文章基本信息

标题：ENSEMBLE MODELING OF MILL LOAD BASED ON EMPIRICAL MODE DECOMPOSITION AND PARTIAL LEAST SQUARES
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作者：LIJIE ZHAO ; JIAN TANG ; WENGRONG ZHENG 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：45
期号：1
页码：179-191
出版社：Journal of Theoretical and Applied
摘要：Reliable measurements of ball mill load parameters and reorganization of the operating statuses are the key factors for saving energy and optimization control. Empirical mode decomposition (EMD) and partial least squares (PLS) are used to analyze shell vibration signal and monitor mill load parameters of ball mill. The shell vibration signal is decomposed into several intrinsic mode functions (IMFs) adaptively. The power spectral density (PSD) of each IMF is analyzed under different grinding conditions. A new index is defined to measure the relative change of each IMF to original signal, which is also used to select more informational IMFs. The ensemble PLS method is used to build soft-sensor models based on frequency spectrum of the selected IMFs. Experimental results show that ensemble soft-sensor model based on EMD and PLS can extract effective features of shell vibration signal and monitor mill load effectively.
关键词：Parameters Estimation; Vibration Signal Analysis; Empirical Mode Decomposition; Partial Least Squares; Ensemble Modeling