A Fiber Bragg Grating (FBG) biosensor with good biocompatibility promises label-free, anti-electromagnetic interference, and non-destructive detection of stress monitoring, it holds the potential to rapidly identify the stress changes in microfluidics systems. Based on signal processing, the correlation between wavelength shift in FBG and flowrate is discussed, an alternative to manual processing of wavelength offset calculation is analyzed, and the automatic selection of FBG wavelength change under high noise conditions is realized. In addition, we propose some technologies of intelligent processing algorithms such as machine learning (BP—back propagation neural network) and moving average. Finally, the feasibility and stability of the signal processing method are verified by experimental validation and multiple data sets testing. This study provides a promising intelligent information processing strategy for rapid and accurate stress sensing of microfluidics systems.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.