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Sensors 2014, 14(9), 16715-16739; doi:10.3390/s140916715

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

1
Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Chaoyang District, Beijing 100124, China
2
School of Mechanical, Electrical and Control Engineering, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District, Beijing 100044, China
*
Authors to whom correspondence should be addressed.
Received: 21 April 2014 / Revised: 24 July 2014 / Accepted: 7 August 2014 / Published: 9 September 2014
(This article belongs to the Section Physical Sensors)

Abstract

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. View Full-Text
Keywords: composite dictionary single-atom matching; termination condition of iteration; fault diagnosis; modulation dictionary; sensor-based vibration signals composite dictionary single-atom matching; termination condition of iteration; fault diagnosis; modulation dictionary; sensor-based vibration signals
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Cui, L.; Wu, N.; Wang, W.; Kang, C. Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm. Sensors 2014, 14, 16715-16739.

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