Dataset Open Access

Laser triangulation measurement for AFP monitoring

Sebastian Zambal


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.3372341</identifier>
  <creators>
    <creator>
      <creatorName>Sebastian Zambal</creatorName>
      <affiliation>PROFACTOR GmbH</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Laser triangulation measurement for AFP monitoring</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Automated Fiber Placement</subject>
    <subject>Laser Triangulation</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-08-20</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3372341</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="Cites">10.1117/12.2521739</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3372340</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This data set was acquired in the context of EU project ZAero. This project has received funding from the European Union&amp;rsquo;s Horizon 2020 research and innovation programme under grant agreement No 721362. Project duration: 2016/10/01 - 2019/09/30. This data set contains a HDF5 file with data used for evaluation in a SAMPE 2019 conference paper [1].&lt;/p&gt;

&lt;p&gt;The main data in this package is contained in a HDF5 file: zaeroFTD1.h5. There are two entries in this file:&lt;br&gt;
/raw: contains the raw laser range data as acuqired during AFP lay-up&lt;br&gt;
/seg: contains the manually defined segmentation that corresponds to the laser range data&lt;/p&gt;

&lt;p&gt;The data was acquired for preliminary test runs for AFP monitoring in the ZAero project. It contains different regions that correspond to the following labels (as defined in /seg):&lt;br&gt;
1 ... gap&lt;br&gt;
2 ... regular tow&lt;br&gt;
3 ... overlap&lt;br&gt;
4 ... fuzzball&lt;/p&gt;

&lt;p&gt;This data is mainly intended for testing of algorithms that perform defect detection on laser range images of AFP data.&lt;/p&gt;

&lt;p&gt;For more information about the HDF5 format, please visit the HDF5 Group website:&lt;br&gt;
https://www.hdfgroup.org/solutions/hdf5/&lt;/p&gt;

&lt;p&gt;An example for loading and visualizing the data in Python comes with this data set:&lt;br&gt;
readDataExample.py&lt;/p&gt;

&lt;p&gt;=====================================&lt;br&gt;
REFERENCES&lt;br&gt;
=====================================&lt;/p&gt;

&lt;p&gt;[1]&lt;br&gt;
@inproceedings{Zambal2019_SAMPE}&lt;br&gt;
&amp;nbsp; author&amp;nbsp;&amp;nbsp;&amp;nbsp; = {Sebastian Zambal and Christoph Heindl and Christian Eitzinger},&lt;br&gt;
&amp;nbsp; title&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; = {Machine Learning for CFRP Quality Control},&lt;br&gt;
&amp;nbsp; booktitle = {Conference of the Society for the Advancement of Material and Process Engineering (SAMPE), Nantes, France},&lt;br&gt;
&amp;nbsp; year&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; = {2019}&lt;br&gt;
}&lt;/p&gt;

&lt;p&gt;[2]&lt;br&gt;
@inproceedings{Zambal2019_QCAV,&lt;br&gt;
&amp;nbsp; author&amp;nbsp;&amp;nbsp;&amp;nbsp; = {Sebastian Zambal and Christoph Heindl and Christian Eitzinger and Josef Scharinger},&lt;br&gt;
&amp;nbsp; title&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; = {End-to-End Defect Detection in Automated Fiber Placement Based on Artifcially Generated Data},&lt;br&gt;
&amp;nbsp; booktitle = {Proc. SPIE 11172, Fourteenth International Conference on Quality Control by Artificial Vision, 111721G},&lt;br&gt;
&amp;nbsp; doi&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; = {DOI: 10.1117/12.2521739},&lt;br&gt;
&amp;nbsp; year&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; = {2019}&lt;br&gt;
}&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/721362/">721362</awardNumber>
      <awardTitle>Zero-defect manufacturing of composite parts in the aerospace industry</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
65
20
views
downloads
All versions This version
Views 6565
Downloads 2020
Data volume 5.5 MB5.5 MB
Unique views 5454
Unique downloads 1919

Share

Cite as