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Raman Spectrum Image Aquisition And Processing System Based On DSP

Posted on:2020-12-10Degree:MasterType:Thesis
Country:ChinaCandidate:H Y JiangFull Text:PDF
GTID:2381330611998700Subject:Instrument Science and Technology
Abstract/Summary:PDF Full Text Request
When Raman spectroscopy is used for the detection of substances,there is no need to pretreat the samples,and the sample to be detected can be solid,liquid,gas,and any mixed form,and when the substance is detected by Raman spectroscopy,it does not need to touch the object to be tested,does not cause damage to the object to be tested,and has the advantages of simple operation,short measurement time,high sensitivity,etc.,and thus it is widely used for material identification and structural analysis.However,the Raman scattered light intensity is usually only 10-6 to 10-12 of the intensity of the excitation light,and far lower than the noise such as Rayleigh scattered light and external stray light.Therefore,to achieve the acquisition of Raman spectroscopy,the Raman spectroscopy system is required to have high sensitivity and strong noise suppression capability.At present,small Raman spectrometers mostly use CCD or CMOS as detectors,which can avoid the wavelength scanning process and obtain full-band Raman spectra at one time.But the detectors for detecting weak spectral signals such as Raman spectroscopy and fluorescence spectroscopy require high sensitivity and signal-to-noise ratio,the sensitivity of CCD or CMOS is much lower than that of photomultiplier tube,so CCD or CMOS is difficult to meet the requirements.Furthermore,the huge amount of computation in image data processing also puts forward higher requirements for the performance of the processor.This subject mainly aims at improving the Raman spectral image acquisition system of LMGPY-290,a small portable Raman spectrometer independently developed by our institute,which is not sensitive enough,exposure time is not long enough,and spectral responsiveness of near infrared light band is low.A new Raman spectrometer is developed by using CMOS image sensor with high sensitivity.A Raman spectral image acquisition system based on DSP is designed and developed to improve the reliability of Raman spectral data from the source and further improve the performance of Raman spectrometer.Firstly,a new spectral image acquisition system is designed.The Sony star-level high-sensitivity CMOS image sensor and Huawei Hi Silicon DSP is selected.The design and development of the image acquisition system was completed by using the Hi Silicon platform.The system realizes the control of parameters and the extension of exposure time,improves the sensitivity and signal-to-noise ratio of the spectral image acquisition system,and expands the spectral response range.Then,the composition and principle of the spectrometer are expounded,and the performance indexes such as blaze angle and dispersion rate of the spectroscopic system and their effects on the performance of the spectrometer are analyzed.A small portable Raman spectrometer is designed and built,and the spectrometer was debugged.Then,the characteristics of the noise of the spectral acquisition system are analyzed.Using the spectral processing methods such as space-time accumulation algorithm,background subtraction,frequency distribution filtering,etc.,the Lab VIEW-based Raman spectral image acquisition and data processing software system is developed to realize the real-time processing and display of Raman spectrum.Finally,experiments are carried out using 532 nm and 785 nm lasers as excitation light,and the experimental results are compared with the experimental results of the small-scale Raman spectrometer LMGPY-290 independently developed by the Institute.The experimental results show that the Raman spectrometer improved by this subject has less noise,higher signal-to-noise ratio,smoother spectral curve and clearer details,which improves the performance of the Raman spectrometer.
Keywords/Search Tags:Raman spectrometer, DSP, HiSilicon platform, Raman spectrum acquisition, LabVIEW
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