Algorithm Research & Explore
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41-44,72

Fault recognition algorithm for rolling bearings based on shift invariant dictionary learning and sparse coding

Qu Jianling1
Yu Lu1
Gao Feng1
Tian Yanping1
Li Yan2
1. Qingdao Branch of Naval Aviation University, Qingdao Shandong 266041, China
2. School of Automation, Northwestern Polytechnical University, Xi'an 710072, China

Abstract

According to current algorithms for rotating machines largely depending on expert prior knowledge, this paper proposed an adaptive fault recognition algorithm based on shift invariant dictionary learning and sparse coding. Firstly, it segmented and smoothed vibration signals to decrease the complexity. Then, it used shift invariant dictionary learning with adaptive penalty factor to learn shift invariant bases in different fault states. After that, it used an efficient sparse coefficient solver called feature sign search for reconstructing signal to be recognized. Lastly, residual was an evidence to determining fault state the signal belonging to. In the experiments of rolling bearing datasets and vibration signals of real aero-engine demonstrate its higher accuracy than up-to-date algorithms and feasibility for practical applications.

Foundation Support

国家自然科学基金资助项目(51505491)
航空科学基金资助项目(20165853040)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.07.0687
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 1
Section: Algorithm Research & Explore
Pages: 41-44,72
Serial Number: 1001-3695(2019)01-009-0041-04

Publish History

[2019-01-05] Printed Article

Cite This Article

曲建岭, 余路, 高峰, 等. 基于移不变字典学习和稀疏编码的滚动轴承故障识别算法 [J]. 计算机应用研究, 2019, 36 (1): 41-44,72. (Qu Jianling, Yu Lu, Gao Feng, et al. Fault recognition algorithm for rolling bearings based on shift invariant dictionary learning and sparse coding [J]. Application Research of Computers, 2019, 36 (1): 41-44,72. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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