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Author:

Cui, Lingli (Cui, Lingli.) (Scholars:崔玲丽) | Wang, Jing (Wang, Jing.) | Lee, Seungchul (Lee, Seungchul.)

Indexed by:

EI Scopus SCIE

Abstract:

The sparse decomposition based on matching pursuit is an adaptive sparse expression of the signals. An adaptive matching pursuit algorithm that uses an impulse dictionary is introduced in this article for rolling bearing vibration signal processing and fault diagnosis. First, a new dictionary model is established according to the characteristics and mechanism of rolling bearing faults. The new model incorporates the rotational speed of the bearing,, the dimensions of the bearing and the bearing fault status, among other parameters. The model can simulate the impulse experienced by the bearing at different bearing fault levels. A simulation experiment suggests that a new impulse dictionary used in a matching pursuit algorithm combined with a genetic algorithm has a more accurate effect on bearing fault diagnosis than using a traditional impulse dictionary. However, those two methods have some weak points, namely, poor stability, rapidity and controllability. Each key parameter in the dictionary model and its influence on the analysis results are systematically studied, and the impulse location is determined as the primary model parameter. The adaptive impulse dictionary is established by changing characteristic parameters progressively. The dictionary built by this method has a lower redundancy and a higher relevance between each dictionary atom and the analyzed vibration signal. The matching pursuit algorithm of an adaptive impulse dictionary is adopted to analyze the simulated signals. The results indicate that the characteristic fault components could be accurately extracted from the noisy simulation fault signals by this algorithm, and the result exhibited a higher efficiency in addition to an improved stability, rapidity and controllability when compared with a matching pursuit approach that was based on a genetic algorithm. We experimentally analyze the early-stage fault signals and composite fault signals of the bearing. The results further demonstrate the effectiveness and superiority of the matching pursuit algorithm that uses the adaptive impulse dictionary. Finally, this algorithm is applied to the analysis of engineering data, and good results are achieved. (C) 2014 Elsevier Ltd. All rights reserved.

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Author Community:

  • [ 1 ] [Cui, Lingli]Beijing Univ Technol, Key Lab Adv Mfg Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Wang, Jing]Beijing Univ Technol, Key Lab Adv Mfg Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Lee, Seungchul]Univ Michigan, Dept Mech Engn, Ann Arbor, MI 48109 USA

Reprint Author's Address:

  • 崔玲丽

    [Cui, Lingli]Beijing Univ Technol, Key Lab Adv Mfg Technol, Beijing 100124, Peoples R China

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Source :

JOURNAL OF SOUND AND VIBRATION

ISSN: 0022-460X

Year: 2014

Issue: 10

Volume: 333

Page: 2840-2862

4 . 7 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:176

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 161

SCOPUS Cited Count: 184

ESI Highly Cited Papers on the List: 12 Unfold All

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WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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