(中南大學(xué) 信息科學(xué)與工程學(xué)院，長(zhǎng)沙 410083)
摘 要: 為了解決復(fù)雜工業(yè)生產(chǎn)過(guò)程多重時(shí)滯辨識(shí)難題，提出一種基于改進(jìn)互相關(guān)函數(shù)的多重時(shí)滯辨識(shí)方法。對(duì)于工業(yè)過(guò)程中多個(gè)受控制信號(hào)作用的過(guò)程變量，確定一個(gè)參考變量，分別考慮其他各變量和參考變量之間的相關(guān)性，選擇變量某個(gè)時(shí)間段內(nèi)的一組數(shù)據(jù)作為辨識(shí)對(duì)象，通過(guò)計(jì)算兩個(gè)變量的數(shù)據(jù)組在不同相對(duì)時(shí)間延遲對(duì)應(yīng)的互相關(guān)矩陣，比較互相關(guān)矩陣的奇異值，其最大奇異值對(duì)應(yīng)的滯后時(shí)間，即為所要辨識(shí)的時(shí)滯。將所提方法應(yīng)用于某鋁廠連續(xù)碳分過(guò)程多重時(shí)滯的辨識(shí)，基于工業(yè)現(xiàn)場(chǎng)采集的生產(chǎn)數(shù)據(jù)，分析變量間的關(guān)聯(lián)關(guān)系，辨識(shí)出多重時(shí)滯，然后將辨識(shí)所得的時(shí)滯代入碳分過(guò)程模型。結(jié)果表明：計(jì)算值和實(shí)測(cè)值的最大平均相對(duì)誤差僅為3.23%，驗(yàn)證了所提方法辨識(shí)多重時(shí)滯的有效性。
關(guān)鍵字: 互相關(guān)函數(shù)；多重時(shí)滯；辨識(shí)；碳分過(guò)程
process based on improved cross-correlation function
（School of Information Science and Engineering, Central South University, Changsha 410083, China）
Abstract:In order to resolve the problem of multi-delays identification for complex industrial process, an improved cross-correlation function was proposed. In all the process variables affected by control signals, the reference variable was selected by considering the correlation with the other variables respectively. For the considered variable, a set of data in a continuous time segment sampled was selected as identification object. The cross-correlation matrix for the data sets of the reference variable and the other variables was calculated. By comparing the singular values of cross-correlation matrix, the delay corresponding to the maximum singular value was the required delay. The proposed method was applied to identifying the multi-delays of alumina carbonation decomposition process using the field data. At last, the identified delays were substituted to alumina carbonation decomposition process model. The results show that the maximum average relative error between the calculated and tested results is only 3.23%, and the proposed multi-delays identification method based on improved cross-correlation function is effective.
Key words: cross-correlation function; multi-delays; identification; carbonation decomposition process
