Method and Application for Raman Spectra SNR Evaluation Based on Extreme Points Statistics
WANG Zi-ru1, LIU Ming-hui2, LIU En-kai1, DONG Zuo-ren2, CAI Sheng-wen1, YIN Lei1, LIU Feng1
1. Nanjing S&S Instruments Co., Ltd., (Mother Company), Nanjing 210046，China
2. Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
Abstract：In recent years, portable spectrometer technology has developed rapidly. Compared with the traditional spectrometer, CCD spectrometer in the spectral collection of the way there have been two changes: (1) The signal is superposed and integrated to generate the spectrum, and the traditional SNR estimation method cannot obtain the detector fluctuation by a single detection. (2) For the spectral noise, the detector responses to random fluctuations and scanning repetitive errors are transformed into differences in pixel response of the CCD detector, detector random noise and mode noise related to the resolution of the optical system. Therefore, it is of great practical significance to propose a more adaptive spectral quality assessment method based on the measured spectrum. According to the changes of Raman spectrometer detector, we analyze the components of the collected spectral signal, and put forward the noise model assumptions of CCD spectrometer on the basis of the analysis. According to this assumption, different signal extremum frequencies are used to separate different noise pixels and the noise frequency mode is numerically simulated. The simulation results are consistent with the assumptions. On the basis of this, we propose and experimentally validate the method for evaluating SNR of Raman spectroscopy to estimate spectral line noise through spectral line spacing. The method includes the following two steps: (1) Collecting multiple measured spectra for superposition, counting the number of spectral extreme points corresponding to different frequencies in the superposition process, and obtaining the statistical results to separate the environmental noise and dark noise in the spectrometer; (2)Applying the above separation results, the statistical average of the spectral line extreme points corresponding to the dark noise in the measured spectrum is calculated, and then the SNR is calculated according to the formula in the text. After the preliminary preparation of step (1), the method can evaluate the random noise of the CCD Raman spectrometer through a single spectrum and evaluate the spectral SNR. In this paper, three Raman spectroscopy systems with the same optical structure and different CCD detectors are used to experiment. By using this method, the spectral quality is controlled by setting the SNR threshold, and a uniform spectral curve is obtained. Based on the method proposed in this paper, the SNR is fitted to the synchronization overlapping average algorithm, and the goodness of fit is up to 98%. The method can be used to evaluate the performance of Raman spectrometer and acquire real-time quality control of Raman spectrum. Theoretical and experimental results show that for the CCD detector-based Raman spectrometer, the SNR can be obtained based on this method when determining the sample and the characteristic peak. The method can also be used to compare different configurations of Raman spectroscopy equipment and as a standard to control the quality of spectra.
王梓儒，刘铭晖，刘恩凯，董作人，蔡圣闻，殷 磊，刘 峰. 基于极值统计的拉曼光谱信噪比评估方法与应用[J]. 光谱学与光谱分析, 2019, 39(04): 1080-1085.
WANG Zi-ru, LIU Ming-hui, LIU En-kai, DONG Zuo-ren, CAI Sheng-wen, YIN Lei, LIU Feng. Method and Application for Raman Spectra SNR Evaluation Based on Extreme Points Statistics. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(04): 1080-1085.
[1] Esmondewhite K A, Cuellar M, Uerpmann C, et al. Analytical & Bioanalytical Chemistry, 2017, 409(3): 637.
[2] Ramasubramanyan N. Raman Spectroscopy for Bioprocess Operations，2016.
[3] Bartko A P. Identification of Mycoplasm Contamination in Biotechnology Production Using Raman Spectroscopy: WO, US9334520，2016.
[4] SUN Zhen-hua, YU Zhen-gang, HUANG Mei-zhen, et al(孙振华, 余镇岗, 黄梅珍, 等). Journal of Optoelectronics·Laser(光电子·激光), 2015，(6): 1132.
[5] JIANG Cheng-zhi(姜承志). PhD Thesis, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences(中国科学院长春光学精密机械与物理研究所博士论文), 2014.
[6] JIANG Cheng-zhi, SUN Qiang, LIU Ying, et al(姜承志, 孙 强, 刘 英, 等). Acta Optica Sinica(光学学报), 2014, 34(6): 0630001.
[7] Kashima N. Ieice Comex, 2014, 3(10): 300.
[8] FAN Xian-guang, WANG Xiu-fen, WANG Xin, et al(范贤光, 王秀芬, 王 昕, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(12): 4082.
[9] WANG Min, LI Ting-ting, CHANG Tian-ying, et al(王 敏, 李婷婷, 常天英, 等). Semiconductor Optoelectronics(半导体光电), 2014, 35(3): 527.
