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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (22): 230297.doi: 10.7527/S1000-6893.2024.30297

• Solid Mechanics and Vehicle Conceptual Design • Previous Articles    

Heterogeneous data fusion and reliability analysis based on two-layer variable weights

Fan ZHANG1,2, Wei CONG3, Runcao TIAN4, Peng WANG1,2()   

  1. 1.Key Laboratory of Civil Aircraft Airworthiness Technology,Civil Aviation University of China,Tianjin  300300,China
    2.College of Electronic Information and Automation,Civil Aviation University of China,Tianjin  300300,China
    3.Science and Technology Innovation Research Institute,Civil Aviation University of China,Tianjin  300300,China
    4.College of Safety Science and Engineering,Civil Aviation University of China,Tianjin  300300,China
  • Received:2024-02-18 Revised:2024-04-07 Accepted:2024-05-07 Online:2024-11-25 Published:2024-05-14
  • Contact: Peng WANG E-mail:pwang@cauc.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2021YFB1600601);Graduate Research Innovation Project(2023YJSKC09014)

Abstract:

Continuous improvements in reliability of aerospace products make it difficult to collect large samples of failure data under normal test conditions, resulting in low accuracy of reliability analysis relying only on a single data source. In this regard, a heterogeneous data fusion and reliability analysis method considering two-layer variable weight is proposed. First, the standard deviation of the heterogeneous data measures its own reliability, and meanwhile, the support function based on the fuzzy area is introduced to measure the similarity between the heterogeneous data, so as to determine the fusion weights of the heterogeneous a priori data from two aspects. Further, a two-parameter Weibull distribution analysis model is established, the heterogeneous data fused using Bayes theory, and the reliability analysis of the target product finally conducted with the stepwise sampling method. The results show that the determination of fusion weights adopting two-layer variable weight analysis can effectively reduce the uncertainty existing in a single data source and improve the accuracy of reliability assessment, exhibiting important engineering application value.

Key words: heterogeneous data fusion, two-level variable weight analysis method, Bayes theory, two-parameter Weibull distribution, stepwise sampling method, reliability assessment

CLC Number: