Identification of trends in process measurements using the wavelet transform

被引：33

作者：

Flehmig, F ^{[1
]}

Von Watzdorf, R ^{[1
]}

Marquardt, W ^{[1
]}

机构：

[1] RWTH Aachen, Lehrstuhl Prozesstech, D-52064 Aachen, Germany

来源：

COMPUTERS & CHEMICAL ENGINEERING | 1998年 / 22卷

关键词：

D O I：

10.1016/S0098-1354(98)00092-1

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In conjunction with model based techniques for plant operation, advanced concepts are required to derive higher value information from plant measurements. Frequently, the qualitative behavior of the plant is of interest rather than sequences of measured data of high sampling rate. In this paper anew, wavelet based approach is suggested to identify and localize polynomial trends in noisy measurements. Due to a hierarchical search in the time-frequency plane, the method is highly computational efficient. It yields both the least-squares polynomials for the identified intervals and a quantitative measure for their goodness of fit. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

引用

页码：S491 / S496

页数：6

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