fosanalysis 0.3

A framework to evaluate distributed fiber optic sensor data

fosanalyis – 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

A quick guide on how to use this framework is provided in Getting Started. To build the full documentation, run doxygen in the root directory of the project (this directory) and it will generate it 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, please cite this paper:

@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},
  language        = {english},
}

Licence and Copyright

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