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Civil aircraft mechanism global sensitivity analytical method based on random parameter-neural network

A neural network and random parameter technology, applied in neural learning methods, biological neural network models, random CAD, etc., can solve problems such as low system robustness

Inactive Publication Date: 2017-08-29
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0006] In order to avoid the deficiencies of the prior art, the present invention proposes a random parameter-neural network-based global sensitivity analysis method for civil aircraft mechanisms, and combines digital simulation techniques to carry out system robustness analysis of typical components of civil aircraft mechanisms to solve the problem of typical civil aircraft mechanisms. The problem of low system robustness of mechanism components under the traditional safety factor design criteria provides theoretical guidance for improving the robustness design of typical mechanism systems of aeronautical vehicles

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[0041] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0042] This embodiment mainly includes the following four steps:

[0043] (1) The size parameters of typical components of the slat mechanism are selected as the input parameters of the system. Based on the geometric dimensions and material properties of the component (as shown in Table 1), the wear amount of the component is calculated using the Archard wear formula (such as formula (4)), and the MSC. A multi-body dynamics simulation model of the slat system is established in figure 1 As shown, the sensitivity analysis is performed on the size parameters of typical components of the slat system, and the screening and removal sensitivity is less than 5×10 -3 parameters, the retention sensitivity is greater than or equal to 5×10 -3 The parameters of the system are used as sensitive input parameters of the system, hereinafter referred to as input parameters, so ...

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Abstract

The invention relates to a civil aircraft mechanism global sensitivity analytical method based on a random parameter-neural network. The technical purpose is to improve the system robustness of a slat mechanism of a civil aircraft. A performance degradation mechanism in which abrasion is adopted as a principal mode is considered, and global sensitivity analysis is conducted on typical parts of the slat mechanism. An artificial intelligent neural network technology is introduced, and through the combination of a random parameter method, a function relation of input parameters of the slat mechanism and output response is obtained, and through the global sensitivity analytical method, a global sensitivity index of the influence of input variables of the slat mechanism on system response is obtained.

Description

technical field [0001] The invention belongs to the technical field of system robustness analysis and structural optimization design, relates to a random parameter-neural network-based global sensitivity analysis method for civil aircraft mechanisms, and focuses on solving the problem of global sensitivity analysis of typical mechanism component systems in civil aircraft engineering design. Background technique [0002] The slat mechanism is an important lift-increasing device of a civil aircraft, and maintaining its normal operation is crucial to the safe flight of a civil aircraft. The shape camber delays the separation of the airflow to meet the demand for increased lift. According to the World Aviation Safety Information report, the number of passengers killed due to failures during takeoff, climb, approach, and landing accounted for 66.7% of all aircraft failure deaths, of which the number of aircraft failures caused by the wear and tear of the slat mechanism alone was ...

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Application Information

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IPC IPC(8): G06F17/50G06N3/08
CPCG06F30/15G06F30/20G06F2111/08G06F2111/20G06N3/084
Inventor 唐成虎周长聪魏鹏飞刘付超张政王文选张盼龙岳珠峰
Owner NORTHWESTERN POLYTECHNICAL UNIV
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