19818/j.cnki.1671-1637.2023.05.009

  • School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China

Funds:

National Natural Science Foundation of China U2033209

More Information
  • Author Bio:

    LI Yao-hua(1974-), male, professor, PhD, li_yaohua@sina.com

  • Received Date: 2023-04-07
    Available Online: 2023-11-17
  • Publish Date: 2023-10-25
    Abstract
  • To effectively utilize the monitoring big data to accurately identify the performance status and predict the performance degradation process of civil aircraft engines, a reliability evaluation model considering the uncertain degradation characteristics of civil aircraft engine performance parameters in different stages was proposed, so as to address the lack of fault data and the multi-stage degradation characteristics of civil aircraft engines during the performance degradation process. The change point detection model based on the Bayesian information criterion (BIC) was improved by the dynamic adaptive window width, and the adaptive change point was identified by the improved BIC with adaptive window width. Based on the identified adaptive change points, a distribution function model of the uncertain Liu process was established in stages. The reliability evaluation was conducted according to the mathematical properties of the first threshold of the performance degradation process of civil aircraft engines. In addition, the accuracy and superiority of the model were verified by comparing the sample data of performance degradation of civil aircraft engines. Analysis results indicate that the mean square error of degradation process in stages described by the change points is 5.8×10-28 after identifying the change points of performance degradation process of civil aircraft engines by using the BIC change point detection model with the improved adaptive window width. Under the conditions that the adaptive window width has different changing rules, the identified change points have no obvious change. Therefore, the model can accurately identify the adaptive change points of performance degradation process of civil aircraft engines and has strong robustness. When the uncertain Liu process in stages is used to analyze the dynamic degradation law of performance parameters of civil aircraft engines, the average evaluation error reduces by about 23.69% compared with the original Liu process model, and the reliability evaluation results are more accurate. Due to the Lipschitz continuity, the improved model can accurately predict the reliability level of performance degradation process of civil aircraft engines in a certain period of time in the future. It can be seen that the established improved reliability evaluation model can provide theoretical methods for the performance status monitoring and health management application of civil aircraft engines in practical engineering.

     

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