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Metadata

Name
Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit)
Repository
ZENODO
Identifier
doi:10.5281/zenodo.5185953
Description
General information on the data set

The dataset was generated with two different measurement systems at the ZeMA testbed for electromechanical cylinders.

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All relevant information can be found within the hdf5 file.

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Example for reading out the metadata of the hdf5 file in MATLAB:

# available structures inside file
dataset = 'axis11_2kHz_ZeMA_PTB_SI.h5';
h5disp(dataset)

% general attributes about file
attr = h5info(dataset).Attributes;
project = jsondecode(attr(1,1).Value)
person = jsondecode(attr(2,1).Value)
publication = jsondecode(attr(3,1).Value)
experiment = jsondecode(attr(4,1).Value)

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Example for reading out the metadata of the hdf5 file in Python:

import h5py
import json

# open file
h5file = h5py.File("axis11_2kHz_ZeMA_PTB_SI.h5", "r")

# general attributes about file
for key in h5file.attrs:
print(key)
val = json.loads(h5file.attrs[key])
for subkey, subval in val.items():
print(" ", subkey, " : ", subval)

# available structures inside file
h5file.visit(print)

# proper exit
h5file.close()

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Metadata output of the hdf5 file:


For the dataset:

HDF5 axis11_2kHz_ZeMA_PTB_SI.h5
Group '/'
Attributes:
'Project': '{
"fullTitle":"Metrology for the Factory of the Future",
"acronym":"Met4FoF",
"websiteLink":"www.met4fof.eu",
"fundingSource":"European Commission (EC)",
"fundingAdministrator":"EURAMET",
"funding programme":"EMPIR",
"fundingNumber":"17IND12",
"acknowledgementText":"This work has received funding within the project 17IND12 Met4FoF from the EMPIR program co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation program. The authors want to thank Clifford Brown, Daniel Hutzschenreuter, Holger Israel, Giacomo Lanza, Bj\u00f6rn Ludwig, and Julia Neumann fromPhysikalisch-Technische Bundesanstalt (PTB) for their helpful suggestions and support."
}'
'Person': '{
"dc:author":[
"Tanja Dorst",
"Maximilian Gruber",
"Anupam Prasad Vedurmudi"
],
"e-mail":[
"t.dorst@zema.de",
"maximilian.gruber@ptb.de",
"anupam.vedurmudi@ptb.de"
],
"affiliation":[
"ZeMA gGmbH",
"Physikalisch-Technische Bundesanstalt",
"Physikalisch-Technische Bundesanstalt"
]
}'
'Publication': '{
"dc:identifier":"10.5281/zenodo.5185953",
"dc:license":"Creative Commons Attribution 4.0 International (CC-BY-4.0)",
"dc:title":"Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit)",
"dc:description":"The data set was generated with two different measurement systems at the ZeMA testbed. The ZeMA DAQ unit consists of 11 sensors and the SmartUp-Unit has 13 differentsignals. A typical working cycle lasts 2.8s and consists of a forward stroke, a waiting time and a return stroke of the electromechanical cylinder. The data set does not consist of the entire working cycles. Only one second of the return stroke of every 100rd working cycle is included. The dataset consists of 4776 cycles. One row represents one second of the return stroke of one working cycle.",
"dc:subject":[
"dynamic measurement",
"measurement uncertainty",
"sensor network",
"digital sensors",
"MEMS",
"machine learning",
"European Union (EU)",
"Horizon 2020",
"EMPIR"
],
"dc:SizeOrDuration":"24 sensors, 4776 cycles and 2000 datapoints each",
"dc:type":"Dataset",
"dc:issued":"2021-09-10",
"dc:bibliographicCitation":"T. Dorst, M. Gruber and A. P. Vedurmudi : Sensor data set of one electromechanical cylinder at ZeMA testbed (ZeMA DAQ and Smart-Up Unit), Zenodo [data set], https://doi.org/10.5281/zenodo.5185953, 2021."
}'
'Experiment': '{
"date":"2021-03-29/2021-04-15",
"DUT":"Festo ESBF cylinder",
"identifier":"axis11",
"label":"Electromechanical cylinder no. 11"
}'

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Example for one sensor (BMA 280, acceleration) of the PTB SmartUp Unit (SUU) and one sensor of ZeMA DAQ (pressure):
HDF5 axis11_2kHz_ZeMA_PTB_SI.h5
Group '/PTB_SUU'
Group '/PTB_SUU/BMA_280'
Group '/PTB_SUU/BMA_280/Acceleration'
Attributes:
'qudt:hasQuantityKind': '[
"qudt:Acceleration",
"qudt:Acceleration",
"qudt:Acceleration"
]'
'misc': '{
"interpolation_scheme":"cubic"
}'
'si:unit': '"\\metre\\second\\tothe{-2}"'
'sosa:madeBySensor': '"BMA 280"'
'rdf:type': '"qudt:Quantity"'
Dataset 'qudt:standardUncertainty'
Size: 4766x1000x3
MaxSize: 4766x1000x3
Datatype: H5T_IEEE_F64LE (double)
ChunkSize: []
Filters: none
FillValue: 0.000000
Attributes:
'si:label': '[
"X acceleration uncertainty",
"Y acceleration uncertainty",
"Z acceleration uncertainty"
]'
Dataset 'qudt:value'
Size: 4766x1000x3
MaxSize: 4766x1000x3
Datatype: H5T_IEEE_F64LE (double)
ChunkSize: []
Filters: none
FillValue: 0.000000
Attributes:
'si:label': '[
"X acceleration",
"Y acceleration",
"Z acceleration"
]'
Group '/ZeMA_DAQ'
Group '/ZeMA_DAQ/Pressure'
Attributes:
'qudt:hasQuantityKind': '"qudt:Pressure"'
'sosa:madeBySensor': '"Festo VPPM"'
'si:unit': '"\\pascal"'
'rdf:type': '"qudt:Quantity"'
Dataset 'qudt:standardUncertainty'
Size: 4766x2000
MaxSize: 4766x2000
Datatype: H5T_IEEE_F64LE (double)
ChunkSize: []
Filters: none
FillValue: 0.000000
Attributes:
'si:label': '"Pneumatic pressure uncertainty"'
Dataset 'qudt:value'
Size: 4766x2000
MaxSize: 4766x2000
Datatype: H5T_IEEE_F64LE (double)
ChunkSize: []
Filters: none
FillValue: 0.000000
Attributes:
'si:label': '"Pneumatic pressure"'
'misc': '{
"raw_data":false,
"comment":"Converted from ADC values based on appropriate conversion."
}'
Data or Study Types
multiple
Source Organization
Unknown
Access Conditions
available
Year
2021
Access Hyperlink
https://doi.org/10.5281/zenodo.5185953

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