低频采样数据的恢复及模型辨识

Reconstruction of Low Sample-rate Data and Process Model Identification

在简单介绍小波变换基本原理的基础上，讨论了工业生产中经常遇到的低频采样数据的恢复及模型辨识问题，给出了有关假设成立条件的判定定理，并提出了一种基于离散小波变换的模型辨识算法——ＤＷＴＭＩ。理论分析、仿真研究及工厂实际数据的检验，表明了该算法的可行性和有效性。

The basic principles of Wavelet Transfor(WT) is introduced. Aimed to solved the reconstruction problem of low sampling rate data during the chemical process, an improved data reconstruction method used scaling function based on WT theory, which is called DWTMI, is presented. The reasonableness of the method is proved. Simulation results and real data test are given to illustrate that the method is effective and feasible in model identification.