SHM demonstrators - Motivation
SHM is expected to cover a structure‘s complete life cycle span starting from manufacturing and ending with recycling in the ideal case. This leads to a variety of disciplines and hence parties to be included which generate a remarkable amount of data that need to be adequately processed to be used for SHM in a most suitable way. An important means to get this explored, demonstrated and validated is through technology demonstrators, which are not limited to a single event only but rather longer term. This should allow the holistic claim of SHM to be better demonstrated, understood and finally applied when compared how SHM has been brought into application in the past.
This year a series of SHM technology demonstrators has been invited to be displayed and operated live at EWSHM 2024. The idea is to make demonstrators available that can be loaded, and onto which sensors of different kind can be applied that do allow loads, geometry, stresses, strain and any kinds of structural degradation to be monitored. Data being generated are intended to be made available if possible such that parties could make use of those for any future elaborations, would it be in terms of benchmarks, new signal processing methods or merging the the data in terms of establishing a complete data process flow in the sense of a digital twin.
The list below provides an overview of demonstrators to be shown at EWSHM 2024 including a brief description, a link to the person being in charge and the possibility of additional sensors to be implemented on the demonstrator as well as data being available from the demonstrator. Parties being interested in getting their sensing technology demonstrated are welcome to get in contact with the respective person in charge at any time, prior as well as post EWSHM 2024, since it is expected that the demonstrators will be displayed at future events such that further technology development can be demonstrated.
What is available currently?
Applications:
• Wind energy
• Metallic structures
• Civil infrastructure
Sensing:
• Strain
• Vibration
• Acoustics
• Electromagnetics
• Sensor systems
• Comparison and benchmark
• Signal processing
Internet-based Platforms for Numerical Simulation:
• Results databases for benchmarks
• Algorithm databases for evaluations
• Internet-based platforms and services with different tools
Type |
Contact |
|
External Monitoring |
Data Available |
|
Steel beams under 3-point bending: A test rig with 2 IPB 100 steel beams of 2 metres in length each that can be loaded with a hydraulic jack even different times in the sense of fatigue. One beam will even be notched such that a crack can be initiated. |
C. Boller |
c.boller@mx.uni-saarland.de | yes | yes |
|
Energy storage pressure vessel: A hydrogen pessure vessel instrumented with acoustic emission, guided ultrasonic wave and fibre optical sensor equippment. Datasets are available for cyclic loading up to 800 bar at various temperatures. |
J. Prager |
jens.prager@bam.de | no | yes |
|
Open guided waves: Several datasets for guided wave-based structural health monitoring are available online: www.openguidedwaves.de |
J. Moll |
no | yes | |
|
Radar-based SHM of wind turbine blades: Measurements from tower installation are available online enabling remote inspection of wind turbine blades in the frequency band from 33.4 – 36.0GHz: https://zenodo.org/records/8366654 |
J. Moll |
jochen.moll@uni-siegen.de | no | yes |
|
Integrated Monitoring system using guided waves: A fibre composite structure with integrated piezoelectric transducers. Datasets with and without damage located on different positions are available, the position of damage can be changed during demonstration. |
L. Schubert |
lars.schubert@ikts.fraunhofer.de enes.savli@ikts.fraunhofer.de kilian.tschoeke@ikts.fraunhofer.de |
no | no |
|
Full life cycle tracking of additively manufactured parts: Unnotched specimens will be additively manufactured and exposed to fatigue loading while being monitored with different NDT techniques. The complete data portfolio from manufacturing until fracture will be demonstrated as a life-cycle data stream. |
C. Boller (Saarland Univ.) & H. Sohn (KAIST) |
c.boller@mx.uni-saarland.de hoonsohn@kaist.ac.kr |
yes, but limited | yes |
|
Composite spigot air brake as a means for data fusion in monitoring: The airbrake demonstrator of a Eurofighter, is demonstrating maintenance scenarios for aircraft that utilize structural health monitoring and damage assessment and visualise them with the help of augmented reality. The SHM system and the in-situ damage assessment are embedded in a virtual assistant application for augmented reality glasses (Microsoft HoloLens). Menu-guided instructions and inspection documentation facilitate on-site inspections. |
P. Wierach (DLR) |
yes | no | |
|
Monitoring of a pressurized water circle system: piping system of 5x9 meters dimension with DN100 steel pipes and two 1000 lt steel vessels; possibility to run pressure cycles up to 16 bar, simulating water leakages, while monitoring acceleration and acoustic emissions. |
A. Marzani |
alessandro.marzani@unibo.it | yes, but limited | yes |
|
Monitoring of bolts: Two types of sensor-integrated bolts will be mounted in a girder joint to showcase in-situ bolt force monitoring |
D. Rill (Fischerwerke) |
Daniel.Rill@fischer.de | no | yes, but limited |
|
Monitoring of tendon fracture in reinforced concrete: The model bridge has the dimensions 100cm x 34cm x36cm and is made from concrete and steel reinforcement. AE sensors are installed and artificial AE can be triggered to simulate traffic noise and potential tendon failures. Data are recorded and analyzed in real time including upload to the cloud-based dashboard. |
M. Häuserer (Vallen Systeme) |
michael.haeuserer@vallen.de | yes, but limited | yes |
|
Load Identification and Damage Detection by a Digital Twin of a Bridge applying Bayesian Model Calibration: A digital twin for decision making during the life cycle of civil infrastructure is a promising concept combining simulation models with corresponding structure-specific sensor data to support maintenance decisions or to investigate the reliability. The sensor data quality as well as the model quality of the digital twin, comprising on modeling assumptions and correct model parameters strongly influences the prognosis results. |
S. Degener (BAM) |
sebastian.degener@bam.de ralf.herrmann@bam.de |
yes | yes |
Explanations
External monitoring: Demonstrator is available for additional sensors to be mounted for data recording.
Data available: Data being available can be made available to the general public for further processing.
The technology demonstration will be on display in Session- A-Room (F1-F3) from 8:30 a.m. to 6 p.m. on Tuesday.