本实验室通过理论方程式,化学计量学和机器学习等方法分析复杂的光谱信息

成员

  • 教授. 土川 覚 [st3842@]
    木材工程,林产品科学,应用光学,农业工程
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  • 讲师. 稲垣 哲也 [inatetsu@]
    木材工程,应用光学,林产品科学
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  • 特任助教. 马 特 [mate@]
    木材工程,应用光学,林产品科学
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研究内容

木材和农产品等天然资源在我们的日常生活中发挥着极其重要的作用。但由于天然材料的形成包含复杂的理化过程,所以具有不同的材料特性。正如人与人之间存在的性格差异,生物材料同样存在着不同的“性格”(例如,不同树木之间其力学性质存在强、弱差异,不同桔子之间也存在甜、酸差异)。因此,为了满足消费者的实际需求,上述材料在生产和加工过程中需要高效无损的品质管理方法。

本研究室主要致力于运用波长比可视光略长的近红外光(人的肉眼其实看不到)对木材以及水果等农产品开展无损检测技术的开发。与此同时,我们的研究兴趣还包括“木材的精密机械加工”,“通过人为控制条件促进植物生产性能的提高”和“可塑性木质材料成型加工”。在上述领域,通过对可再生资源加工处理机械的开发及在线产品质量的非破坏检测技术的创新来减少对自然环境的压力。同样把看似矛盾的机械学和农学的概念有效地结合起来,针对可再生天然材料的高效利用方向开展独特研究。

近红外光谱在木质材料中的应用。

用近红外光谱结合新化学计量学方法或将现有分析技术融合,建立木材化学及物理性质的可靠预测模型。

关键词:近红外光谱法,木材,考古学,含水量,密度,热处理,人工林,力学性能

相关发表论文:

  • S. Tsuchikawa, “A Review of Recent Near Infrared Research for Wood and Paper”, Applied Spectroscopy Review ,42, 43-71(2007)
  • T. Inagaki, Y. Asanuma, S. Tsuchikawa, “Selective Assessment of Duplex Heat-Treated Wood by Near-Infrared Spectroscopy with Principal Component and Kinetic Analyses”, Journal of Wood Science, 64, 6-15 (2018).
  • V. T. H. Tham, T, Inagaki, S. Tsuchikawa, “A novel combined application of capacitive method and near-infrared spectroscopy for predicting the density and moisture content of solid wood”, Wood Science and Technology, 52, 115-129 (2018).
  • T. Inagaki, H. Yonenobu, Y. Asanuma, S. Tsuchikawa, “Determination of physical and chemical properties and degradation of archeological Japanese cypress wood from the Tohyamago area using near-infrared spectroscopy”, Journal of Wood Science, 64, 347-355 (2018).
  • I. A. Sofianto, T, Inagaki, K. Kato, M. Itoh, S. Tsuchikawa, “Modulus of elasticity prediction model on sugi (Cryptomeria japonica) lumber using online near-infrared (NIR) spectroscopic system”, International Wood Products Journal, 8, 193-200 (2017).

材料中光散射的研究

通过辐射转移理论,采用时间或空间分辨光谱学对样品中的复杂光散射现象开展研究。

基于上述实验和研究中获得的知识,促进新型的廉价便携检测设备开发。

关键词:优化散射系数,时间分辨光谱学,空间分辨光谱学,辐射传输理论,折射率失配,TFDRS(三纤维漫反射光谱)

相关发表论文:

  • M. Ban, T, Inagaki, T. Ma, S. Tsuchikawa, “Effect of cellular structure on the optical properties of wood”, Journal of Near Infrared Spectroscopy, 26, 53-60 (2018).
  • T. Ma, G. Schajer, Z. Pirouz, T. Inagaki, S. Tsuchikawa, “Optical characteristics of Douglas fir at various densities, grain directions, and thicknesses investigated by Near-Infrared Spatially Resolved Spectroscopy (NIR-SRS)”, Holzforschung, 72, 789-796 (2018).
  • T. Ma, T. Inagaki, M. Ban, S. Tsuchikawa, “Rapid identification of wood species by near infrared spatially-resolved spectroscopy (NIR-SRS) based on hyperspectral imaging (HSI)”, Holzforschung, 73, 323-330(2018).
  • R. Kitamura, T. Inagaki, S. Tsuchikawa, “Determination of true optical absorption and scattering coefficient of wooden cell wall substance by time-of-flight near infrared spectroscopy”, Optic Express, 24, 3999-4009, (2016).
  • K. Konagaya, T. Inagaki, R. Kitamura, S. Tsuchikawa, “Optical properties of drying wood studied by time-resolved near-infrared spectroscopy”, Optic Express, 24, 9561-9573, (2016).
  • T. Inagaki, D. Nozawa, Y. Shimomura, S. Tsuchikawa, “Three fiber-based diffuse reflectance spectroscopy for estimation of total solid content in natural rubber latex”, Journal of Near Infrared Spectroscopy, 24, 327-335 (2016).

近红外高光谱成像的成像分析

运用化学计量学和机器学习技术为近红外高光谱成像数据建立稳健可靠的校准,并通过神经网络深度学习对其进行高精度画像识别。

关键词:高光谱成像,机器学习,化学计量学,深度学习,CNN(卷积神经网络)

相关发表论文:

  • H. Kanayama, T. Ma, S. Tsuchikawa, T. Inagaki, “Cognitive spectroscopy for wood species identification: Near infrared hyperspectral imaging combined with convolutional neural network”, Analyst 144,6438-6446 (DOI: 10.1039/C9AN01180C
  • T. Ma, X. Li, T. Inagaki, H. Yang, S. Tsuchikawa, “Noncontact Evaluation of Soluble Solids Content in Apples by Near-Infrared Hyperspectral Imaging”, Journal of Food Engineering, 224, 53-61 (2018).
  • T. Ma, T. Inagaki, S. Tsuchikawa, “Calibration of SilviScan data of Cryptomeria japonica wood concerning density and microfibril angles with NIR hyperspectral imaging with high spatial resolution”, Holzforschung, 71, 341-347 (2017).
  • H. Yang, T. Inagaki, T. Ma, S. Tsuchikawa, “High-Resolution and Non-destructive Evaluation of the Spatial Distribution of Nitrate and Its Dynamics in Spinach (Spinacia oleracea L.) Leaves by Near-Infrared Hyperspectral Imaging”, frontiers in Plant Science, 8, 1937 (2017).

基于太赫兹的木质材料评估

基于太赫兹光谱技术对工程木质复合材性能的无损检测(晶体结构,含水量,密度,纤维取向)

关键词:太赫兹时域光谱,有效介质理论,纤维素晶体结构,MFA(微纤维角)

相关发表论文:

  • H. Wang, T. Inagaki, I. D. Hartley, S. Tsuchikawa, M. Reid, “Determination of dielectric function of water in THz region in wood cell wall result in an accurate prediction of moisture content”, International Journal of Infrared and Millimeter Waves,40,6,673-687(2019)
  • T. Inagaki, B. Ahmed, I.D. Hartley, S. Tsuchikawa S. and M. Reid, “Simultaneous Prediction of Density and Moisture Content of Wood by Terahertz Time Domain Spectroscopy”, Journal of Infrared Millimeter and Terahertz Wave, 35, 949-961 (2014)
  • T. Inagaki, I.D. Hartley, S. Tsuchikawa and M. Reid, “Prediction of Oven-dry Density of Wood by Time-domain Terahertz Spectroscopy”, Holzforschung, 68, 61-68 (2014).

 

名古屋大学大学院生命农学研究科

生物系统工学研究室

Na464-8601日本名古屋市千种区不老町

TEL:052-789-4157

FAX:052-789-4157

东山校区

从名古屋站:

乘坐地铁东山线到本山站。 (15分钟)。

然后换乘地铁名城线至名古屋大学站。 (东山校区就在地铁出口旁。)

 

从日本中部国际机场:

乘坐名铁线到金山站。 (30分钟。)

然后换乘地铁名城到名古屋大学站。 (21分钟)