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Database structure for storing and processing SHM data for SHM analyses and SHM algorithm research

Behrens, Tim and Moix-Bonet, Maria and Wierach, Peter (2022) Database structure for storing and processing SHM data for SHM analyses and SHM algorithm research. In: 22nd Onera-DLR Aerospace Symposium. 22nd Onera-DLR Aerospace Symposium, 2022-06-01 - 2022-06-03, Hamburg, Deutschland. (Unpublished)

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Damage identification in aircraft structures is a complex task. Especially in structural components made out of fiber composites and fiber metal laminates the traditional non-destructive methods for the detection of damage are time consuming and expensive. Structural health monitoring (SHM) can potentially reduce maintenance time and cost, but also be an enabler for condition-based maintenance as well as be used as an information source for the digital twin. The guided wave-based SHM System uses a network of transducers spread over the monitored structure. Additional information from other sensing systems may be also recorded. The data is locally acquired on the aircraft and it needs to be pre-processed, stored and accessible for analyzation. A meaningful implementation of SHM requires the integration of the SHM workflow into the aircraft processes as well as machine learning tools to analyze the acquired data in an adequate time frame. The current work focuses on a sever based application including a database which is storing the data and collating other sensing systems to it, as well as data preprocessing steps. Via the application programming interface, the results, with neglectable data volume, can be handed over for local processing or other web-based tools. Latter enables easy accessibility to demonstration and analyzation of the examined structure in different conditions. Furthermore, this infrastructure provides a good base for machine learning algorithm research (supervised classification and neural networks) in order to gain knowledge out of the additional sensing systems data. This data-management and -processing infrastructure is a necessary step towards the ultimate goal of in-time SHM.

Item URL in elib:https://elib.dlr.de/189409/
Document Type:Conference or Workshop Item (Speech)
Title:Database structure for storing and processing SHM data for SHM analyses and SHM algorithm research
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Moix-Bonet, MariaUNSPECIFIEDhttps://orcid.org/0000-0002-1327-0080UNSPECIFIED
Wierach, PeterUNSPECIFIEDhttps://orcid.org/0000-0003-0852-9112UNSPECIFIED
Date:June 2022
Journal or Publication Title:22nd Onera-DLR Aerospace Symposium
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Keywords:structural health monitoring, database, datafusion, algorithm developement, maschine leaning
Event Title:22nd Onera-DLR Aerospace Symposium
Event Location:Hamburg, Deutschland
Event Type:international Conference
Event Start Date:1 June 2022
Event End Date:3 June 2022
Organizer:ONERA & DLR
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Digital Technologies
Location: Braunschweig
Institutes and Institutions:Institute of Composite Structures and Adaptive Systems > Multifunctional Materials
Deposited By: Behrens, Tim
Deposited On:14 Nov 2022 08:51
Last Modified:24 Apr 2024 20:50

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