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Aircraft structure fatigue reliability degree Bayesian combination forecasting method

A technology for aircraft structure and combination prediction, which is applied in computer-aided design, special data processing applications, instruments, etc.

Inactive Publication Date: 2017-09-05
XIAMEN UNIV
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AI Technical Summary

Problems solved by technology

However, Bayesian combined forecasting methods are rarely used in engineering
[0003] Research on Fatigue Reliability Analysis of Aircraft Structure (FRAAS) (Yang J N, Trapp W J. Reliability analysis of aircraft structures under random loading and periodic inspection. AIAA journal, 1974, 12(12): 1623-1630.) Due to the existence of various uncertain factors, it is extremely difficult to predict the fatigue reliability of aircraft structures

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  • Aircraft structure fatigue reliability degree Bayesian combination forecasting method
  • Aircraft structure fatigue reliability degree Bayesian combination forecasting method
  • Aircraft structure fatigue reliability degree Bayesian combination forecasting method

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Embodiment Construction

[0090] In order to illustrate the technical characteristics of the present invention more clearly, the present invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings.

[0091] The invention provides a method for obtaining aircraft structure fatigue reliability information based on aircraft structure fatigue crack growth data. The accuracy is higher. The invention makes full use of the dynamic information of the fatigue crack growth of the aircraft structure. On the one hand, the fatigue reliability of the aircraft can be predicted more accurately through the model; The accuracy of aircraft fatigue reliability prediction is improved.

[0092] Such as figure 1 Shown is a kind of aircraft structure fatigue reliability Bayesian combination prediction method of the present invention, it comprises the following steps:

[0093] Step 1, data acquisition: acquire the historical data of fatigue crack growth of the ai...

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Abstract

The invention relates to an aircraft structure fatigue reliability degree Bayesian combination forecasting method, relating to combination forecasting. The method comprises the steps of data obtaining, modeling, model combination and reliability degree forecasting. By fully utilizing the advantage of Bayesian combination forecasting, the aircraft structure fatigue reliability degree information obtained by using the provided method is more accurate, and the accuracy is higher. Based on the Bayesian combination forecasting, a factor that the structure fatigue crack growth of an aircraft in the service stage is fully considered, the obtained aircraft structure fatigue crack growth data are utilized, and the result of the Bayesian combination forecasting is characterized by high accuracy and precision.

Description

technical field [0001] The invention relates to combination prediction, in particular to a Bayesian combination prediction method for aircraft structure fatigue reliability. Background technique [0002] The Combination of Forecasts (The Combination of Forecasts, CF) (J.M.Bates, C.W.J. Granger. The Combination of Forecasts. Journal of the Operational Research Society. December 1969, Volume 20, Issue 4, pp 451–468) was developed in 1969 by J.M.BatesC. and W.J. The two Grangers first proposed it in the Journal of the Operational Research Society. This method not only improves the prediction accuracy, but also fully considers the information expressed by the prediction samples. Bayesian Combined Forecasts (BCF) (In-Seok Park. Quantification of Multiple Types of Uncertaintyin Physics-Based Simulation. School of Graduate Studies, Wright State University, 2012) is a combined forecasting method that considers prior information , on the basis of making full use of prior information...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/15G06F2119/04
Inventor 袁修开刘文杰
Owner XIAMEN UNIV
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