数据驱动下孪生贝叶斯理论非齐次泊松过程的结构损伤评估方法
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国家自然科学基金资助项目(51805447);江苏省自然科学基金青年项目(BK20190911,BK20170418);中国博士后科学基金资助项目(2019M661947);江苏省农业自主创新资金资助项目(CX(20)3060)


Data driven structural damage assessment approach by the twin of Bayesian theory non-homogeneous Poisson process
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    摘要:

    以结构件裂纹扩展过程中的损伤状态评估为研究对象,提出了一种孪生贝叶斯理论非齐次泊松过程的结构损伤评估方法。首先,结合基于裂尖场能量的可靠度序化策略与非齐次泊松过程,运用贝叶斯理论对试验信息及总体过程参数的渐进关系进行组合,获得过程参数先验分布。同时,基于裂尖场能量递进因子与似然函数的概念,通过先验信息、序化策略及后验信息的组合,建立了孪生贝叶斯理论非齐次泊松过程的参数后验分布模型。最后以典型结构为例,结合声发射检测到的裂纹扩展数据对提出方法的可行性进行验证,并将预测结果与独立的试验结果进行比较。结果表明,提出方法的平均预测精度为92.1%,可以实现通过少量试验信息完成不同初始损伤状态下结构件损伤状态评估的目的。

    Abstract:

    A damage assessment approach for structure by twin Bayesian theory for non-homogeneous Poisson process is proposed,in which the damage for structure in the crack propagation is selected as the object. The prior parameter distribution for different damage situation is obtained by combine the reliability sequencing strategy based on crack tip field energy with the non-homogeneous Poisson model,and having an effective integration on the test information with the gradual relation by using Bayesian method. At the same time,the posterior distribution calculation approach based on Bayesian is achieved by using the prior information,based on the progressive factor of crack tip field energy and the likelihood function. Furthermore,the typical structure is selected as a case study. The evaluation results are compared with the test results. It can be clearly found from the results that the average accuracy of the proposed approach is 92.1%,and this approach can be used to complete the purpose of damage assessment by using a small amount of test information.

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朱林,陈敏,贾民平,冯月贵,庆光蔚.数据驱动下孪生贝叶斯理论非齐次泊松过程的结构损伤评估方法[J].振动工程学报,2021,34(1):134~140.[ZHU Lin, CHEN Min, JIA Min?ping, FENG Yue?gui, QING Guang?wei. Data driven structural damage assessment approach by the twin of Bayesian theory non-homogeneous Poisson process[J]. Journal of Vibration Engineering,2021,34(1):134~140.]

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  • 在线发布日期: 2022-05-12
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