TY - GEN

T1 - Wire Break Detection in Bridge Tendons Using Low-Frequency Acoustic Emissions

AU - Lange, Alexander

AU - Käding, Max

AU - Hinrichs, Reemt

AU - Ostermann, Jörn

AU - Marx, Steffen

N1 - Funding Information: This research was supported by German Federal Ministry for Economic Affairs and Climate Action (BMWK). The authors also thank Prof. Dr.-Ing. Thomas Braml, Matthias Haslbeck, M.Sc. and Christian Merkl, M.Sc. from the Universitaet der Bundeswehr Muenchen for faciliating the experiments.

PY - 2023

Y1 - 2023

N2 - Aging infrastructure is increasingly becoming a problem in industrialized countries. As a matter of fact, many existing bridges were already built in the mid-to-late twentieth century and hence are not in a good condition. A majority of these bridges were built from prestressed concrete and therefore may suffer from stress corrosion cracking of steel tendons. Due to their importance for structural integrity and hence structural safety, a reliable monitoring method of bridge tendons is of major interest. Recent research suggests the use of acoustic emissions (AE) using ultrasonic sensors to detect wire break events in civil engineering structures. In this work, accelerometers operating in the audible frequency range (<17 kHz) are used to record more than hundred wire breaks manually conducted at two old girders taken from a demolished bridge in Roding, Germany. Based on these experiments, approximately twelve days of continuous operational recordings conducted at a similar bridge construction in Hagen, Germany and additional wire breaks recorded at the bridge structure in Roding before demolition, we train and evaluate a support vector machine to detect wire break events in bridge tendons using low-level frequency domain features such as the spectral bandwidth. On the evaluation dataset, we achieve a recall score of more than 90% while having a FP-rate of approximately ten events per day. It should be noted that using low-frequency acoustic emissions we are able to detect wire break events in distances up to more than 20 m.

AB - Aging infrastructure is increasingly becoming a problem in industrialized countries. As a matter of fact, many existing bridges were already built in the mid-to-late twentieth century and hence are not in a good condition. A majority of these bridges were built from prestressed concrete and therefore may suffer from stress corrosion cracking of steel tendons. Due to their importance for structural integrity and hence structural safety, a reliable monitoring method of bridge tendons is of major interest. Recent research suggests the use of acoustic emissions (AE) using ultrasonic sensors to detect wire break events in civil engineering structures. In this work, accelerometers operating in the audible frequency range (<17 kHz) are used to record more than hundred wire breaks manually conducted at two old girders taken from a demolished bridge in Roding, Germany. Based on these experiments, approximately twelve days of continuous operational recordings conducted at a similar bridge construction in Hagen, Germany and additional wire breaks recorded at the bridge structure in Roding before demolition, we train and evaluate a support vector machine to detect wire break events in bridge tendons using low-level frequency domain features such as the spectral bandwidth. On the evaluation dataset, we achieve a recall score of more than 90% while having a FP-rate of approximately ten events per day. It should be noted that using low-frequency acoustic emissions we are able to detect wire break events in distances up to more than 20 m.

KW - Acoustic emission

KW - Bridge monitoring

KW - Damage detection

KW - Support vector machines

UR - http://www.scopus.com/inward/record.url?scp=85134298680&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-07322-9_104

DO - 10.1007/978-3-031-07322-9_104

M3 - Conference contribution

AN - SCOPUS:85134298680

SN - 9783031073212

T3 - Lecture Notes in Civil Engineering

SP - 1024

EP - 1033

BT - European Workshop on Structural Health Monitoring, EWSHM 2022, Volume 3

A2 - Rizzo, Piervincenzo

A2 - Milazzo, Alberto

PB - Springer Science and Business Media Deutschland GmbH

CY - Cham

T2 - 10th European Workshop on Structural Health Monitoring, EWSHM 2022

Y2 - 4 July 2022 through 7 July 2022

ER -