复杂工况下的纸浆Kappa值软测量方法

Soft Sensing Method for the Kappa Number of Pulp Under Complex Working Conditions

在纸浆Kappa值软测量技术的研究与应用中 ,发现直接基于经验模型的Kappa值软测量方法在复杂工况应用中预测精度有所下降 .针对这个问题 ,提出了首先利用Daubechies小波变换获得升温过程特征信息来进行工况分类 ,再进行分类模型预测的方法 .以某制浆车间的 130组样本数据为对象进行分析 。

During the research and application processes of the soft sensing technology for pulp Kappa number, the predicting precision decrease of the soft sensing method under complex conditions based directly on experiential models was observed. To overcome this problem, a new soft sensing method was introduced. In this method, the characteristic information of temperature-rising process extracted by Daubechies wavelet transform was used to classify the producing conditions, and a classified prediction model of Kappa number was then proposed. It is proved by the analysis of 130 sample data from a certain pulping workshop that,under complex working conditions and comparing with the results by the methods based directly on experiential models, better prediction results would be obtained by the proposed method.