fosanalysis 0.5

A framework to evaluate distributed fiber optic sensor data

fosanalysis – A framework to evaluate distributed fiber optic sensor data

Fiber optic sensors make quasi-continuous strain measurements possible, due to their high spatial resolution. Therefore, this measurement technique has great potential for structural health monitoring. The rich data enables valuable insights, e.g., for monitoring crack widths or global deformations. Aggregating this data to information requires efficient and scientifically substantiated algorithms. This project provides a framework for analyzing distributed fiber optic sensor data with the focus on crack width calculation.

fosanalysis is developed under Python 3.9 and is available in the Python Package Index (PyPI). To install the latest stable version, please run (or equivalent in your IDE):

• Linux and Mac: python3 -m pip install -U fosanalysis
• Windows: py -m pip install -U fosanalysis

The documentation for the most recent release is available here. A quick guide on how to use this framework is provided in Getting Started. To build the documentation yourself, run doxygen in the root directory of the project (this directory). The generated files will available in the directory ./Documentation/.

See CONTRIBUTING for details on how to contribute to fosanalysis.

Overview of news is given in CHANGELOG.

If you use this framework, you might want to cite these papers:

@Article{Richter_2023_CrackMonitoringConcrete,
  author          = {Richter, Bertram and Herbers, Max and Marx, Steffen},
  date            = {2023},
  journaltitle    = {Structural Concrete},
  title           = {Crack monitoring on concrete structures with distributed fiber optic sensors---Toward automated data evaluation and assessment},
  doi             = {10.1002/suco.202300100},
  issn            = {1751-7648},
  journalsubtitle = {Journal of the fib},
  number          = {2},
  pages           = {1465--1480},
  volume          = {25},
  publisher       = {John Wiley \& Sons Ltd},
}

@Article{Richter_2024_Advancesdatapreprocessing,
  author       = {Richter, Bertram and Ulbrich, Lisa and Herbers, Max and Marx, Steffen},
  date         = {2024},
  journaltitle = {Sensors},
  title        = {Advances in Data Pre-Processing Methods for Distributed Fiber Optic Strain Sensing},
  doi          = {10.3390/s24237454},
  eid          = {7454},
  issn         = {1424-8220},
  number       = {23},
  volume       = {24},
  publisher    = {MDPI},
}

Licence and Copyright

Author: Bertram Richter, more see CONTRIBUTING.
Copyright: Copyright by the authors, 2023—2024.
License: This software is released under GPLv3, see LICENSE for details.