Pretreatment of near-infrared spectroscopy of wood based on wavelet compression
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摘要: 近红外光谱数据维数多、数据量大,直接保存需要庞大储存空间,且海量数据会对网络化在线检测的分析速度和准确性产生影响。为探讨应用小波压缩进行近红外光谱预处理的可行性及其对枫桦木材密度预测精度的影响,通过强光探头采集木材圆盘的近红外光谱,在Matlab软件中应用小波变换法对枫桦木材密度近红外光谱数据进行压缩。结果表明:当小波基sym2分解层为6时,基于均衡稀疏标准形式的全局硬阈值压缩效果最好,将2 151个变量压缩成38个小波系数,其能量保留成分、零系数成分、压缩比分别为99.66%、98.34%、56.61%。用未处理光谱数据和压缩后的38个小波系数分别建立偏最小二乘定标分析模型,同时做内部交叉验证,并用未处理和压缩后的预测集做外部检验,得知压缩后校正模型对压缩后样品预测能力较好,预测决定系数为0.913 9。因此,小波压缩可有效简化近红外光谱数据,提高近红外光谱对枫桦木材密度的预测精度。Abstract: Due to the multi-dimension of near infrared spectrum (NIRS) and large volume of data, huge storage space is needed for data processing, which directly affects the speed and accuracy of online data analysis. This study aims to discuss the feasibility of pretreatment of near-infrared spectroscopy of wood based on wavelet compression as well as its effect on prediction accuracy of Betula costata Trautv wood density using NIR technology. The NIRS data of B. costata wood were compressed using wavelet transform algorithm with the aid of Matlab. Results showed that the global threshold value based on balance sparsity norm and the heuristic threshold value were observed to be the best with decomposition layer of 6 for the sym2 wavelet. With the method, the 2 151 variables were compressed into 38 wavelet coefficients, and the corresponding energy reserved component, zero coefficient component and compression ratio were 99.66%, 98.34% and 56.61%, respectively. The partial least squares (PLS) models were developed based on both the original NIRS and the 38 wavelet coefficients after compression. The inner cross validation was used and the external validation was applied to both the original and the compressed dataset. The best prediction results were associated with the calibration model developed with the compressed NIR data with determination coefficient (R2) of 0.913 9. This study indicates that the wavelet compression method could effectively simplify NIRS data and improve the prediction accuracy.
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Key words:
- NIRS /
- wavelet compression /
- Betula costata Trautv /
- wood density
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