2093. A wavelet thresholding method for vibration signals denoising of high-piled wharf structure based on a modified artificial bee colony algorithm

Xun Zhang1, Juelong Li2, Jianchun Xing3, Ping Wang4, Liqiang Xie5

1, 2, 3, 4, 5College of Defense Engineering, PLA University of Science and Technology,
Nanjing 210007, China

2Research Center of Coastal Defense Engineering, Beijing 100841, China

2Corresponding author

E-mail: 1xunzhang893@163.com, 2lijuelong@126.com, 3xjc@893.com.cn, 4wp893@sina.com, 5xielq@outlook.com

Received 23 March 2016; received in revised form 26 June 2016; accepted 30 June 2016

DOI https://doi.org/10.21595/jve.2016.17005

Abstract. Vibration monitoring signals are widely used for damage alarming among the structural health monitoring system. However, these signals are easily corrupted by the environmental noise in the collecting that hampers the accuracy and reliability of measured results. In this paper, a modified artificial bee colony (MABC) algorithm-based wavelet thresholding method has been proposed for noise reduction in the real measured vibration signals. Kent chaotic map and general opposition-based learning strategies are firstly adopted to initialize the colony. Tournament selection mechanism is then employed to choose the food source. Finally, the Kent chaotic search is applied to exploit the global optimum solution according to the current optimal value. Moreover, a generalized cross validation (GCV) based fitness function is constructed without requiring foreknowledge of the noise-free signals. A physical model experiment for a high‑piled wharf structure is implemented to verify the feasibility of the proposed signal denoising approach. Particle swarm optimization (PSO) algorithm, basic artificial bee colony (BABC) algorithm and Logistic chaos artificial bee colony (LABC) algorithm and are also taken as contrast tests. Comparison results demonstrate that the proposed algorithm outperforms the other algorithms in terms of convergence speed and precision, and can effectively reduce the noise from the measured vibration signals of the high-piled wharf structure.

Keywords: high-piled wharf, vibration signal, wavelet thresholding denoising, artificial bee colony algorithm.


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Cite this article

Zhang Xun, Li Juelong, Xing Jianchun, Wang Ping, Xie Liqiang A wavelet thresholding method for vibration signals denoising of high‑piled wharf structure based on a modified artificial bee colony algorithm. Journal of Vibroengineering, Vol. 18, Issue 5, 2016, p. 2899‑2915.


JVE International Ltd. Journal of Vibroengineering. Aug 2016, Vol. 18, Issue 5. ISSN 1392-8716