文章基本信息

标题：Application of Signal Feature Extraction of Double Cavity Jaw Crusher Based on DEPSO
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作者：Mu, Fusheng ; Liu, Chao ; Li, Hui 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2013
卷号：8
期号：2
页码：448-454
DOI：10.4304/jcp.8.2.448-454
语种：English
出版社：Academy Publisher
摘要：The sparse decomposition of vibration signal is an important part of the fault diagnosis of Double Cavity Jaw Crusher. But calculation of sparse decomposition is very large, and it is difficult to fulfill signal processing. After analysing characteristics of Double Cavity Jaw Crusher, this paper proposes to apply the hybrid algorithm, DEPSO which mixes the advantages of particle swarm optimization (PSO) and difference evolution (DE) algorithm to extract signal feature of Double Cavity Jaw Crusher and deal with the search of the best atoms during the signal decomposition. With the combination of PSO and DE, this method avoids falling into the partial optimal solution. Besides, after the algorithm imports the chiasm and variation operations, its adaptability has made a great improvement. The test result shows that applying DEPSO to extracting signal feature of Double Cavity Jaw Crusher improves the search speed, the efficiency and accuracy of decomposition, and the calculation has also dropped down dramatically.
关键词：cavity jaw crusher;depso;matching pursuit;signal feature extraction