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dagghe / pyOMA2

Python module for conducting operational modal analysis
MIT License
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Correlation signal subsetbased SSI (CoS-SSI) #12

Open Ayubirad opened 7 months ago

Ayubirad commented 7 months ago

Dear @dagghe ,

I hope this message finds you well. As an admirer of your work on the Operational Modal Analysis (OMA) package on GitHub, I would like to propose an exciting enhancement that could significantly expand the package's capabilities and attract a wider user base. The proposed method, called correlation signal subset-based SSI (CoS-SSI), is specifically designed to handle free decay vibration data, which is currently not supported by most OMA packages.

Implementing CoS-SSI in your OMA package would provide users with a powerful tool for analyzing free decay vibration data, which is crucial in various applications such as structural health monitoring, damage detection, and modal testing. By incorporating this novel method, your package would stand out as one of the few offering comprehensive solutions for both ambient and free decay vibration analysis. I have attached these research articles that provides a detailed introduction to the CoS-SSI method, along with simulation and experimental case studies demonstrating its performance. These article also includes a clear description of the algorithm, which could serve as a valuable reference for the implementation process.

https://eprints.hud.ac.uk/id/eprint/35357/1/FINAL%20THESIS%20-%20Liu.pdf https://pure.hud.ac.uk/ws/portalfiles/portal/16499556/v20c_20190226_final.pdf https://downloads.hindawi.com/journals/sv/2019/6581516.pdf

Thank you for considering this proposal. I look forward to hearing your thoughts and discussing the potential of this exciting enhancement.

Best regards, Mohammad

dagghe commented 5 months ago

Dear @Ayubirad Sorry for the late reply. Unfortunately, we do not have time at the moment to look further into this. However, as this is an open-source project, you can always fork the repository, try to implement the algorithm (though it might be more of a method for the SSIcov algorithm) locally, and then submit a pull request. We are happy to help if you encounter difficulties or need any clarification, but this might be the quickest way to see this implemented as we are currently working towards a stable release by the end of the summer.