On-line characterization of wood chip brightness and chemical composition by means of visible and near-infrared spectroscopy

被引:7
作者
Hans, Guillaume [1 ]
Allison, Bruce [1 ]
机构
[1] FPInnovations, Smart Mfg, 2665 East Mall, Vancouver, BC V6T 1Z4, Canada
关键词
analyzer; chemical composition; near-infrared spectroscopy; non-destructive; on-line monitoring; wood chips; LIGNIN CONTENT; EUCALYPTUS-GLOBULUS; RAPID PREDICTION; BIOMASS; EXTRACTIVES; SELECTION; PULP; TEMPERATURE; SPECTRA; STORAGE;
D O I
10.1515/hf-2021-0027
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Historically, on-line and real-time measurement of wood chip properties in the pulp and paper industry has been a challenge and has hampered the development of advanced process control strategies. In this study, visible and near-infrared (VIS-NIR) spectroscopy is investigated as a means to characterize wood chip brightness and chemical composition (i.e. extractives, lignin and holocellulose content) on-line. The estimated standard error on the holocellulose reference measurement was significantly reduced using data reconciliation. VIS-NIR calibration models were developed using partial least square regression. Derivative and baseline correction were found to be the most appropriate pre-processing methods. Model desensitization to the influence of moisture content and temperature by means of external parameter orthogonalization resulted in more robust models critical for on-line applications under harsh industrial conditions. Wavelength selection improved model accuracy for all properties. A comparison of two different spectrometer and probe combinations demonstrated that, after wavelengths selection, a non-contact measurement of wood chips performs as well as a contact measurement of wood powder for monitoring chemical composition. On-line prediction of wood chip brightness and chemical composition using the developed VIS-NIR models was demonstrated over 7 months in a kraft pulp mill processing both hardwood and softwood chips.
引用
收藏
页码:989 / 1000
页数:12
相关论文
共 52 条
  • [1] Achiche S., 2005, P 91 ANN M PULP PAP
  • [2] Online prediction of pulp brightness using fuzzy logic models
    Achiche, Sofiane
    Baron, Luc
    Balazinski, Marek
    Benaoudia, Mokhtar
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2007, 20 (01) : 25 - 36
  • [3] Non-destructive prediction of the properties of forest biomass for chemical and bioenergy applications using near infrared spectroscopy
    Acquah, Gifty E.
    Via, Brian K.
    Fasina, Oladiran O.
    Eckhardt, Lori G.
    [J]. JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2015, 23 (02) : 93 - 102
  • [4] Allen L.H, 1987, MR116 FPINNOVATIONS
  • [5] ALLEN LH, 1991, J PULP PAP SCI, V17, pJ85
  • [6] [Anonymous], 2005, HDB WOOD CHEM WOOD C, DOI [DOI 10.1201/B12487, 10.1201/b12487]
  • [7] Axrup L, 2000, J CHEMOMETR, V14, P561, DOI 10.1002/1099-128X(200009/12)14:5/6<561::AID-CEM608>3.0.CO
  • [8] 2-2
  • [9] Benaoudia M., 2005, Patent No. [2447098A1, 2447098]
  • [10] RECONCILIATION OF PROCESS FLOW-RATES BY MATRIX PROJECTION .1. LINEAR CASE
    CROWE, CM
    CAMPOS, YAG
    HRYMAK, A
    [J]. AICHE JOURNAL, 1983, 29 (06) : 881 - 888