RESUMEN
The rapid determination of ore grade can improve the efficiency of beneficiation. The existing molybdenum ore grade determination methods lag behind the beneficiation work. Therefore, this paper proposes a method based on a combination of Visible-infrared spectroscopy and machine learning to rapidly determine molybdenum ore grade. Firstly, 128 molybdenum ores were collected as spectral test samples to obtain spectral data. Then 13 latent variables were extracted from the 973 spectral features using partial least square. The Durbin-Watson test and the runs test were used to detect the partial residual plots and augmented partial residual plots of LV1 and LV2 to determine the non-linear relationship between spectral signal and molybdenum content. Extreme Learning Machine (ELM) was used instead of linear modeling methods to model the grade of molybdenum ores because of the non-linear behavior of the spectral data. In this paper, the Golden Jackal Optimization of adaptive T-distribution was used to optimize the parameters of the ELM to solve the problem of unreasonable parameters. Aiming at solving ill-posed problems by ELM, this paper decomposes the ELM output matrix by using the improved truncated singular value decomposition. Finally, this paper proposes an extreme learning machine method based on a modified truncated singular value decomposition and a Golden Jackal Optimization of adaptive T-distribution (MTSVD-TGJO-ELM). Compared with other classical machine learning algorithms, MTSVD-TGJO-ELM has the highest accuracy. This provides a new method for rapid detection of ore grade in the mining process and facilitates accurate beneficiation of molybdenum ores to improve ore recovery rate.
RESUMEN
In this investigation, the bandgaps and nonreciprocal transmission of the nonlinear piezoelectric phononic crystal and elastic wave metamaterial are studied. Analytical solutions for the wave motion equations with the electro-mechanical coupling are obtained. According to the continuous conditions, the stop bands and transmission coefficients of both fundamental wave and second harmonic are derived by the stiffness matrix method. Some particular examples are presented to show the nonreciprocal transmission of the nonlinear elastic waves. Additionally, nonlinear ultrasonic experiments are applied to verify the theoretical analyses and numerical simulations. This work is intended to be helpful in the design and fabrication of devices of the elastic wave diode with piezoelectric materials.
RESUMEN
In this investigation, the non-reciprocal transmission in a nonlinear elastic metamaterial with imperfect interfaces is studied. Based on the Bloch theorem and stiffness matrix method, the band gaps and transmission coefficients with imperfect interfaces are obtained for the fundamental and double frequency cases. The interfacial influences on the transmission behaviour are discussed for both the nonlinear phononic crystal and elastic metamaterial. Numerical results for the imperfect interface structure are compared with those for the perfect one. Furthermore, experiments are performed to support the theoretical analysis. The present research is expected to be helpful to design tunable devices with the non-reciprocal transmission and diode behaviour of the elastic metamaterial.