Determination of the ash content, volatile matter and calorific value in coal with laser-induced breakdown spectroscopy (LIBS) is significantly affected by the matrix effect, due to the physical and chemical properties of different types of coals. This work aimed to achieve more accurate determination of the ash content, volatile matter and calorific value via the classification of coal samples by their ash contents. The support vector machine (SVM) classification method, which was optimized by using a genetic algorithm (GA), was used to classify the coal samples into three categories. And then, the partial least squares regression (PLSR) was employed to establish different models for each type of coal. With this detailed classification scheme, the coefficient of determination (R²) of the training set and test set of volatile matter was improved from 0.9269 and 0.9310 to 0.9959 and 0.9888, respectively. The root-mean-square error of cross-validation (RMSECV) and the root-mean-square error of prediction (RMSEP) of volatile matter were also reduced from 1.9940% and 1.8320% to 0.4989% and 0.7719%, respectively. The results of the ash content and calorific value are also improved. This work demonstrated that this LIBS-based quantitative analysis method can be widely used in the coal industry to improve current coal property analysis.

A hybrid model based on a wavelet threshold de-noising (WTD) and recursive feature elimination with cross-validation (RFECV) method was proposed to improve the measurements in quantitative analysis of coal properties using laser-induced breakdown spectroscopy (LIBS). First, a modified threshold of WTD was proposed based on wavelet coefficient theory. Interference of noise in the LIBS spectrum was reduced by using this modified method. Then, the RFECV method was applied to extract effective features from the de-noised LIBS spectrum. Finally, support vector regression (SVR) models of coal properties were established by the selected features. A validation set was used to verify the effectiveness and robustness of the hybrid model. The improvement of the hybrid model on the quantitative analysis of each index of coal properties (heat value, ash, volatile content) was studied and discussed. By using the proposed model, the determination coefficient ( R 2 ), root mean square error of prediction, average relative error, and relative standard deviation were all significantly improved over the original spectra model. The results demonstrated that the proposed model could effectively improve the accuracy and precision of LIBS quantitative analysis for coal properties.

The influences of the focusing geometry and axial focusing position of the second laser pulse on orthogonal double-pulse LIBS were investigated.

By using a kind of simple Michelson-type lateral shearing interferometry, in this paper, the precise quantitative phase measurement of transparent microscopic objects is realized successfully. For this interferometry, on the basis of the fundamental structure of the traditional Michelson interferometer, the two plane mirrors are replaced with two ordinary right-angle prisms. In the beginning, the ridges of the two right-angle prisms are set to align with the optical axis and be in the vertical direction. Subsequently, to achieve the lateral shear, one of these two right-angle prisms is rotated around its ridge. Furthermore, the goal to obtain more lateral shear can be achieved by introducing a bigger rotating angle or rotating another prism simultaneously. In addition, owing to the simple structure of the Michelson interferometer and the inexpensive optical components used, the system is compact, portable, easy to operate, and low cost. The experimental results show the practicability of this system.