动态时间错位理论及应用研究

A Study on Dynamic Time Warping

将动态时间错位 (DTW)理论运用于分析和处理间歇反应过程中批次轨迹不同步问题 .在间歇反应过程中 ,由于批次与批次之间物理特性和约束的影响 ,批次轨迹常常具有持续时间不同步的特点 .如果要用统计的方法分析和比较 2个批次轨迹的数据特征 ,首先必须使 2个批次的持续时间长度保持一致 .动态时间错位 (DTW)理论可适时转换、扩张或压缩 2个批次轨迹的局部模式特征 ,取得 2轨迹之间的最短距离和最优同步路径 ,使 2批次轨迹实现同步化 .

Dynamic time warping (DTW) is a pattern matching method that can reconcile similar characteristics of two trajectories based on dynamic programming, this technique has been used in the area of speech recognition successfully. This paper discusses the application of dynamic time warping (DTW) to the analysis and disposal unsynchronized trajectories of batch processes. In batch process, due to the presence of batch batch disturbances and existence of physical constraints, batch processes often are characterized by unsynchronized trajectories. To compare these batch histories and apply statistical analysis, one needs to reconcile the timing difference among these histories first. Dynamic time warping (DTW) has the ability to synchronize two trajectories by appropriately translating, expanding, and contracting localized segments within both trajectories to achieve a minimum distance between the trajectories and optimal path, then synchronize two trajectories.