噪声与振动控制2018，Vol.38Issue(3)：146-151,6.DOI:10.3969/j.issn.1006-1355.2018.03.028
基于CEEMDAN和多尺度排列熵的球磨机负荷识别方法
Load Identification Method for Ball Mills based on CEEMDAN and Multi-scale Permutation Entropy
摘要
Abstract
It is difficult to extract the load characteristics and identify the loading condition for ball mills. To solve this problem, a ball mill load identification method based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and multi-scale permutation entropy is proposed. Firstly, the CEEMDAN is used to process the vibration signal of the ball mill and decompose it into a series of modal components, and the sensitive modal components with high correlation with the original signal are selected for signal reconstruction. Secondly, the optimal parameters for multi-scale permutation entropy algorithm are determined. Based on the algorithm, the permutation entropy of the reconstructed signal is obtained. Finally, the partial mean value of the multi-scale permutation entropy is calculated and the load state of the ball mill is identified with the partial mean value as the characteristic value. The experimental results show that this method can effectively identify the different load state of the ball mills and has a certain feasibility.关键词
振动与波/球磨机/CEEMDAN/多尺度排列熵/负荷识别Key words
vibration and wave/ball mill/CEEMDAN/multi-scale permutation entropy/load identification分类
数理科学引用本文复制引用
胡显能,蔡改贫,罗小燕,宗路..基于CEEMDAN和多尺度排列熵的球磨机负荷识别方法[J].噪声与振动控制,2018,38(3):146-151,6.基金项目
国家自然科学基金资助项目(51464017) （51464017）
江西省教育厅科技重点资助项目(GJJ150618) （GJJ150618）
