TimesSeriesStreaming.VI: LabVIEW program for reliable data streaming of large analog time series

Fabian Czerwinski; Lene Broeng Oddershede

doi:10.1016/j.cpc.2010.10.019

TimesSeriesStreaming.VI: LabVIEW program for reliable data streaming of large analog time series

Fabian Czerwinski, Lene Broeng Oddershede

Biokompleksitet

6 Citationer (Scopus)

Abstract

With modern data acquisition devices that work fast and very precise, scientists often face the task of dealing with huge amounts of data. These need to be rapidly processed and stored onto a hard disk. We present a LabVIEW program which reliably streams analog time series of MHz sampling. Its run time has virtually no limitation. We explicitly show how to use the program to extract time series from two experiments: For a photodiode detection system that tracks the position of an optically trapped particle and for a measurement of ionic current through a glass capillary. The program is easy to use and versatile as the input can be any type of analog signal. Also, the data streaming software is simple, highly reliable, and can be easily customized to include, e.g., real-time power spectral analysis and Allan variance noise quantification.

Originalsprog	Engelsk
Tidsskrift	Computer Physics Communications
Vol/bind	182
Udgave nummer	2
Sider (fra-til)	485-489
Antal sider	4
ISSN	0010-4655
DOI	https://doi.org/10.1016/j.cpc.2010.10.019
Status	Udgivet - 1 feb. 2011

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10.1016/j.cpc.2010.10.019

Citationsformater

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title = "TimesSeriesStreaming.VI: LabVIEW program for reliable data streaming of large analog time series",

abstract = "With modern data acquisition devices that work fast and very precise, scientists often face the task of dealing with huge amounts of data. These need to be rapidly processed and stored onto a hard disk. We present a LabVIEW program which reliably streams analog time series of MHz sampling. Its run time has virtually no limitation. We explicitly show how to use the program to extract time series from two experiments: For a photodiode detection system that tracks the position of an optically trapped particle and for a measurement of ionic current through a glass capillary. The program is easy to use and versatile as the input can be any type of analog signal. Also, the data streaming software is simple, highly reliable, and can be easily customized to include, e.g., real-time power spectral analysis and Allan variance noise quantification.",

author = "Fabian Czerwinski and Oddershede, {Lene Broeng}",

year = "2011",

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doi = "10.1016/j.cpc.2010.10.019",

language = "English",

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journal = "Computer Physics Communications",

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AU - Czerwinski, Fabian

AU - Oddershede, Lene Broeng

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Y1 - 2011/2/1

N2 - With modern data acquisition devices that work fast and very precise, scientists often face the task of dealing with huge amounts of data. These need to be rapidly processed and stored onto a hard disk. We present a LabVIEW program which reliably streams analog time series of MHz sampling. Its run time has virtually no limitation. We explicitly show how to use the program to extract time series from two experiments: For a photodiode detection system that tracks the position of an optically trapped particle and for a measurement of ionic current through a glass capillary. The program is easy to use and versatile as the input can be any type of analog signal. Also, the data streaming software is simple, highly reliable, and can be easily customized to include, e.g., real-time power spectral analysis and Allan variance noise quantification.

AB - With modern data acquisition devices that work fast and very precise, scientists often face the task of dealing with huge amounts of data. These need to be rapidly processed and stored onto a hard disk. We present a LabVIEW program which reliably streams analog time series of MHz sampling. Its run time has virtually no limitation. We explicitly show how to use the program to extract time series from two experiments: For a photodiode detection system that tracks the position of an optically trapped particle and for a measurement of ionic current through a glass capillary. The program is easy to use and versatile as the input can be any type of analog signal. Also, the data streaming software is simple, highly reliable, and can be easily customized to include, e.g., real-time power spectral analysis and Allan variance noise quantification.

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DO - 10.1016/j.cpc.2010.10.019

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SP - 485

EP - 489

JO - Computer Physics Communications

JF - Computer Physics Communications

IS - 2

ER -

TimesSeriesStreaming.VI: LabVIEW program for reliable data streaming of large analog time series

Abstract

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