This paper analyses several wavelength demodulation methods based on optical fiber Fabry-Perot tunable filter. In view of the shortcomings of these methods, we proposed a real-time data acquisition method and a simple and effective demodulation algorithm based on optical fiber Fabry-Perot tunable filter and set up a temperature sensing system. The sensing system consists of an FBG sensor part, a data acquisition part, a data demodulation part and a data display part, we introduce the operation of the data acquisition part by explaining how the hardware and software work. Then we introduce the method of data demodulation we proposed, and demonstrated the steps of data demodulation in detail. We test the performance of this data acquisition part by carrying out a temperature sensor experiment, and prove the effectiveness of the demodulation algorithm at the same time. In addition, most programming languages can implement this simple and effective algorithm.
We propose a real-time monitoring method for shield tunnel boring machine cutter wear based on chirped fiber Bragg grating (CFBG). We use the chirped fiber Bragg grating as the wear detection sensor. When the wear occurs at the end face of the wear detection sensor (the end face of chirped fiber Bragg grating), the grating area of the chirped fiber Bragg grating will shorten with the occurrence of wear, which causes the bandwidth of the grating reflection spectrum to be narrowed, and the correlation theory of the fiber Bragg grating is used to calculate the wear rate. Experimental data shows that the sensor can survive in the actual operating conditions of the shield tunnel boring machine. After calibration, measurement accuracy can less than 1mm, and it can be used for real time wear detection of large machinery, such as shield tunnel boring machine.
Technology for fluorescence spectral imaging of microscopic has made significant strides advantages in the past several
years. These advances have led to the enhanced choice of suitable diagnosis bases. Of course, fluorescence imaging can
facilitate the study of disease at the molecular level in vivo. And this type of optical imaging has enabled real-time
research to track cell movement, cell growth and other cell functions. With the addition of spectral imaging, fluorescence
spectral imaging could complete a so-called 4-dimension imaging for the object. The investigator can obtain either the
color imaging information or the information beyond it. The combination of both of them could show the relative
completeness message. For evolution of software tools to deal with the resulting high-dimensionality datasets, it is
necessary to find some effective and comparative reliable datasets analytical methods. In this paper, it also describes
some quantitative fluorescence in tissue and addresses further applications of fluorescence spectral imaging. It includes
MSE (Minimum Squared Error), PCA (Principal Components Analysis), ICA (Independent Component Analysis), FEA
(Finite-Element Analysis), wavelet theory and their applications. They are useful in intact animals for disease detection,
screening, diagnosis, treatment evaluation and drug development.
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