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首页> 外文期刊>Journal of Nondestructive Evaluation >Condition Based Structural Health Monitoring and Prognosis of Composite Structures under Uniaxial and Biaxial Loading
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Condition Based Structural Health Monitoring and Prognosis of Composite Structures under Uniaxial and Biaxial Loading

机译:单轴和双轴载荷下基于状态的结构健康监测与复合结构预测

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摘要

This paper presents a condition based structural health monitoring (SHM) and prognosis approach to estimate the residual useful life (RUL) of composite specimens in real time. On-line damage states, which are estimated using real time sensing information, are fed to an off-line predictive model to update future damage states and RUL. The on-line damage index or damage state at any given fatigue cycle is estimated using correlation analysis. Based on the on-line information of the previous and current damage states, an off-line model is developed to predict the future damage state and estimate the RUL. The off-line model is a stochastic model which is developed based on the Gaussian process approach. In this paper, the condition based prognosis model is used to estimate the cumulative fatigue damage in composite test structures under constant amplitude fatigue loading. The proposed procedure is validated under uniaxial fatigue loading as well as biaxial fatigue loading. Experimental validations demonstrate that the prediction capability of the prognosis algorithm is effective in predicting the RUL under complex stress states.
机译:本文提出了一种基于状态的结构健康监测(SHM)和预后方法,可实时估算复合材料标本的剩余使用寿命(RUL)。使用实时感测信息估计的在线损坏状态被馈送到离线预测模型以更新未来的损​​坏状态和RUL。使用相关分析可以估算任何给定疲劳周期的在线损伤指数或损伤状态。基于先前和当前损坏状态的在线信息,开发了离线模型来预测未来的损坏状态并估计RUL。离线模型是基于高斯过程方法开发的随机模型。本文采用基于状态的预测模型来估计复合测试结构在恒定振幅疲劳载荷下的累积疲劳损伤。所提出的程序在单轴疲劳载荷和双轴疲劳载荷下均得到验证。实验验证表明,预后算法的预测能力可有效预测复杂应力状态下的RUL。

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