Study on the Signal Processing and Analysis System of Micro-Spectrometer

In order to study functions of spectral signal and intelligent spectrometer in materials analysis, this paper designs the signal processing and analysis test of micro-spectrometer. The study object is spectral signal. This paper deeply discusses about problems on signal processing and analysis techniques of micro- spectrometer, establishes a model structure of signal processing and analysis system of micro-spectrometer, deeply studies the selection of wavelength and spectral recognition problems, and puts forward corresponding algorithm and strategies. This paper also discusses the wavelength selection during quantitative analysis of spectral signal and puts forward the method for selecting segmented wavelength based on particle swarm optimization algorithm. Test results prove that this algorithm can be used to solve the subjective randomness for wavelength selection during quantitative analysis and complexity and slow convergence of the existing methods. In addition, this paper also researches the module transformation of spectral signal and puts forward that segmented direct correction method of support vector machine is used to solve data conversion problems of different spectrometers among measuring signals in different solutions under same measuring conditions, so as to provide basis for universality and comparability of measurement data of different spectrometers. It can be known herein that spectrum research experiment of micro-spectrometer lays a foundation for its application and development in each field in the future.