Prestressed steel tendons, as the key load-bearing component of prestressed concrete girders, will inevitably suffer damage, threatening the bridge’s safety and durability. Existing methods of locating damage to prestressed steel tendons necessitate the arrangement of numerous acoustic emission (AE) sensors outside the girder. To reduce the AE monitoring costs of the actual bridge, a dual-sensor AE localization method is proposed to monitor which steel tendon is damaged in a prestressed concrete girder. The key to implementing the proposed method is using a waveguide rod to preconnect the prestressed steel tendons inside the girder. To validate the feasibility of the proposed method, simplified positioning tests were performed on a test platform connected by waveguide rods, which includes connection forms of rebar welding, rebar adhesion, steel plate welding, and steel plate adhesion. Furthermore, the practicality of the proposed method was demonstrated by preinstallation of waveguide rods within a posttensioned prestressed hollow slab. Results indicate the dual-sensor localization method could precisely determine which prestressed steel tendon is suffering damage regardless of ambient AE noise, where AE wave velocity for localization could be selected empirically. The proposed method helps to reduce the cost of AE-based tendon breakage monitoring of bridges.
ZhuQWangHSpencerBF, et al. Mapping of temperature-induced response increments for monitoring long-span steel truss arch bridges based on machine learning. J Struct Eng2022; 148(5): 4022034.
2.
DoroudiRLavassaniSHHShahrouziM. Optimal tuning of three deep learning methods with signal processing and anomaly detection for multi-class damage detection of a large-scale bridge. Struct Health Monit2024; 23(5): 3227–3252.
3.
ZhuQWangHZhuX, et al. Investigation on the pattern for train-induced strains of the long-span steel truss railway bridge. Eng Struct2023; 275(A): 115268.
4.
HuZLinPGuoH, et al. Evaluation of the residual bearing capacity of prestressed concrete T-girder bridges based on bending stiffness reduction. J Bridge Eng2025; 30(1): 4024107.
5.
KwonOSohnHLimHJ. Post-tensioning tendon force estimation of in-service prestressed concrete structure using cylindrical Lamb waves. Struct Health Monit2025; 24(1): 421–433.
6.
JiangSChengYZhangJ. Vision-guided unmanned aerial system for rapid multiple-type damage detection and localization. Struct Health Monit2023; 22(1): 319–337.
7.
SahaASThrockmortonELucierG, et al. Determining prestress losses, residual capacity, and degradation from testing of prestressed concrete bridge girders after 56 years of service. J Bridge Eng2025; 30(2): 4024115.
8.
StefaniukDMechaalaABelarbiA. Transfer length of stainless-steel strands in prestressed bridge elements: a combined experimental and numerical modeling approach. Eng Struct2025; 325: 119482.
9.
BaralMAljewadABreunigA, et al. Acoustic emission monitoring for necking in sheet metal forming. J Mater Process Technol2022; 310: 117758.
10.
ZhouZRuiYCaiXA. novel linear-correction localization method of acoustic emission source for velocity-free system. Ultrasonics2021; 115: 106458.
11.
SantisS deTomorAK. Laboratory and field studies on the use of acoustic emission for masonry bridges. NDT E Int2013; 55: 64–74.
12.
MegidWAChaineyMALebrunP, et al. Monitoring fatigue cracks on eyebars of steel bridges using acoustic emission: a case study. Eng Fract Mech2019; 211: 198–208.
13.
TangLLiuXWuX, et al. Defect localization on rolling element bearing stationary outer race with acoustic emission technology. Appl Acoust2021; 182: 108207.
14.
QuyTBKimJ. Crack detection and localization in a fluid pipeline based on acoustic emission signals. Mech Syst Signal Process2021; 150: 107254.
15.
LiDNieJRenW, et al. A novel acoustic emission source location method for crack monitoring of orthotropic steel plates. Eng Struct2022; 253: 113717.
16.
LiSLiuZXiaL, et al. Wire breaking localization of parallel steel wire bundle using acoustic emission tests and finite element analysis. Struct Control Health Monit2021; 28(3): 1–18.
17.
BarboshMSadhuA. Wavelet packet transformation-based improved acoustic emission method for structural damage identification. Smart Mater Struct2025; 34(1): 15036.
18.
DasAKLaiTTChanCW, et al. A new non-linear framework for localization of acoustic sources. Struct Health Monit2019; 18(2): 590–601.
19.
van SteenCPahlavanLVerstryngeE. Smart aggregates for acoustic emission monitoring of concrete cracking and reinforcement corrosion. Constr Build Mater2024; 443: 137644.
20.
KocurGKSaengerEHGrosseCU, et al. Time reverse modeling of acoustic emissions in a reinforced concrete beam. Ultrasonics2016; 65: 96–104.
21.
DasAKLeungCKY. A new power-based method to determine the first arrival information of an acoustic emission wave. Struct Health Monit2019; 18(5–6): 1620–1632.
22.
ZhangFPahlavanLYangY. Evaluation of acoustic emission source localization accuracy in concrete structures. Struct Health Monit2020; 19(6): 2063–2074.
23.
ZhangFYangYNaaktgeborenM, et al. Probability density field of acoustic emission events: damage identification in concrete structures. Constr Build Mater2022; 327: 126984.
24.
BarboshMLiBQSadhuA. Improved acoustic source localization method for crack identification in structures. Appl Acoust2024; 223: 110093.
25.
SabzevariSAHVakili AzghandiM. Acoustic source localization in an isotropic plate: Damper’s coverage length optimization based on response surface method (RSM). Measurement2022; 199: 111476.
26.
FuWLiuYWangL, et al. Minimum squared error method based on modal analysis for acoustic emission source location using microfiber coupler sensor. Measurement2023; 220: 113406.
27.
ZhangLZhangTChenE, et al. Phased acoustic emission sensor array for localizing radial and axial positions of defects in hollow structures. Measurement2020; 151: 107223.
28.
LiuZLiSLiuL. Investigation of wave propagation path and damage source 3D localization in parallel steel wire bundle. Struct Control Health Monit2022; 29(10): e3051.
29.
ManuelloANiccoliniGCarpinteriA. AE monitoring of a concrete arch road tunnel: damage evolution and localization. Eng Fract Mech2019; 210: 279–287.
30.
JinachandranSNingYWuB, et al. Cold crack monitoring and localization in welding using fiber Bragg grating sensors. IEEE Trans Instrum Meas2020; 69(11): 9228–9236.
31.
QinGLiMFangS, et al. Study of a grid-based regional localization method for damage sources during three-point bending tests of wood. Constr Build Mater2024; 419: 135348.
32.
ZhangJMaHYanW, et al. Defect detection and location in switch rails by acoustic emission and Lamb wave analysis: a feasibility study. Appl Acoust2016; 105: 67–74.
33.
YuFOkabeY. Linear damage localization in CFRP laminates using one single fiber-optic Bragg grating acoustic emission sensor. Compos Struct2020; 238: 111992.
34.
PuYChenJJiangD, et al. Improved method for acoustic emission source location in rocks without prior information. Rock Mech Rock Eng2022; 55(8): 5123–5137.
35.
LiSZhangLGuoP, et al. Characteristic analysis of acoustic emission monitoring parameters for crack propagation in UHPC-NC composite beam under bending test. Constr Build Mater2021; 278: 122401.
36.
LiSWuYShiH. A novel acoustic emission monitoring method of cross-section precise localization of defects and wire breaking of parallel wire bundle. Struct Control Health Monit2019; 26(4): e2334.
37.
MiaoSGaoLTongF, et al. Research on high precision optical fiber acoustic emission system for weak damage location on concrete. Constr Build Mater2022; 347: 128331.
38.
LiuCShangXMiaoR. Acoustic emission source location on a cylindrical shell structure through grouped sensors based analytical solution and data field theory. Appl Acoust2022; 192: 108747.
39.
WuYPerrinMPastorML, et al. On the determination of acoustic emission wave propagation velocity in composite sandwich structures. Compos Struct2021; 259: 113231.
40.
NiriEDFarhidzadehASalamoneS. Nonlinear Kalman filtering for acoustic emission source localization in anisotropic panels. Ultrasonics2014; 54(2): 486–501.
41.
YuJHongYByunY, et al. Non-destructive evaluation of the grouted ratio of a pipe roof support system in tunneling. Tunn Undergr Sp Tech2016; 56: 1–11.
