Data pre-processing for soft-sensor modeling in chemical process using wavelet transform

doi:10.3778/j.issn.1002-8331.2009.14.062

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (14): 201-203.DOI: 10.3778/j.issn.1002-8331.2009.14.062

• 工程与应用 • Previous Articles Next Articles

Data pre-processing for soft-sensor modeling in chemical process using wavelet transform

DOU Wei¹,ZHANG Shi¹,BO Cui-mei¹,JIANG Nan²

1.College of Automation，Nanjing University of Technology，Nanjing 210009，China
2.Xi’an Municiple Environmental Protection Research Institute，Xi’an 710054，China

Received:2008-03-17 Revised:2008-06-06 Online:2009-05-11 Published:2009-05-11
Contact: DOU Wei

小波变换的数据预处理在软测量建模中的应用

窦伟¹,张湜¹,薄翠梅¹,蒋楠²

1.南京工业大学自动化学院，南京 210009
2.西安市环境保护研究所，西安 710054

通讯作者: 窦伟

Abstract

Abstract: Data-driven soft-sensing is based on the large number of industrial data，so the data pre-processing is an important task for soft-sensing modeling.In this paper，a new method is used to process the gross error result in noise.That is a compromising algorithm between soft-threshold and hard-threshold of wavelet coefficient through adding a weight for threshold function.Simulation result and industrial application show that this method proposed is feasible and effective.

Key words: wavelet transform, soft-hard threshold, soft-sensing

摘要： 数据驱动的软测量建模的基础是大量可靠而准确的工业现场数据，因此数据预处理是软测量建模的重要任务。提出将小波系数软硬阈值折中方法应用于去除噪声干扰所产生的随机误差，即通过增加一个权值的应用，以综合软阈值和硬阈值两种方法的优点。仿真实验和工业实例应用证明了该方法的可行性和有效性。

关键词: 小波变换, 软硬阈值, 软测量

DOU Wei¹,ZHANG Shi¹,BO Cui-mei¹,JIANG Nan². Data pre-processing for soft-sensor modeling in chemical process using wavelet transform[J]. Computer Engineering and Applications, 2009, 45(14): 201-203.

窦伟¹,张湜¹,薄翠梅¹,蒋楠². 小波变换的数据预处理在软测量建模中的应用[J]. 计算机工程与应用, 2009, 45(14): 201-203.

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Data pre-processing for soft-sensor modeling in chemical process using wavelet transform

小波变换的数据预处理在软测量建模中的应用

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