噪声与振动控制2019，Vol.39Issue(5)：203-208,6.DOI:10.3969/j.issn.1006-1355.2019.05.038
罐笼偏载状态下滑动罐耳与罐道冲击模式识别
Impact Pattern Recognition between Sliding Tank Ear and Tank Track under Unbalanced Load State of the Cage
摘要
Abstract
Current fault diagnosis of the existing tank tracks only considers the balance state of the hoist, but ignores the unbalanced load of the hoist caused by the failure of the suspended cylinders in ultra-deep mine. In this paper, a recognition method for the impact pattern between sliding tank ear and tank under the normal, bulges and dislocation conditions of the cage guide is proposed under the unbalanced load of the hoist. With the energy entropy, singular value, standard deviation and waveform index of each frequency band after the wavelet packet decomposition of the lateral vibration signal of the hoist as the original feature set, and the irrelevant and redundant features removed by neighborhood rough set, the sensitive feature set is obtained, which is used for pattern recognition based on support vector machine optimized by cuckoo algorithm(CS). The experimental study shows that compared with genetic algorithm(GA), particle swarm optimization algorithm(PSO) and firefly algorithm(FA) optimization, the support vector machine optimized by cuckoo algorithm has higher classification accuracy (91.7 %) and shorter operation time, which is of great significance to ensure the safe operation of the lifting system.关键词
振动与波/罐笼/罐道/邻域粗糙集/布谷鸟搜索算法(CS)/支持向量机Key words
vibration and wave /hoist/cage guide/neighborhood rough set/cuckoo searching algorithm/SVM分类
信息技术与安全科学引用本文复制引用
陈昭君,谭建平,石理想,薛少华,黄天然..罐笼偏载状态下滑动罐耳与罐道冲击模式识别[J].噪声与振动控制,2019,39(5):203-208,6.基金项目
国家重点基础研究发展规划资助项目(973计划):(2014CB049400) （973计划）
