Application of approximate entropy in concrete structures damage identification

被引：3
作者：
Xie, Zhong-Kai [1 ]
Liu, Guo-Hua [1 ]
机构：
[1] Institute of Hydraulic Structures and Water Environment, Zhejiang University
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2013年 / 47卷 / 03期
关键词：
ApEn; Auto spectral density; Cross-correlation ApEn; Damage identification; Decay signal;
D O I：
10.3785/j.issn.1008-973X.2013.03.009
中图分类号：
学科分类号：
摘要：
Approximate entropy (ApEn) was introduced to detect damage in reinforced concrete beam structures based on free vibration signal. Decay signal was divided into various categories via auto spectral density function, and different ApEn methods were proposed according to different signal patterns. Cross-correlation function was applied to transform irregular decay signal into regular cross-correlation time series. The feasibility of introducing ApEn into calculating decay signal was validated by numerical simulation and experiment method. Tiny damage in concrete structures could be sensitively detected by applying cross-correlation ApEn method to free vibration signal tested from the experiment under various damage conditions. Various-intensity noise was added to the original tested signal, and the cross-correlation ApEn method was found to be able to recognize the damage under a very low signal-to-noise ratio condition, which confirms that the cross-correlation ApEn method has strong antinoise ability.
引用
收藏
页码：456 / 464
页数：8
相关论文
共 18 条
  • [1] Wang S.-X., Jiang Z., Present developing situation and research advances in the field of structural damage detection, Journal of Vibration and Shock, 23, 4, pp. 99-102, (2004)
  • [2] Zheng D.-L., Li Z.-F., Hua H.-X., A summary review of structural initial damage identification methods, Journal of Vibration and Shock, 21, 2, pp. 1-10, (2002)
  • [3] Zhang J.-F., Zhao D.-Y., Summary review of vibration-based crack diagnosis technique for engingeering structures, Journal of Vibration and Shock, 21, 4, pp. 22-26, (2002)
  • [4] Ma H.-W., Yang G.-T., Basic methods for damage detection based on structural vibration, Journal of Taiyuan University of Technology, 29, 4, pp. 513-527, (1999)
  • [5] Liu G.-H., Wu Z.-G., New thought on dynamic identification technology for damage detection of RC structures by introducing information entropy theory, Journal of Vibration and Shock, 30, 6, pp. 162-171, (2011)
  • [6] Pincus S.M., Approximate Entropy as a measure of system complexity, Proceedings of the National Academy of Sciences of the United States of America, 88, 6, pp. 2297-2301, (1991)
  • [7] Pincus S.M., Keefe D.L., Quantification of hormone pulsatility via an approximate entropy algorithm, American Journal of Physiology, 262, 5, (1992)
  • [8] Pincus S.M., Assessing serial irregularity and its Implications for health, Annals of the New York Academy of Sciences, 954, 1, pp. 245-267, (2001)
  • [9] Cancio L.C., Batchinsky A.I., Salinas J., Et al., Heart-rate complexity for prediction of prehospital lifesaving interventions in trauma patients, Journal of Trauma-Injury Infection & Critical Care, 65, 4, pp. 813-819, (2008)
  • [10] Ocak H., Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy, Expert Systems with Applications, 36, 2, pp. 2027-2036, (2009)
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