This study introduces an innovative sensor system using micro energy harvesters based on micro-electro-mechanical systems (MEMS) integrated with Sacrificial Anode Metal Sheets (SAMS) for monitoring chloride-induced steel corrosion in reinforced concrete (RC) structures. MEMS devices enable real-time structural health monitoring by tracking changes in frequency and amplitude due to vibration-based electrostatic power generation. Among the tested SAMS materials (aluminum, copper, iron, and zinc), Fe demonstrated the highest sensitivity, with consistent frequency drops of 250 Hz under wet and dry conditions, creating it as the most suitable for MEMS integration. Parametric experiments also identified optimal target frequencies for energy harvesting: 300 and 350 Hz for a 20 mm cantilever length, and 150 and 200 Hz for a 30 mm cantilever. This proactive approach enables early detection of corrosion in RC structures, enhancing infrastructure safety and advancing corrosion detection methodologies.
WattanapornpromRIshidaT. Modeling of chloride penetration into concrete under airborne chloride environmental conditions combined with washout effects. J Adv Concr Technol2017; 15: 126–142.
4.
PhamNDOkazakiSKuriyamaY, et al. Real-time aerosol chloride deposition measuring device using a conductivity sensor. Atmos Environ2019; 213: 757–766.
5.
DangTDMiuraS. Evaluation of applicability of weathering steel by exposure tests in Ho Chi Minh city marine area. In: IOP conference series: Materials Science and Engineering, Institute of Physics Publishing, 2020, Ho Chi Minh City, Vietnam, 18–20 October 2019, vol. 869, p. 032018. IOP.
6.
TranTTHaTMAoyamaT, et al. Long-term corrosion monitoring by titanium wire sensor and vibration-based energy harvester. Int J Struct Civ Eng Res2020; 10: 17–25.
7.
RafdinalRSAoyamaTFukugawaN. Development of titanium wire sensor for corrosion monitoring in the concrete structures. PS Mitsubishi Tech Rep2028; 16: 28–29.
8.
ZhuHLuoHAiD, et al. Mechanical impedance-based technique for steel structural corrosion damage detection. Measurement2016; 88: 353–359.
9.
NaoumMCPapadopoulosNASapidisGM, et al. Efficacy of PZT sensors network different configurations in damage detection of fiber-reinforced concrete prisms under repeated loading. Sensors2024; 24: 5660.
10.
LiuQDaiGWangC, et al. Interfacial effect on quantitative concrete stress monitoring via embedded PZT sensors based on EMI technique. Buildings2023; 13: 560.
11.
NaoumMCPapadopoulosNAVoutetakiME, et al. Structural health monitoring of fiber-reinforced concrete prisms with polyolefin macro-fibers using a piezoelectric materials network under various load-induced stress. Buildings2023; 13: 2465.
12.
SunGQiaoGXuB. Corrosion monitoring sensor networks with energy harvesting. IEEE Sens J2011; 11: 1476–1477.
13.
OzevinD. Micro-electro-mechanical-systems (MEMS) for assessing and monitoring civil infrastructures. Sens Technol Civ Infrastruct2014; 1: 265–302.
14.
TokognonACGaoBTianGY, et al. Structural health monitoring framework based on internet of things: a survey. IEEE Internet Things J2017; 4: 619–635.
15.
KamariotisAChatziEStraubD. A framework for quantifying the value of vibration-based structural health monitoring. Mech Syst Signal Process2023; 184: 109708.
16.
Di NuzzoFBrunelliDPolonelliT, et al. Structural health monitoring system with narrowband IoT and MEMS sensors. IEEE Sens J2021; 21: 16371–16380.
17.
Abdul RazakAHAbdullahNSAl JunidSAM, et al. Structural crack detection system using internet of things (IoT) for structural health monitoring (SHM): a review. J Kejuruteraan2022; 34: 983–998.
18.
LamonacaFScuroCSciammarellaPF, et al. Number 2. Acta IMEKO | www, 2019, pp. 45–52, www.imeko.org (accessed 17 September 2024).
19.
PengZLiJHaoH. Development and experimental verification of an IoT sensing system for drive-by bridge health monitoring. Eng Struct2023; 293: 116705.
20.
CeylanHGopalakrishnanKKimS, et al. Highway infrastructure health monitoring using micro-electromechanical sensors and systems (MEMS). J Civ Eng Manag2013; 19: S188–S201.
21.
RossiABocchettaGBottaF, et al. Accuracy characterization of a MEMS accelerometer for vibration monitoring in a rotating framework. Appl Sci2023; 13: 5070.
22.
VillacortaJJDel-ValLMartínezRD, et al. Design and validation of a scalable, reconfigurable and low-cost structural health monitoring system. Sensors2021; 21: 1–16.
23.
MitsuyaHAshizawaHShimomuraN, et al. A method for optimizing the output power of MEMS vibrational energy harvester. In: Symposium on design test integration & packaging of MEMS and MOEMS, Lyon, France, 15–26 June 2020. IEEE.
24.
OhataYNakanishiTChokawaK, et al. Improvement of the reliability of potassium-ion electrets thorough an additional oxidation process. Appl Phys Lett2022; 121:243903.
25.
ToshiyoshiHHonmaHMitsuyaH, et al. Electrostatic vibrational MEMS energy harvester with thin film electrets. Vacuum Surf Sci2020; 63: 223–228.
26.
OhataYAraidaiMIshiguroT, et al. Effect of hydrogen atoms on potassium-ion electrets used in vibration-powered generators. Mater Sci Semicond Process2023; 157: 107306.
27.
MitsuyaHHashimotoKChangK-C, et al. Low-power frequency monitoring system for bridge using MEMS vibrational-energy harvesting sensor. IEEJ Trans Sens Micromach2022; 142: 139–146.
28.
HashiguchiGToshiyoshiH. Electret MEMS vibration energy harvester with reconfigurable frequency response. Sens Mater2023; 35: 1957–1983.
29.
HonmaHIkenoSToshiyoshiH. MEMS electrostatic energy harvester developed by simultaneous process for anodic bonding and electret charging. Sens Mater2023; 35: 1941–1955.
30.
HirakiYMasudaAIkedaN, et al. Wideband piezoelectric energy harvester for low-frequency application with plucking mechanism. In: Active and passive smart structures and integrated system, 2015, San Diego, California, 8–12 March 2015, vol. 9431, p. 943137. SPIE.
31.
KogaHMitsuyaHHonmaH, et al. Development of a cantilever-type electrostatic energy harvester and its charging characteristics on a highway viaduct. Micromachines2017; 8: 293.
32.
ChangKCHashimotoKMitsuyaH, et al. Electrostatic micro-electro-mechanical system vibrational energy harvesters for bridge damage detection, The Rise of Smart Cities. Elsevier, 2022, pp. 319–342.
33.
HashimotoKShiotaniTMitsuyaH, et al. Mems vibrational power generator for bridge slab and pier health monitoring. Appl Sci2020; 10: 1–13.
34.
SinghRSharmaSSharmaMS. Guided waves for damage monitoring in plates with corrosion defects. Int J Innov Res Sci Eng Technol2007; 3: 10072–10083.
35.
ChengLMaruyamaI. Effect of relative humidity and temperature on steel corrosion rate in chloride contaminated mortar. Cem Sci Concr Technol2021; 75: 225–232.
36.
YooJ-SKimG-IKimJ-G. Effect of frequency and ratio of wet/dry stages in cyclic corrosion test on localized corrosion of complex phase high-strength steel. Materials2023; 16(23): 7329.
37.
FranchettiFPüschelM.FFT (fast Fourier transform). In: WahB (ed.) Encyclopedia of computer science and engineering. New York: Springer, 2009, pp. 658–671.
38.
MitchesonPDYeatmanEMRaoGK, et al. Energy harvesting from human and machine motion for wireless electronic devices. Proc IEEE2008; 96: 1457–1486.
39.
ToshiyoshiHJuSHonmaH, et al. MEMS vibrational energy harvesters. Sci Technol Adv Mater2019; 20: 124–143.
40.
HonmaHMitsuyaHHashiguchiG, et al. Power generation demonstration of electrostatic vibrational energy harvester with comb electrodes and suspensions located in upper and lower decks. Sensors Mater2022; 34: 1527–1538.
41.
HonmaHMitsuyaHHashiguchiG, et al. Improvement of energy conversion effectiveness and maximum output power of electrostatic induction-type MEMS energy harvesters by using symmetric comb-electrode structures. J Micromech Microeng2018; 28: 064005–064017.
42.
HonmaHTohyamaYIkenoS, et al. Equivalent circuit model for MEMS vibrational energy harvester compatible with sinusoidal and nonsinusoidal vibrations. Sensors Mater2020; 32(7): 2475–2492.
43.
GorejováRŠišolákováICipaP, et al. Corrosion behavior of Zn, Fe and Fe-Zn powder materials prepared via uniaxial compression. Materials2021; 14: 4983.
44.
ChenYZhangWMaitzMF, et al. Comparative corrosion behavior of Zn with Fe and Mg in the course of immersion degradation in phosphate-buffered saline. Corros Sci2016; 111: 541–555.
45.
StehrerTPraherBViskupR, et al. Laser-induced breakdown spectroscopy of iron oxide powder. J Anal At Spectrom2009; 24: 973–978.
46.
SchlatterNLottermoserBG. Laser-induced breakdown spectroscopy applied to elemental analysis of aqueous solutions—a comprehensive review. Spectrosc J2024; 2(1): 1–32.
47.
YuanRTangYZhuZ, et al. Accuracy improvement of quantitative analysis for major elements in laser-induced breakdown spectroscopy using single-sample calibration. Anal Chim Acta2019; 1064: 11–16.
48.
XiaoKLiZSongJ, et al. Effect of concentrations of Fe2+ and Fe3+ on the corrosion behavior of carbon steel in Cl− and SO42− aqueous environments. Metals Mater Int2021; 27: 2623–2633.
49.
MengGLiYShaoY, et al. Effect of Cl− on the properties of the passive films formed on 316L stainless steel in acidic solution. J Mater Sci Technol2014; 30: 253–258.
50.
PrawotoYIbrahimKNikWSW. Effect of pH and chloride concentration on the corrosion of duplex stainless steel. Arab J Sci Eng2009; 34(2): 115.
51.
NishimuraNTKatayamaHNodaK, et al. Electrochemical behavior of rust formed on carbon steel in a wet/dry environment containing chloride ions. Corrosion2000; 56: 935–941.
52.
CaiYKZhaoYZhangZK, et al. Atmospheric and marine corrosion: influential environmental factors and models. IWEMSE2018; 1: 178–186.
53.
SongGL. The grand challenges in electrochemical corrosion research. Front Mater2014; 1: 2.
54.
LynchYJPLohKJ. A summary review of wireless sensors and sensor networks for structural health monitoring. Shock Vibrat Dig2006; 38: 91–128.
55.
TsubokuraYNoguchiKYagiT. Numerical simulation of airborne salt particle behavior in dry gauze method using porous media model. J Appl Mech2021; 88: 101001.
