论文标题
停止木板压缩的时间检测：功能性时间序列方法
Stopping time detection of wood panel compression: A functional time series approach
论文作者
论文摘要
我们考虑确定在自动过程环境中木板胶水固化的最佳停止时间。使用近红外光谱技术来监视制造过程，可确保能源和时间的大量节省。我们从由72个光谱组成的近红外光谱探针中收集时间序列，旨在检测最佳的停止时间。我们提出了一个估计程序，以确定木板压缩的最佳停止时间以及与估计停止时间相关的估计不确定性。我们的方法首先将整个数据集划分为训练样本和测试样本，然后根据测试样本迭代计算集成平方的预测误差。然后，我们使用一个断点进行结构断裂检测方法，以确定综合平方预测误差的单变量时间序列的估计最佳停止时间。我们还通过一系列仿真研究研究了所提出方法的有限样本性能。
We consider determining the optimal stopping time for the glue curing of wood panels in an automatic process environment. Using the near-infrared spectroscopy technology to monitor the manufacturing process ensures substantial savings in energy and time. We collect a time series of curves from a near-infrared spectrum probe consisting of 72 spectra and aim to detect an optimal stopping time. We propose an estimation procedure to determine the optimal stopping time of wood panel compression and the estimation uncertainty associated with the estimated stopping time. Our method first divides the entire data set into a training sample and a testing sample, then iteratively computes integrated squared forecast errors based on the testing sample. We then apply a structural break detection method with one breakpoint to determine an estimated optimal stopping time from a univariate time series of the integrated squared forecast errors. We also investigate the finite-sample performance of the proposed method via a series of simulation studies.
