Detection of K in soil using time-resolved laser-induced breakdown spectroscopy based on convolutional neural networks

One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy (LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem, this paper investigated a combination of time-resolved LIBS and convolutional neural networks (CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R²_c=0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network (ANN), showing R²_v=0.6318 and the root mean square error of validation (RMSEV)=0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R²_v=0.7366 and RMSEV=0.7855. These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K. However, due to limited calibration samples, the two-dimensional models presented over-fitting. The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R²_v=0.9968 and RMSEV=0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.     

凝视型AOTF高光谱成像系统设计

以声光可调谐滤波器(AOTF)为分光元件,集成了一种凝视型AOTF高光谱成像系统.系统硬件由AOTF及其控制器、CCD近红外相机、镜头、计算机组成,系统软件采用VC++2010语言,调用机器视觉算法包HALCON10.0的库文件和AOTF的库文件,实现对AOTF控制器和相机操作的控制及高光谱图像预处理.所集成的AOTF的凝视型光谱成像系统能连续采集被测物体的高光谱图像,光谱段为550～1 000 nm,光谱分辨率为2～6 nm,图像分辨率为1392像素×1 040像素.     

Delta-Sigma调制器在电机电流高精度测量系统中的应用研究

Delta-SigmaAD转换技术是高分辨率应用中的一项通用技术之一,其广泛用于高信号完整度和电流隔离的交流电机电流测量系统中。提出了一种应用于交流电机电流测量系统中的Σ-ΔAD转换设计,并且对ADC解调和滤波,采用了Sinc^3数字抽取滤波器对其以滤波和抽取方式进行解调,其中Sinc^3数字抽取滤波器采用现场可编程门阵列(FPGA)来设计,实现了Σ-Δ调制器输出信号的高频滤波,实现了电机电流高精度隔离采样,满足了交流电机电流测量对采样精度和响应速度的要求。