Damage detection in noisy environments based on EMI and Lamb waves: A comparative study

被引:2
|
作者
Campeiro, Leandro Melo [1 ,2 ]
Budoya, Danilo Ecidir [1 ]
Baptista, Fabricio Guimaraes [1 ]
机构
[1] Sao Paulo State Univ UNESP, Sch Engn, Dept Elect Engn, Bauru, SP, Brazil
[2] Sao Paulo State Univ UNESP, Sch Engn, Dept Elect Engn, Av Eng Luiz Edmundo C Coube 14-01, BR-17033360 Bauru, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Piezoelectric transducers; electromechanical impedance; Lamb waves; noise; damage detection;
D O I
10.1177/1045389X221128583
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Structural health monitoring (SHM) systems have shown the potential to detect damage in various types of structures, thus increasing safety and reducing maintenance costs. Among the damage detection methods are those that use small piezoelectric transducers attached to the monitored structure, such as the electromechanical impedance (EMI) and Lamb waves methods. Although both methods have shown to be effective in detecting structural damage, external disturbances such as noise can alter the signals from piezoelectric sensors in real applications and prejudice the correct diagnosis of the monitored structure. Therefore, this paper presents a comparative analysis of the performance of EMI and Lamb waves methods in noisy environments, which is a condition commonly found in real structures. The obtained results add value to the SHM field by allowing to know the tradeoff in choosing the appropriate method regarding the detection, quantification, and location of structural damage under noise conditions. Experimental tests were performed on aluminum structures to assess the effectiveness of both techniques to detect, quantify, and locate structural damage under noise of different intensities. The experimental results show that each technique has different characteristics in terms of effectiveness in detecting, quantifying, and locating damage under noise effects.
引用
收藏
页码:1042 / 1056
页数:15
相关论文
共 50 条
  • [31] Comparative Study of Electromechanical Impedance and Lamb Wave Techniques for Fatigue Crack Detection and Monitoring in Metallic Structures
    Lim, Say Ian
    Liu, Yu
    Soh, Chee Kiong
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2012, PTS 1 AND 2, 2012, 8345
  • [32] Damage Feature Extraction and Parameter Characterization of Large Generator Stator Insulation Based on Lamb Waves Detection Method
    She, Zhifeng
    Li, Ruihua
    Gu, Haojie
    Hu, Bo
    Mao, Zhongya
    2019 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL MATERIALS AND POWER EQUIPMENT (ICEMPE 2019), 2019, : 421 - 425
  • [33] Adaptive Weighted Damage Imaging of Lamb Waves Based on Deep Learning
    Shen, Ronghe
    Zhou, Zixing
    Xu, Guidong
    Zhang, Sai
    Xu, Chenguang
    Xu, Baiqiang
    Luo, Ying
    IEEE ACCESS, 2024, 12 : 128860 - 128870
  • [34] Nondestructive testing method based on lamb waves for localization and extent of damage
    Chen, Jianlin
    Li, Zheng
    Gong, Kezhuang
    ACTA MECHANICA SOLIDA SINICA, 2017, 30 (01) : 65 - 74
  • [35] A Comparative Study on Denoising Algorithms for Footsteps Sounds as Biometric in Noisy Environments
    Caravaca-Mora, Ronald
    Brenes-Jimenez, Carlos
    Coto-Jimenez, Marvin
    COMPUTATION, 2022, 10 (08)
  • [36] An imaging algorithm for damage detection with dispersion compensation using piezoceramic induced lamb waves
    Zhang, Guangmin
    Gao, Weihang
    Song, Gangbing
    Song, Yue
    SMART MATERIALS AND STRUCTURES, 2017, 26 (02)
  • [38] Baseline Signal Reconstruction for Temperature Compensation in Lamb Wave-Based Damage Detection
    Liu, Guoqiang
    Xiao, Yingchun
    Zhang, Hua
    Ren, Gexue
    SENSORS, 2016, 16 (08)
  • [39] Experimental research on damage detection of large thin aluminum plate based on Lamb wave
    Zhao, Naizhi
    Yan, Shi
    SENSORS AND SMART STRUCTURES TECHNOLOGIES FOR CIVIL, MECHANICAL, AND AEROSPACE SYSTEMS 2010, 2010, 7647
  • [40] EVALUATION OF THE LAMB WAVES APPROACH TO DETECT SIMULATED DAMAGE IN AN ORTHOGONAL PLANE OF THE SENSOR NETWORK SURFACE FOR CORROSION DETECTION APPLICATION
    Dotta, Fernando
    Ceresetti, Leandro Bruno
    HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS 2013, 2013, 8695