中圖分類號(hào)： TP274
文獻(xiàn)標(biāo)識(shí)碼： A
DOI： 10.19358/j.issn.2096-5133.2022.02.008
引用格式： 郭儲(chǔ)磊. 基于差分進(jìn)化算法的PTA過(guò)程平均粒徑的動(dòng)態(tài)軟測(cè)量[J].信息技術(shù)與網(wǎng)絡(luò)安全，2022，41(2)：46-52.

Dynamic soft sensor of average particle size in PTA process based on differential evolution algorithm

Abstract： Aiming at the problem that the prediction accuracy of soft sensor model is not high due to the delay problem in industrial process, a dynamic soft sensor method using differential evolution algorithm to estimate the delay is proposed. The problem of time delay estimation of soft measurement system is transformed into a multi-dimensional nonlinear optimization problem by establishing a suitable fitness function by partial least square method, and then the global search ability of differential evolution algorithm is used to solve the optimization problem. Aiming at the modeling of PTA mean particle size in PTA refining process, the results show that the introduction of delay parameter estimation greatly improves the prediction accuracy of soft sensor model, and the validity and feasibility of the proposed method are verified.

Key words : soft sensor; differential evolution; time delay estimation; partial least squares