<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>60911</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>4</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Monitoring of composite pressure vessels using surface applied distributed fiber optic sensors</title>
    <abstract language="eng">In this paper, we report on surface-applied distributed fibre optic sensors for monitoring composite pressure vessels designed for hydrogen storage. Previous reports have revealed that integrating optical fibres within vessel composite structures effectively enables the monitoring of structural behavior throughout their lifetime.&#13;
However, integrating optical fibres during the manufacturing process is complex and time-consuming. Therefore, we aim to simplify this process by attaching the optical fibres to the vessel’s surface. This method is significantly more timeefficient than the integration process and can be applied to any vessel. Our results demonstrate that surface-applied fibre optic sensors can detect and precisely localise damage.&#13;
Additionally, signs of damage can be recognised even before the damage occurs. Predictive maintenance using fibre optic sensors could reduce premature maintenance costs and periodic inspections while increasing safety and extending the vessel’s useful service life. The role of machine learning in predictive maintenance is also discussed.</abstract>
    <parentTitle language="eng">Proceedings of the 20th Sensors &amp; their Applications Conference</parentTitle>
    <enrichment key="eventName">20th Sensors &amp; their Applications Conference</enrichment>
    <enrichment key="eventPlace">Limerick, Ireland</enrichment>
    <enrichment key="eventStart">11.08.2024</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="eventEnd">14.0/8.2024</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Christos Karapanagiotis</author>
    <author>Marcus Schukar</author>
    <author>Mathias Breithaupt</author>
    <author>Katerina Krebber</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fiber optic sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Composites</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Structural health monitoring</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.6 Faseroptische Sensorik</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="themenfelder" number="">Wasserstoff</collection>
  </doc>
  <doc>
    <id>61894</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>NDT.net</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data</title>
    <abstract language="eng">In this paper, we report on a sensor network for structural health monitoring (SHM) of Type IV composite overwrapped pressure vessels (COPVs) designed for hydrogen storage. The sensor network consists of three different SHM sensing technologies: ultrasonic guided waves (GW), acoustic emission (AE) testing, and distributed fiber optic sensors (DFOS). We present an experimental setup for a lifetime test, where a COPV is subjected to cyclic loading. Data from all sensors are collected and centrally evaluated. The COPV failed after approximately 60,000 load cycles, and the sensor network proved capable of detecting and localizing the damage even before the failure of the COPV. This multi-sensor approach offers significantly more channels of information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including artificial intelligence (AI)-based evaluation. This not only has a positive effect on operational c</abstract>
    <parentTitle language="eng">Research and Review Journal of Nondestructive Testing (ReJNDT)</parentTitle>
    <identifier type="doi">10.58286/30513</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-618948</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Christos Karapanagiotis</author>
    <author>Jan Heimann</author>
    <author>Eric Duffner</author>
    <author>Amir Charmi</author>
    <author>Marcus Schukar</author>
    <author>Seyedreza Hashemi</author>
    <author>Jens Prager</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ffiber optic sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Acoustic emission</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Guided waves</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Digital twin</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Structural health monitoring</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.4 Akustische und elektromagnetische Verfahren</collection>
    <collection role="institutes" number="">8.6 Faseroptische Sensorik</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">3.5 Sicherheit von Gasspeichern und Gefahrguttanks</collection>
    <collection role="themenfelder" number="">Wasserstoff</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/61894/Towards_predictive_maintenance_of_hydrogen_pressure_vessels_based_on_multi-sensor_data.pdf</file>
  </doc>
  <doc>
    <id>60310</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>NDT.net</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels</title>
    <abstract language="eng">We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for automotive use. The paper deals with the condition monitoring of such composite pressure vessels (CPVs) using the optical backscatter reflectometry (OBR) applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the polymer liner during the manufacturing process of the carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors can be an opportunity for monitoring the material degradation of CPVs under static and cyclic loading.</abstract>
    <parentTitle language="eng">Conference Proceedings - Prepublication</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:b43-603105</identifier>
    <enrichment key="eventName">11th European Workshop on Structural Health Monitoring</enrichment>
    <enrichment key="eventPlace">Potsdam, Germany</enrichment>
    <enrichment key="eventStart">10.06.2024</enrichment>
    <enrichment key="eventEnd">13.06.2024</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Aleksander Wosniok</author>
    <author>Marcus Schukar</author>
    <author>Paul Woody</author>
    <author>Bin Wang</author>
    <author>Mathias Breithaupt</author>
    <author>Andreas Kriegsmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fiber optic sensor</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Distributed strain sensing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Composite pressure vessel</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Structural health monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fiber-reinforced plastics</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.6 Faseroptische Sensorik</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">3.5 Sicherheit von Gasspeichern und Gefahrguttanks</collection>
    <collection role="themenfelder" number="">Wasserstoff</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/60310/EWSHM_H2_DFOS_manuscript.pdf</file>
  </doc>
  <doc>
    <id>60276</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>NDT.net</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Towards predictive maintenance of hydrogen pressure vessels based on multi-sensor data fusion and digital twin modeling</title>
    <abstract language="eng">Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin.</abstract>
    <parentTitle language="eng">Proceedings of the 11th European Workshop on Structural Health Monitoring</parentTitle>
    <identifier type="url">https://www.ndt.net/search/docs.php3?id=29702</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-602764</identifier>
    <enrichment key="eventName">11th European Workshop on Structural Health Monitoring</enrichment>
    <enrichment key="eventPlace">Potsdam, Germany</enrichment>
    <enrichment key="eventStart">10.06.2024</enrichment>
    <enrichment key="eventEnd">13.06.2024</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Christos Karapanagiotis</author>
    <author>Jan Heimann</author>
    <author>Eric Duffner</author>
    <author>Amir Charmi</author>
    <author>Marcus Schukar</author>
    <author>Seyedreza Hashemi</author>
    <author>Jens Prager</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Acoustic emission</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Ultrasonic guided waves</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fiber optic sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Pressure vessels</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Structural health monitoring</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.4 Akustische und elektromagnetische Verfahren</collection>
    <collection role="institutes" number="">8.6 Faseroptische Sensorik</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">3.5 Sicherheit von Gasspeichern und Gefahrguttanks</collection>
    <collection role="themenfelder" number="">Wasserstoff</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/60276/ml_504_1713201190 (2).pdf</file>
  </doc>
  <doc>
    <id>60273</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>7</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>NDT.net</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing</title>
    <abstract language="eng">We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future.</abstract>
    <parentTitle language="eng">Proceedings of the 11th European Workshop on Structural Health Monitoring</parentTitle>
    <identifier type="url">https://www.ndt.net/search/docs.php3?id=29701</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-602731</identifier>
    <enrichment key="eventName">11th European Workshop on Structural Health Monitoring</enrichment>
    <enrichment key="eventPlace">Potsdam, Germany</enrichment>
    <enrichment key="eventStart">10.06.2024</enrichment>
    <enrichment key="eventEnd">13.06.2024</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Christos Karapanagiotis</author>
    <author>Marcus Schukar</author>
    <author>Mathias Breithaupt</author>
    <author>Eric Duffner</author>
    <author>Alexander Ulbricht</author>
    <author>Jens Prager</author>
    <author>Katerina Krebber</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hydrogen</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fiber optic sensors</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Composites</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Structural health monitoring</value>
    </subject>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.4 Akustische und elektromagnetische Verfahren</collection>
    <collection role="institutes" number="">8.5 Röntgenbildgebung</collection>
    <collection role="institutes" number="">8.6 Faseroptische Sensorik</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">3.5 Sicherheit von Gasspeichern und Gefahrguttanks</collection>
    <collection role="themenfelder" number="">Wasserstoff</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/60273/503_manuscript.pdf</file>
  </doc>
</export-example>
