School of Technology, Beijing Forestry University, Beijing 100083, China.
Beijing Laboratory of Urban and Rural Ecological Environment, Beijing 100083, China.
Sensors (Basel). 2018 Jun 18;18(6):1963. doi: 10.3390/s18061963.
This article presents a non-destructive methodology to determine the modulus of elasticity (MOE) in static bending of wood through the use of near-infrared (NIR) spectroscopy. Wood specimens were obtained from growing in Northeast of China. The NIR spectra of specimens were acquired by using a one-chip NIR fiber optic spectrometer whose spectral range was 900~1900 nm. The raw spectra of specimens were pretreated by multiplication scatter correlation and Savitzky-Golay smoothing and differentiation filter. To reduce the dimensions of data and complexity of modeling, the synergy interval partial least squares and successive projections algorithm were applied to extract the characteristic wavelengths, which had closing relevance with the MOE of wood, and five characteristic wavelengths were selected from full 117 variables of a spectrum. Taking the characteristic wavelengths as input values, partial least square regression (PLSR) and the propagation neural network (BPNN) were implemented to establish calibration models. The predictive ability of the models was estimated by the coefficient of determination () and the root mean square error of prediction (RMSEP) and in the prediction set. In comparison with the predicted results of the models, BPNN performed better results with the higher of 0.91 and lower RMSEP of 0.76. The results indicate that it is feasible to accurately determine the MOE of wood by using the NIR spectroscopy technique.
本文提出了一种通过使用近红外（NIR）光谱法在静态弯曲中测定木材弹性模量（MOE）的无损方法。样本取自中国东北地区生长的木材。使用单芯片 NIR 光纤光谱仪采集样本的 NIR 光谱，其光谱范围为 900~1900nm。通过使用乘法散射相关和 Savitzky-Golay 平滑和差分滤波器对样本的原始光谱进行预处理。为了降低数据的维度和模型的复杂性，应用协同区间偏最小二乘法和连续投影算法提取与木材 MOE 密切相关的特征波长，从全谱的 117 个变量中选择了五个特征波长。以特征波长为输入值，实施偏最小二乘回归（PLSR）和传播神经网络（BPNN）以建立校准模型。通过确定系数（）和预测集的预测均方根误差（RMSEP）来评估模型的预测能力。与模型的预测结果相比，BPNN 的表现更好，其 更高，为 0.91，RMSEP 更低，为 0.76。结果表明，使用 NIR 光谱技术可以准确地确定木材的 MOE。
