Wireless Crack Detection System Based on IoT and Acoustic Emission

被引:0
|
作者
Sayyaf, Mohamad Issam [1 ]
Carni, Domenico Luca [1 ]
Lamonaca, Francesco [1 ]
机构
[1] Univ Calabria, Dept Informat Modeling Elect & Syst Engn, Arcavacata Di Rende, Italy
来源
2023 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR LIVING ENVIRONMENT, METROLIVENV | 2023年
关键词
Smart sensor; Crack detection; Wireless sensor; IoT; Edge computing; concrete; Acoustic Emission; CONCRETE STRUCTURES; DAMAGE;
D O I
10.1109/MetroLivEnv56897.2023.10164053
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper proposes a Wireless Crack Detection System (WCDS) for concrete structures based on IoT and Acoustic Emission (AE). A crack is a rupture inside the building material occurring due stress, aging, and other damaging factors. When a crack occurs, energy is released in term of an ultrasonic wave, also, known as AE. The WCDS objective is to timely detect cracks and wirelessly transmit the collected data to a central server for analysis. The AE sensor captures the crack signals, which undergo analogy signal processing to improve signal quality and remove noise. The acquired signals are analysed, and if a crack is detected, the proposed system extracts the features from the signal, generates a GPS-based timestamp with microsecond accuracy, and uses the MQTT protocol to send the data to the server (Raspberry Pi). Node-RED is utilized for data visualization, making it simple for users to monitor the system and study the crack signals.
引用
收藏
页码:80 / 84
页数:5
相关论文
共 50 条
  • [31] An optical fiber F-P acoustic emission sensor system for the detection of steel crack initiation
    Tong, Xinglin
    Ji, Tao
    Wei, Wanting
    Wen, Changshan
    Zhu, Xiaolong
    Leng, Zhuoyan
    22ND INTERNATIONAL CONFERENCE ON OPTICAL FIBER SENSORS, PTS 1-3, 2012, 8421
  • [32] Detection and location of microdefects during selective laser melting by wireless acoustic emission measurement
    Ito, Kaita
    Kusano, Masahiro
    Demura, Masahiko
    Watanabe, Makoto
    ADDITIVE MANUFACTURING, 2021, 40
  • [33] Approximate entropy as acoustic emission feature parametric data for crack detection
    Lin, Li
    Chu, Fulei
    NONDESTRUCTIVE TESTING AND EVALUATION, 2011, 26 (02) : 119 - 128
  • [34] Electromagnetic Stimulation of the Acoustic Emission for Fatigue Crack Detection of the Sheet Metal
    Jin, Liang
    Yang, Qingxin
    Liu, Suzhen
    Zhang, Chuang
    Li, Peng
    IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY, 2010, 20 (03) : 1848 - 1851
  • [35] A Wireless Communication System of IoT Based on UAV
    Zhang, Yu
    Wu, Qingcai
    Wang, Jichang
    PAAP 2021: 2021 12TH INTERNATIONAL SYMPOSIUM ON PARALLEL ARCHITECTURES, ALGORITHMS AND PROGRAMMING, 2021, : 178 - 182
  • [36] Noise isolation with phononic crystals to enhance fatigue crack growth detection using acoustic emission
    Kabir, Minoo
    Mostavi, Amir
    Ozevin, Didem
    JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, 2018, 8 (03) : 529 - 542
  • [37] Acoustic emission for corrosion detection
    Cole, P.
    Watson, J. R.
    ACOUSTIC EMISSION TESTING, 2006, 13-14 : 231 - +
  • [38] Concrete damage detection based on embedded acoustic emission sensors
    Sha, Fei
    Xu, Dongyu
    Huang, Shifeng
    Cheng, Xin
    ADVANCES IN CIVIL STRUCTURES, PTS 1 AND 2, 2013, 351-352 : 1222 - 1225
  • [39] Crack Pattern Recognition Based on Acoustic Emission Waveform Features
    Jingjing Dai
    Jianfeng Liu
    Lulin Zhou
    Xin He
    Rock Mechanics and Rock Engineering, 2023, 56 : 1063 - 1076
  • [40] Acoustic Emission-Based Fatigue Crack Growth Prediction
    Keshtgar, Azadeh
    Modarres, Mohammad
    59TH ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM (RAMS), 2013,