Volume 8 Number 2 (Feb. 2013)
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JCP 2013 Vol.8(2): 448-454 ISSN: 1796-203X
doi: 10.4304/jcp.8.2.448-454

Application of Signal Feature Extraction of Double Cavity Jaw Crusher Based on DEPSO

Fusheng Mu, Chao Liu, Hui Li, Ling Deng, and Sheng Huang
College of Mechanical and Electrical Engineering, Central South University, Changsha, China

Abstract—The sparse decomposition of vibration signal is the important part of the fault diagnosis of Double Cavity Jaw Crusher. But the calculation count of sparse decomposition is very large, and it is difficult to fulfill signal processing. After analyzing characteristics of Double Cavity Jaw Crusher, this paper proposes applying the hybrid algorithm, DEPSO which mixed the characteristics of particle swarm optimization (PSO) and difference evolution (DE) algorithm to extracting signal feature of Double Cavity Jaw Crusher and using it to complete signal decomposition of the best atoms search. With the combination of PSO and DE, this method avoids falling into the partial optimal solution. Besides, after the algorithm import the chiasma or variation operations?, the adaptability of the algorithm has made a lot of improvement. The result shows that applying DEPSO to extracting signal feature of Double Cavity Jaw Crusher greatly improves the searching speed, efficiency and accuracy of decomposition, and the calculation has also dropped down dramatically.

Index Terms—Double Cavity Jaw Crusher, DEPSO, Matching pursuit, Signal feature extraction

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Cite: Fusheng Mu, Chao Liu, Hui Li, Ling Deng, and Sheng Huang, " Application of Signal Feature Extraction of Double Cavity Jaw Crusher Based on DEPSO," Journal of Computers vol. 8, no. 2, pp. 448-454, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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