论文标题
在剩余终身估计中应用生成对抗网络的应用
On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation
论文作者
论文摘要
结构性健康监测（SHM）的一个主要问题是损害的预后和结构剩余使用寿命的定义。这两个任务都取决于许多参数，其中许多参数通常不确定。许多模型是针对上述任务开发的，但是它们是确定性的或随机的，只能考虑到结构的过去状态限制的能力。在当前的工作中，提出了一个生成模型，以预测结构的破坏演变。该模型能够在基于人群的SHM（PBSHM）框架中执行，以考虑到许多过去的结构状态，以在建模过程中纳入不确定性，并根据从结构中获得的数据产生潜在的损害进化结果。该算法在模拟的损伤演化示例上进行了测试，结果表明，它能够提供有关人群内结构剩余使用寿命的非常自信的预测。
A major problem of structural health monitoring (SHM) has been the prognosis of damage and the definition of the remaining useful life of a structure. Both tasks depend on many parameters, many of which are often uncertain. Many models have been developed for the aforementioned tasks but they have been either deterministic or stochastic with the ability to take into account only a restricted amount of past states of the structure. In the current work, a generative model is proposed in order to make predictions about the damage evolution of structures. The model is able to perform in a population-based SHM (PBSHM) framework, to take into account many past states of the damaged structure, to incorporate uncertainties in the modelling process and to generate potential damage evolution outcomes according to data acquired from a structure. The algorithm is tested on a simulated damage evolution example and the results reveal that it is able to provide quite confident predictions about the remaining useful life of structures within a population.
