基于波浪激励响应自适应变分模态分解的高桩码头桩基损伤识别

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (21) : 147-155.

论文

基于波浪激励响应自适应变分模态分解的高桩码头桩基损伤识别

王泊淳1，王启明1,2，朱瑞虎2,3，李成明1

作者信息 +

Damage identification of high-piled wharf pile foundation based on IAVMD under wave excitation

WANG Bochun1, WANG Qiming1,2, ZHU Ruihu2,3, LI Chengming1

Author information +

文章历史 +

摘要

波浪激励下高桩码头桩基动力响应存在多类型信号混杂现象，因此信号重构对于码头桩基的损伤检测至关重要。变分模态分解(Variational Mode Decomposition，VMD)方法能够有效避免信号重构中的模态混叠问题，但由于波浪激励下的动力响应频谱复杂，分解所需的模态数和罚因子会严重影响分解结果。为解决该问题，提出了一种自适应变分模态分解方法(Improved Adaptive Variational Mode Decomposition，IAVMD)，该方法通过罚权系数自适应调整各频率分量的罚因子，并通过分解结果的信号完整度来确定最佳模态数。进一步通过波浪激励下的高桩码头模型试验对IAVMD的有效性、适用性进行了验证。结果表明，该方法能够准确分离出动力响应损伤特征子信号，并根据能量因子确定损伤位置和大小。

Abstract

There is multi-type aliasing phenomenon in the dynamic response of pile foundation of high-piled wharf under wave excitation, signal reconstruction is crucial for the damage detection. Variational Mode Decomposition method can effectively avoid the problem of mode aliasing, but because the dynamic response’s spectrum is complex, the number of modes and penalty factors can seriously affect the decomposition results. To solve this problem, an Improved Adaptive Variational Mode Decomposition method is proposed, in which the penalty factor of each frequency component is adjusted adaptively with the penalty weight coefficient, and the optimal mode number is determined using the signal integrity of the decomposition result. Furthermore, the validity and applicability of IAVMD are verified through the model test of high-piled wharf under wave excitation. The results show that, IAVMD can accurately separate the damage characteristic signals and determine the location and size of the damage according to the energy factor.

导出引用

王泊淳1, 王启明1, 2, 朱瑞虎2, 3, 李成明1. 基于波浪激励响应自适应变分模态分解的高桩码头桩基损伤识别[J]. 振动与冲击, 2024, 43(21): 147-155

WANG Bochun1, WANG Qiming1, 2, ZHU Ruihu2, 3, LI Chengming1. Damage identification of high-piled wharf pile foundation based on IAVMD under wave excitation[J]. Journal of Vibration and Shock, 2024, 43(21): 147-155

参考文献

[1] 刘利琴,陈建峰,罗超等.高桩码头在船舶撞击下的动力响应及损伤分析[J].哈尔滨工程大学学报,2023,44(04):519-526.
Liu Liqin, Chen Jianfeng, Luo Chao et al. Dynamic response and damage analysis of high pile wharf under ship impact [J]. Journal of Harbin Engineering University, 2023,44(04): 519-526.
[2] WANG Q, ZHU R, ZHENG J, et al. A Method for the Damage Detection of Pile Foundation in High-Pile Wharf Based on A Curvature Mode Deletion Model[J]. China Ocean Engineering, 2020,34(06):871-880.
[3] 王启明,朱瑞虎,王宁,等.基于波浪激励下动力响应统计矩的高桩码头桩基损伤识别[C].第二十届中国海洋（岸）工程学术讨论会论文集（下）, 2022:247-255.
Wang Qiming, Zhu Ruihu, Wang Ning, et al. Damage identification of pile foundation of high pile pier based on statistical moment of dynamic response under wave excitation [C]. Proceedings of the 20th China Ocean (Coastal) Engineering Symposium (II), 2022-247-255.
[4] 朱瑞虎,王宁,王启明,等.基于模态应变能的高桩码头桩基损伤识别研究[J].水道港口, 2021,042(004):504-509, 537.
ZHU Ruihu, WANG Ning, WANG Qiming, et al. Rsearch on damage identification of pile foundation of high pile wharf
based on modal strain energy [J]. Journal of Waterway and
Harbor, 2021, 42(04): 504-509.
[5] 张汝学,郑永来,韩雨莘,等.基于模态柔度的高桩码头损伤识别方法研究[J].施工技术(中英文), 2023,52(21):26-32.
Zhang Ruxue, Zheng Yonglai, Han Yucai, et al. Study on damage identification method of high-piled wharf based on modal flexibility [J].Construction Technology (Chinese and English), 2023,52(21):26-32.
[6]刘金梅,周国强,韩国有,等.波浪作用下海洋石油井架模态参数识别与承载力评价[J]. 海洋工程, 2009,27(01):22-27.
Liu Jinmei, Zhou Guoqiang, Korea You, et al. Modal parameter identification and bearing capacity evaluation of offshore oil derrick under wave action [J]. Ocean Engineering, 2009,27(01):22-27.
[7] 嵇春艳,陈明璐,元志明,等.海洋平台结构损伤识别与定位新方法及试验验证[J].海洋工程, 2010,28(04):9-17.
Ji Chunyan, Chen Minglu, Yuan Zhiming, et al. A new method for structural damage identification and location of offshore platforms and its experimental verification [J]. Ocean Engineering, 2010,28(04):9-17.
[8] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings Mathematical Physical & Engineering Sciences, 1998,454(1971):903-995.
[9] Wu Z, Huang N E. A study of the characteristics of white noise using the empirical mode decomposition method[J]. Proceedings Mathematical Physical & Engineering Sciences, 2004,460(2046):1597-1611.
[10] Mousavi A A, Zhang C, Masri S F, et al. Structural damage detection method based on the complete ensemble empirical mode decomposition with adaptive noise: a model steel truss bridge case study:[J]. Structural Health Monitoring, 2022,21(3):887-912.
[11] Hu Y, Wang Q, Zhu R, et al. Online robustness damage identification of dynamic response of high pile wharf under wave excitation[J]. Ocean Engineering, 2023,273:113950.
[12]朱俊杰,张清华,朱冠华,等.基于EEMD和CNN-SVM的滚动轴承故障诊断[EB/OL].[2023-12-05](2024-04-11).https://link.cnki.net/urlid/44.1259.TH.20231204.1614.006.
[13]Li C, Wang Q, Zhu R, et al. Damage identification for pile foundation in high-piled wharf using composite energy factors driven by dynamic response under wave impact excitation[J]. Ocean Engineering, 2024, 291: 116286.
[14] Dragomiretskiy K, Zosso D. Variational Mode Decomposition [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014,62(3):531-544.
[15] Xie D, Sun H, Qi J. A New Feature Extraction Method Based on Improved Variational Mode Decomposition, Normalized Maximal Information Coefficient and Permutation Entropy for Ship-Radiated Noise[J]. Entropy (Basel, Switzerland), 2020,22(6):620.
[16] Huokun L, Gang W, Bowen W, et al. Improved variational mode decomposition method for vibration signal processing of flood discharge structure[J]. Journal of Vibration and Control, 2022,28(19-20).
[17] Li J, Chen Y, Lu C. Application of an improved variational mode decomposition algorithm in leakage location detection of water supply pipeline[J]. Measurement, 2020,173(8): 108587.
[18] 位莎,杨阳,杜明刚,等.基于参数化滤波的旋转设备特征频率提取[J].振动与冲击, 2023,42(17):203-209.
Wei Sha, Yang Yang, Du Minggang, et al. Feature Frequency Extraction of Rotating Equipment based on Parametric Filtering [J]. Journal of Vibration and Shock, 2023,42(17): 203-209.
[19] 刘运思,左帆,彭亚雄,等.基于参数优化变分模态分解算法的列车振动信号分析研究[J]. 湖南文理学院学报(自然科学版), 2023,35(04):79-85.
Liu Yunsi, Zuo Fan, Peng Yaxiong, et al. Research on Train vibration signal Analysis based on Parameter optimization variational mode decomposition algorithm [J]. Journal of Hunan University of Arts and Sciences (Natural Science Edition), 2023,35(04):79-85.
[20] Alsalah A, Holloway D, Mousavi M, et al. Identification of wave impacts and separation of responses using EMD[J]. Mechanical systems and signal processing, 2021,151(151-):107385.
[21] Mousavi A A, Zhang C, Masri S F, et al. Structural damage detection method based on the complete ensemble empirical mode decomposition with adaptive noise: a model steel truss bridge case study:[J]. Structural Health Monitoring, 2022,21(3):887-912.
[22] Liu W Q, Lü Q T, Chen R J, et al. A modified empirical mode decomposition method for multiperiod time-series detrending and the application in full-waveform induced polarization data[J]. GEOPHYSICAL JOURNAL INTERNATIONAL, 2019,217(2):1058-1079.
[23] Cheraghi N, Riley M J, Taheri F, et al. A novel approach for detection of damage in adhesivelybonded joints in plastic pipes based on vibration method using piezoelectric sensors: INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOL 1-4, PROCEEDINGS[Z]. IEEE International Conference on Systems, Man and Cybernetics: 2005,4:3472-3478.