Research On Acquisition And Processing Of Multiscattering-Enhanced Optical Absorption Spectrum

In the detection process of low-concentration samples,the application of absorption spectrometry in low-concentration and high-precision detection is limited due to the problems of low concentration of analytes of interest,less useful information and larger noise.Compared with the traditional absorption spectrometry,multiscattering spectrometry can improve the optical path of light in the sample under test,thus improving the detection sensitivity and reducing the detection noise,and providing a new detection method for the detection of micro samples.Therefore,this paper proposes to use multiscattering method to enhance the signal of optical absorption spectrum,the wavelet analysis method and the improved bat algorithm optimization are used to obtain useful spectral information and improve the detection accuracy of the absorption spectrum.The main research contents include:1?This paper designs and constructs a spectrum acquisition system based on multiscattering-enhanced technology.With method of multiscattering-enhanced absorption,water phase monodisperse SiO₂ nanoparticles with different particle sizes were added into Cy3fluorescent dye solution to act as random scattering medium.In this way,multiple scattering of light is realized,the detection light path is increased,and the detection limit of Cy3 solution is greatly improved.It also provides a new method for the detection of absorption enhancement of small samples.2?In the process of spectral acquisition,the system noise introduced by the spectral acquisition equipment and the influence of the surrounding environment make the measured spectral signals often contain high-frequency noise,which reduces the credibility of the signal.The wavelet threshold method is used to deal with these noises.A new threshold function with good continuity,high order derivability and adjustable parameters is proposed.By adjusting the shape parameters of the new threshold function,it can be flexibly transformed between soft and hard threshold functions.The experimental simulation verifies that the de-noising effect of this threshold function is better than other traditional threshold functions,which improves the signal to noise ratio and reduces the mean square error.3?Aiming at the shortcomings of fixed threshold and threshold function shapes in the traditional threshold de-noising method,the wavelet threshold function is combined with the bat algorithm to propose a new de-noising method.An improved bat optimization algorithm for the problem that the traditional bat algorithm has strong dependence on the initial solution and is easy to be trapped in the local optimal solution.The method takes the mean square error between the original signal and the reconstructed signal as the objective function,and uses the improved bat algorithm to seek the optimal threshold value of each decomposition layer and the shape adjustment parameter of the improves threshold function adaptively.The de-noised signal is closer to the original signal,and the de-noising effect is effectively improved.