Dataset supporting the University of Southampton Doctoral Thesis "Novel fibres for next-generation fibre optic gyroscopes"
Dataset supporting the University of Southampton Doctoral Thesis "Novel fibres for next-generation fibre optic gyroscopes"
Dataset supporting the University of Southampton Doctoral Thesis "Novel fibres for next-generation fibre optic gyroscopes".
This is an ensemble of all gyro data acquisition runs for the multicore IFOG (MCIFOG ) and the benchmark PM IFOG (Benchmark IFOG) described in the thesis. The conditions for each individual test data run is given in an excel workbook which tabulates all the relevant conditions for the run. The Readme file gives a further description of all the data files.
All data can be processed via the MATLAB scripts contained in the folder "Gyro Data Analysis".
Process data by updating the "main_dir" variable in the main script, "analyze_gyro_data_v8.m", to match the data folder which is to be processed.
The temperature log for a given run can be processed simultaneously by enabling the "use_thermal_data" option.
Descriptions of processing options and other analysis features is given in the comments of the MATLAB code.
A detailed description of the test configuration for each gyro run is given in the excel files:
"MCIFOG 1 Test Log.xlsx" and "PM Gyro Test Log.xlsx"
Some of the data included in this set is given in the following publication:
A. Taranta, A. Gillooly, V. I. Kopp, D. Neugroschl, M. Ibsen, C. Emslie, and J. Sahu, "Performance Characteristics of a Multicore Interferometric Fiber Optic Gyroscope Using a 7-Core Fiber," in 2020 DGON Inertial Sensors and Systems (ISS) (IEEE, 2020), pp. 1–20.
University of Southampton
Taranta, Austin Acker
7eae1d1a-8e8c-4e2c-8b38-00fefa4abbff
Taranta, Austin Acker
7eae1d1a-8e8c-4e2c-8b38-00fefa4abbff
Taranta, Austin Acker
(2024)
Dataset supporting the University of Southampton Doctoral Thesis "Novel fibres for next-generation fibre optic gyroscopes".
University of Southampton
doi:10.5258/SOTON/D3066
[Dataset]
Abstract
Dataset supporting the University of Southampton Doctoral Thesis "Novel fibres for next-generation fibre optic gyroscopes".
This is an ensemble of all gyro data acquisition runs for the multicore IFOG (MCIFOG ) and the benchmark PM IFOG (Benchmark IFOG) described in the thesis. The conditions for each individual test data run is given in an excel workbook which tabulates all the relevant conditions for the run. The Readme file gives a further description of all the data files.
All data can be processed via the MATLAB scripts contained in the folder "Gyro Data Analysis".
Process data by updating the "main_dir" variable in the main script, "analyze_gyro_data_v8.m", to match the data folder which is to be processed.
The temperature log for a given run can be processed simultaneously by enabling the "use_thermal_data" option.
Descriptions of processing options and other analysis features is given in the comments of the MATLAB code.
A detailed description of the test configuration for each gyro run is given in the excel files:
"MCIFOG 1 Test Log.xlsx" and "PM Gyro Test Log.xlsx"
Some of the data included in this set is given in the following publication:
A. Taranta, A. Gillooly, V. I. Kopp, D. Neugroschl, M. Ibsen, C. Emslie, and J. Sahu, "Performance Characteristics of a Multicore Interferometric Fiber Optic Gyroscope Using a 7-Core Fiber," in 2020 DGON Inertial Sensors and Systems (ISS) (IEEE, 2020), pp. 1–20.
Archive
MCIFOG_Data_Part_2.zip
- Dataset
Archive
MCIFOG_Data_Part_3.zip
- Dataset
Spreadsheet
MCIFOG_1_Test_Log.xlsx
- Dataset
Archive
Gyro_Data_Analysis.zip
- Dataset
Archive
MCIFOG_Data_Part_1.zip
- Dataset
Archive
Benchmark_IFOG_Data.zip
- Dataset
Text
D3066-README_for_Thesis_Dataset.txt
- Dataset
Show all 7 downloads.
More information
Published date: 2024
Identifiers
Local EPrints ID: 490369
URI: http://eprints.soton.ac.uk/id/eprint/490369
PURE UUID: 102e8011-8d26-4484-b62b-365453272a3c
Catalogue record
Date deposited: 23 May 2024 17:25
Last modified: 25 May 2024 01:54
Export record
Altmetrics
Contributors
Creator:
Austin Acker Taranta
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics