基于小波分析的火灾后灌浆套筒损伤的线性与非线性超声评价

PDF(3748 KB)

振动与冲击 ›› 2025, Vol. 44 ›› Issue (9) : 303-312.

故障诊断分析

基于小波分析的火灾后灌浆套筒损伤的线性与非线性超声评价

张璐，唐永泽，曾家俊，贾尚达，李红豫*，刘其舟

作者信息 +

Linear and nonlinear ultrasonic evaluation of post-fire grouted sleeve damage based on wavelet analysis

ZHANG Lu, TANG Yongze, ZENG Jiajun, JIA Shangda, LI Hongyu*, LIU Qizhou

Author information +

文章历史 +

摘要

评估火灾后预制混凝土建筑节点的安全性至关重要，可为建筑后续使用和修复提供可靠参考。半灌浆套筒连接件（Half Grouted Sleeve Connection，HGSC）是预制建筑构件中最常见的连接方式之一，其火灾后的力学性能代表着整个节点的安全性。因此，为研究火灾后HGSC的损伤，制作了3组缺陷率，共15个试件用于超声波检测试验（Ultrasonic Testing, UT），应用了5种不同火灾温度来产生不同的火灾后损伤。温度变化产生的损伤和缺陷通过UT信号的畸变表现出来，通过分析信号的差异可以区别不同的损伤程度。本文提出使用小波分析对超声波信号进行量化分析。对于线性超声波(Linear Ultrasonic Testing，LUT)检测信号，通过小波包分解（Wavelet Packet Decomposition, WPD）得到的分解等级为8的小波能量比进行分析。对于非线性超声波检测（Non-Linear Ultrasonic Testing，NLUT）信号，通过小波变换提取的一次和二次谐波超声时域信号得到声学非线性参数（Acoustic Nonlinear Parameters，ANP），并进行量化分析。结果表明，UT信号通过WPD计算的Ⅰ频段的小波包能量占比随火灾温度增加而增加，Ⅱ频段则相反，可以区分常温和受火灾影响的HGSC。通过比较不同缺陷率HGSC的小波包能量占比，可以区分无灌浆缺陷和有灌浆缺陷。ANP与火灾温度具有较强的线性相关性，可以通过ANP量化HGSC受火灾温度的影响。分析实验数据发现黏结强度同时与温度和ANP的变化存在较强的线性关系，通过建立温度和ANP同黏结强度的数学模型，即可以量化损失。因此，温度和ANP可以作为量化黏结强度的评估参数。本文的研究方法可为工程应用提供参考依据。

Abstract

Evaluation of the post-fire prefabricated concrete building, especially for the key members and its connection nodes, is crucial for the forensic investigation and the subsequent fire protection design. Usually, the connection node plays a vital role in mechanical behavior in the PC building. Herein, a grouted sleeve connection (HGSC) is one of the most common connections in precast buildings due to its excellent mechanical performance and installation convenience. Therefore, in order to assess the post-fire damage of HGSC, the combined linear and nonlinear ultrasonic testing (UT) strategy was proposed and verified experimentally. Specifically, 15 specimens with three different defect rates were fabricated, and five different fire temperatures were applied to create different post-fire damages. The damage caused by different fire temperatures directly reflects on the distortion of the UT signals. In this paper, to interpret the UT signals, we propose using the wavelet method to decompose the ultrasonic signals. For Linear Ultrasonic Testing (LUT) signals, the wavelet energy ratio obtained by wavelet packet decomposition (WPD) with a decomposition level of 8 is quantitatively analyzed. For Non-Linear Ultrasonic Testing (NLUT) signals, the acoustic nonlinear parameters (ANP) obtained from the first and second harmonic decomposition of UT signals were used to correlate with the damage. The results show that the proportion of wavelet packet energy in Band I increases with fire temperature; on the contrary, the signal energy in Band II decreases with the temperature, which can be used to distinguish post-fire damage from normal damage. While, the existence of grouting defects can be identified by wavelet packet energy ratio. The ANP shows a strong linear relationship with fire temperature, which can be used to quantify the post-fire damage in HGSC. Moreover, the bond strength exhibits a similar strong linear relationship with both temperature and ANP, allowing to quantify the loss of bond strength by these parameters. Therefore, the post-fire temperature and ANP can serve as the effective features to quantitatively evaluate the bond strength. The proposed method in this paper can provide a feasible option for evaluation of post-fire damage for in-situ application.

导出引用

张璐, 唐永泽, 曾家俊, 贾尚达, 李红豫, 刘其舟. 基于小波分析的火灾后灌浆套筒损伤的线性与非线性超声评价[J]. 振动与冲击, 2025, 44(9): 303-312

ZHANG Lu, TANG Yongze, ZENG Jiajun, JIA Shangda, LI Hongyu, LIU Qizhou. Linear and nonlinear ultrasonic evaluation of post-fire grouted sleeve damage based on wavelet analysis[J]. Journal of Vibration and Shock, 2025, 44(9): 303-312

参考文献

[1] Mohd Radzi N A, Hamid R, A. Mutalib A, et.al. A Review of Precast Concrete Beam-to-Column[J]. Advances in Civil Engineering, 2020, 2020(1): 1-23.
[2] Kose M M, Temiz H, Binici H. Effects of fire on precast members: A case study[J]. Engineering Failure Analysis, 2006, 13(8): 1191-1201.
[3] XIAO S, WANG Z L, LI X M, et al. Study of effects of sleeve grouting defects on the seismic performance of precast concrete shear walls[J]. Engineering Structures, 2021, 236: 111833.
[4] LI X M, XIAO S, GAO R D, et al. Effects of grout sleeve defects and their repair on the seismic performance of precast concrete frame structures[J]. Engineering Structures, 2021, 242: 112619.
[5] GUO T, YANG J, WANG W, et al. Experimental investigation on connection performance of fully-grouted sleeve connectors with various grouting defects[J]. Construction and Building Materials, 2022, 327: 126981.
[6] Paulsen J A, Renn M, Christenson K, et al. Future of Instrumentation International Workshop (FIIW) Proceedings[J]. Gatlinburg, TN, USA, 2012: 1-4.
[7] Ibrahim Y, Li Z, Davies C M, et al. Acoustic resonance testing of additive manufactured lattice structures[J]. Additive Manufacturing, 2018, 24: 566-576.
[8] Aldave I J, Bosom P V, González L V, et al. Review of thermal imaging systems in composite defect detection[J]. Infrared Physics & Technology, 2013, 61: 167-175.
[9] Kaur N, Goyal S, Anand K, et al. A cost-effective approach for assessment of pre-stressing force in bridges using piezoelectric transducers[J]. Measurement, 2021, 168: 108324.
[10] Markovic N, Nestorovic T, Stojic D. Numerical modeling of damage detection in concrete beams using piezoelectric patches[J]. Mechanics Research Communications, 2015, 64: 15-22.
[11] LIU T H, WEI H K, ZHANG C, et al. Time series forecasting based on wavelet decomposition and feature extraction[J]. Neural Computing and Applications, 2017, 28: 183-195.
[12] LU Y, TANG J. On time-frequency domain feature extraction of wave signals for structural health monitoring[J]. Measurement, 2018, 114: 51-59.
[13] Bayissa W L, Haritos N, Thelandersson S. Vibration-based structural damage identification using wavelet transform[J]. Mechanical systems and signal processing, 2008, 22(5): 1194-1215.
[14] CAO H Y, JIANG M S, JIA L, et al. An ultrasonic signal processing method to improve defect depth estimation in composites based on empirical mode decomposition[J]. Measurement Science and Technology, 2021, 32(11): 115112.
[15] WEI W, LI L, SHI W F, et al. Ultrasonic imaging recognition of coal-rock interface based on the improved variational mode decomposition[J]. Measurement, 2021, 170: 108728.
[16] ZHAO B, Basir O A, Mittal G S. Estimation of ultrasound attenuation and dispersion using short time Fourier transform[J]. Ultrasonics, 2005, 43(5): 375-381.
[17] Fernandes F C A, van Spaendonck R L C, Burrus C S. A new framework for complex wavelet transforms[J]. IEEE Transactions on signal processing, 2003, 51(7): 1825-1837.
[18] Sifuzzaman M, Islam M R, Ali M Z. Application of wavelet transform and its advantages compared to Fourier transform[J]. Journal of Physical Sciences, 2009, 13: 121-134.
[19] SUN Z, CHANG C C. Statistical wavelet-based method for structural health monitoring[J]. Journal of structural engineering, 2004, 130(7): 1055-1062.
[20] Asgarian B, Aghaeidoost V, Shokrgozar H R. Damage detection of jacket type offshore platforms using rate of signal energy using wavelet packet transform[J]. Marine Structures, 2016, 45: 1-21.
[21] CAO D, PAN Z F, ZHANG Z, et al. Defect detection of grouting sleeve connection with energy ratio change in frequency domain[J]. Applied Acoustics, 2024, 221: 110037.
[22] CAO D, PAN Z F, ZHANG Z, et al. Study on non-destructive testing method of grouting sleeve compactness with wavelet packet energy ratio change[J]. Construction and Building Materials, 2023, 389: 131767.
[23] YU A P, LI X H, FU F, et al. Detection of Sleeve Grouting Compactness Based on Acoustic Emission Technology[J]. Materials, 2023, 16(4): 1455.
[24] MA Y F, LI S L, WU Y Q, et al. Acoustic emission testing method for the sleeve grouting compactness of fabricated structure[J]. Construction and Building Materials, 2019, 221: 800-810.
[25] ZHANG M X, LI M C, ZHANG J R, et al. Onset detection of ultrasonic signals for the testing of concrete foundation piles by coupled continuous wavelet transform and machine learning algorithms[J]. Advanced Engineering Informatics, 2020, 43: 101034.
[26] 姜绍飞,蔡婉霞. 灌浆套筒密实度的超声波检测方法[J]. 振动与冲击,2018,37(10):43-49.
JIANG Shaofei, CAI Wanxia. Ultrasonic testing method of grouting sleeve compactness[J]. Journal of Vibration and Shock, 2018, 37(10): 43-49.
[27] ZHANG L, FANG Z M, TANG Y Z, et al. Characterization of Damage Progress in the Defective Grouted Sleeve Connection Using Combined Acoustic Emission and Ultrasonics[J]. Sensors, 2022, 22(21): 8579.
[28] Coifman R R, Meyer Y, Quake S, et al. Signal processing and compression with wavelet packets[J]. Wavelets and their applications, 1994: 363-379.
[29] HAO Q S, ZHANG X, WANG Y, et al. A novel rail defect detection method based on undecimated lifting wavelet packet transform and Shannon entropy-improved adaptive line enhancer[J]. Journal of Sound and Vibration, 2018, 425: 208-220.
[30] Carpinteri A, XU J, Lacidogna G, et al. Reliable onset time determination and source location of acoustic emissions in concrete structures[J]. Cement and concrete composites, 2012, 34(4): 529-537.
[31] Graps A. An introduction to wavelets[J]. IEEE computational science and engineering, 1995, 2(2): 50-61.
[32] Mostavi A, Kamali N, Tehrani N, et al. Wavelet based harmonics decomposition of ultrasonic signal in assessment of plastic strain in aluminum[J]. Measurement, 2017, 106: 66-78.
[33] Ruiz A, Ortiz N, Medina A, et al. Application of ultrasonic methods for early detection of thermal damage in 2205 duplex stainless steel[J]. Ndt & E International, 2013, 54: 19-26.
[34] 吕晶,尹豪,周天华,等. 不同冷却方式下S280GD+Z钢材高温后力学性能试验研究[J]. 建筑科学,2023,39(5):124-133.
LV Jing, YIN Hao, ZHOU Tianhua, et al. Experimental research on mechanical properties of S280GD+Z steel after higtemperature under different cooling methods[J]. Building Science, 2023, 39(5): 124-133.
[35] 陈俊,张白,杨鸥,等. 微锈蚀钢筋混凝土高温后粘结锚固性能试验研究[J]. 工程力学,2018,35(10):92-100.
CHEN Jun, ZHANG Bai, YANG Ou, et al.Bond performance between slightly corroded seeel bars and concrete after exposed to high temperatures[J]. Engineering mechanics, 2018, 35(10): 92-100.
[36] Fursa T V, Dann D D, Petrov M V. Evaluation of freeze-thaw damage to reinforced concrete based on the parameters of electric response to mechanical impact[J]. Construction and Building Materials, 2017, 155: 451-462.
[37] JGJ 355-2015. 钢筋套筒灌浆连接应用技术规程[S]. 北京: 中国建筑工业出版社, 2015.
JGJ 355-2015. Technical specification for grout sleeve splicing of rebars[S]. Beijing: China Architecture & Building Press, 2015.
[38] JGJ 107-2016. 钢筋机械连接技术规程[S]. 北京: 中国建筑工业出版社, 2016.
JGJ 107-2016. Technical specification for mechanical splicing of steel reinforcing bars[S]. Beijing: China Architecture & Building Press, 2016.
[39] GB/T 9978.1-2008. 建筑构件耐火试验方法第1部分：通用要求[S]. 北京:中国标准出版社, 2008.
GB/T 9978.1-2008. Fire-resistance tests-Elements of building construction - Part 1: General requirements[S]. Beijing: Standards Press of China, 2008
[40] LIN J, QU L S. Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis[J]. Journal of sound and vibration, 2000, 234(1): 135-148.
[41] Mostavi A, Kamali N, Tehrani N, et al. Wavelet based harmonics decomposition of ultrasonic signal in assessment of plastic strain in aluminum[J]. Measurement, 2017, 106: 66-78.
[42] ZHANG T H, ZHANG L, Ozevin D, et al. Multi-scale ultrasonic imaging of sub-surface concrete defects[J]. Measurement Science and Technology, 2023, 35(3): 035901.