On-line monitoring of the buffer capacity of particleboard furnish by near-infrared spectroscopy

Control and Signal Acquisition System of Broad-Spectrum Micro-Near-Infrared Spectrometer Based on Dual Single Detector

Based on the scanning grating mirror developed by us, this paper presents a method for precise control of the scanning grating mirror and high-speed spectrum data acquisition. In addition, a system circuit of the scanning grating mirror control and a spectrum signal acquisition system were designed and manufactured. The final results of the experiment show that the control system successfully allowed the precise control of the swing of the scanning grating mirror and the acquisition system successfully carried out the high-speed acquisition and transmission of the spectrum and angle data. The spectrum detection range of the NIR spectrometer was 80–2532 nm. The overall resolution of the spectrum was better than 12 nm.

The Buffer Effect of Different Wood Species and the Influence of Oak on Panel Composites Binders

The buffer action of certain wood species can intensely affect the curing and hardening of some thermosetting wood adhesives. The present article presents a quantification of such buffering effects, determined under controlled conditions, in various wood species. The buffer capacity of oak has been found to be rather extreme and is likely to affect quite heavily the ability of urea-formaldehyde (UF) and melamine-urea-formaldehyde (MUF) wood panel adhesives in industrial operations. A variation of the buffer capacity of furnishes containing between 0% and 30% oak chips has been investigated. This was correlated with the internal bond (IB) strength of MUF bonded laboratory particleboards. The wood mixture buffering capacity increases with the oak content, while the panel IB strength decreases.

A Control and Detecting System of Micro-Near-Infrared Spectrometer Based on a MOEMS Scanning Grating Mirror

Based on the scanning grating mirror we developed, this paper presents a method of the precise control of a scanning grating mirror and of high-speed spectrum data detection. In addition, the system circuit of the scanning grating mirror control and spectrum signal detecting is designed and manufactured in this paper. The mirror control system includes a drive generator module, an amplitude detection module, a feedback control module, and a variable gain amplification (VGA) module; the detecting system includes a field programmable gate array (FPGA) main control module, a synchronous trigger module, an analog-digital conversion (ADC) module, and a universal serial bus (USB) interface module. The final results of the experiment show that the control system has successfully realized the precision control of the swing of the scanning grating mirror and that the detecting system has successfully realized the high-speed acquisition and transmission of the spectral signal and the angle signals. The spectrum has been reconstructed according to the mathematical relationship between the wavelength λ and the angle β of the mirror. The resolution of the spectrometer reaches 10 nm in the wavelength range of 800–1800 nm, the signal-to-noise ratio (SNR) of the spectrometer is 4562 at full scale, the spectrum data drift is 0.9% in 24 h, and the precision of the closed loop control is 0.06%.

Enhanced discrimination and calibration of biomass NIR spectral data using non-linear kernel methods

Rapid methods for the characterization of biomass for energy purpose utilization are fundamental. In this work, near infrared spectroscopy is used to measure ash and char content of various types of biomass. Very strong models were developed, independently of the type of biomass, to predict ash and char content by near infrared spectroscopy and multivariate analysis. Several statistical approaches such as principal component analysis (PCA), orthogonal signal correction (OSC) treated PCA and partial least squares (PLS), Kernel PCA and PLS were tested in order to find the best method to deal with near infrared data to classify and predict these biomass characteristics. The model with the highest coefficient of correlation and the lowest RMSEP was obtained with OSC-treated Kernel PLS method.

Extraction of information from laser-induced breakdown spectroscopy spectral data by multivariate analysis

Laser-induced breakdown spectroscopy (LIBS) is being proposed more and more as a high-throughput technology to assess the elemental composition of materials. When a specific element is of interest, semiquantification is possible by building a calibration model using the emission line intensity of this element for known samples. However, a unique element has usually more than one emission line, and there are many examples where several emission lines used in combination give dramatically better results than any of the individual variables used alone. With a multivariate approach, models can be constructed that take into account all the emission lines related to a specific element; therefore more robust models can be developed. In this work, chemometric methods such as principal component analysis and partial least squares are proposed to resolve and extract useful information from the LIBS spectral data collected on biological materials.