Title:
REAL-TIME SPECTRAL ANALYSIS THROUGH HIGH-SPEED SPECTRAL CLASSIFICATION
Document Type and Number:
WIPO Patent Application WO/2019/039313
Kind Code:
A1
Abstract:
The present invention pertains to spectral analysis in spectrometry, in particular, to improvement in spectral analysis technology through high-speed spectral classification. Disclosed is a spectral analysis device 10 which is provided with a measurement means 20 for measuring sample spectra of an object sample 30 and an analysis means 40 for analyzing the sample spectra, and which is for identifying a compound contained in the object sample 30, the spectral analysis device being characterized in that: the analysis means 40 has a library that has been arithmetically processed in advance; the library contains a plurality of compound groups into which the aforementioned compound is classified; the analysis means 40 is further provided with an analysis display unit 42; and the analysis display unit 42 displays, in real time, a compound group to which the aforementioned compound belongs, as an analysis progress or analysis result during the analysis of the sample spectra.
Inventors:
NAGAMORI KOSHI (JP)
AKAO KENICHI (JP)
TAMURA KOHEI (JP)
KANNO MIYUKI (JP)
NAGOSHI TOSHIYUKI (JP)
AKAO KENICHI (JP)
TAMURA KOHEI (JP)
KANNO MIYUKI (JP)
NAGOSHI TOSHIYUKI (JP)
Application Number:
PCT/JP2018/030028
Publication Date:
February 28, 2019
Filing Date:
August 10, 2018
Export Citation:
Assignee:
JASCO CORP (JP)
International Classes:
G01N21/27; G06N3/08
Foreign References:
| JP2016528496A | 2016-09-15 | |||
| US20170242234A1 | 2017-08-24 |
Other References:
KLAWUN, C. ET AL.: "Neural Network Assisted Rapid Screening of Large Infrared Spectral Databases", ANALYTICAL CHEMISTRY, vol. 67, no. 2, 15 January 1995 (1995-01-15), pages 374 - 378, XP055578731, DOI: 10.1021/ac00098a023
LE, B. T. ET AL.: "Coal analysis based on visible- infrared spectroscopy and a deep neural network", INFRARED PHYSICS & TECHNOLOGY, vol. 93, 11 July 2018 (2018-07-11), pages 34 - 40, XP085471468, Retrieved from the Internet DOI: doi:10.1016/j.infrared.2018.07.013
ACQUARELLI, J. ET AL.: "Convolutional neural networks for vibrational spectroscopic data analysis", ANALYTICA CHIMICA ACTA, vol. 954, 27 December 2016 (2016-12-27), pages 22 - 31, XP029879096, DOI: doi:10.1016/j.aca.2016.12.010
LIU, J. ET AL.: "Deep Convolutional Neural Networks for Raman Spectrum Recognition: A Unified Solution", ARXIV:1708.09022, 18 August 2017 (2017-08-18), pages 1 - 14, XP080955100, Retrieved from the Internet DOI: 10.1039/C7AN01371J
LE, B. T. ET AL.: "Coal analysis based on visible- infrared spectroscopy and a deep neural network", INFRARED PHYSICS & TECHNOLOGY, vol. 93, 11 July 2018 (2018-07-11), pages 34 - 40, XP085471468, Retrieved from the Internet
ACQUARELLI, J. ET AL.: "Convolutional neural networks for vibrational spectroscopic data analysis", ANALYTICA CHIMICA ACTA, vol. 954, 27 December 2016 (2016-12-27), pages 22 - 31, XP029879096, DOI: doi:10.1016/j.aca.2016.12.010
LIU, J. ET AL.: "Deep Convolutional Neural Networks for Raman Spectrum Recognition: A Unified Solution", ARXIV:1708.09022, 18 August 2017 (2017-08-18), pages 1 - 14, XP080955100, Retrieved from the Internet
Attorney, Agent or Firm:
IWAHASHI Yuji (JP)
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