Influence of coal cowl parameters on the coal loading process of thin coal seam shearer drum.

The low loading rate of the thin coal seam shearer drum is a severe obstacle to the efficient mining of thin seam resources, and the auxiliary drum loading through the cowl is an effective measure to alleviate this situation. However, the working mechanism of the coal cowl still remains unclear. In this paper, with the help of the discrete element method and the modeling experiment method, the effects of coal cowl's offset distance, tilt angle and wrap angle on the coal loading rate under different loading modes of the drum are investigated; and the significance of various factors and their interactions to the drum coal loading rate is explored by designing response surface experiments. The findings show that a monotonous negative correlation between the offset distance of the coal cowl and the coal loading rate is identified, and that a smaller offset distance can effectively improve the coal loading rate of the drum. The conveying torque is significantly increased, easily inducing the drum choking, coal recycling coal over-crushing. Along with the increasing tilt angle, the rate of ejection loading decreases monotonically, and the rate of pushing loading increases first and then decreases. Coal loading rate is weakly affected by changes in coal cowl's wrap angle. The results of response surface analysis reveal that the most significant factors affecting the drum's coal loading rate are tilt angle and offset distance in ejection and pushing loading modes, respectively. The conclusions drawn here offer implications for improving the coal loading performance of the thin coal seam shearer drum, as well as certain guidance on the optimal design of coal cowl parameters.

Experimental study on shearer traction vibration considering attitude disturbances.

Due to the influence of structural clearances, the shearer's oscillates and jumps concerning the scraper are frequent, which induces the collision and vibration impact of the traction components and exacerbates the traction failure of the shearer. Therefore, to explore the correlation between attitude disturbance and traction vibration, an experiment on the traction vibration is carried out, the spatial swaying of the shearer and vibration differences between two traction components are obtained, the influence of the lifting angle of the rocker arm is discussed, and the influence mechanism of the shearer attitude disturbance on traction vibration is elucidated. The results indicate that the rolling swing intensity of the shearer is the highest while the yawing swing intensity is the lowest, and the pitch swing intensity increases with the increase of the lifting angle of the rocker arm. Besides, the vibration impact indices of the two walking mechanisms have a competitive relationship of one decreasing but the other increasing, which can be used as a reference signal to judge the rolling swing and load-sharing performance of the traction part. Moreover, with the swing attitude, the competitive relationship of the average of vibration peaks is shown in the two support shoes, and it can be used as a reference signal to judge the pitching swing and the load-sharing performance of the traction part. This result reveals the impact mechanism of attitude disturbances on traction vibration and proposes a signal monitoring approach for judging the traction attitude disturbance and load-sharing performance, providing a reference for reducing traction faults.

Interfacial dipole engineering in all-inorganic perovskite solar cells.

Severe nonradiative recombination and energy level mismatch in perovskite solar cells (PSCs) are key factors affecting efficiency. Here, we report an effective strategy for surface passivation and interfacial dipole engineering of perovskite films. By precisely introducing electron-withdrawing and electron-donating groups on 7-azaindole, we have effectively controlled the passivation ability of N atoms and the polarity of the interfacial dipole, thereby regulating the perovskite surface's work function and obtaining the optimal energy level matching. This strategy yields an impressive efficiency of 10.76% for the CsPbBr3 PSC and exceptional stability.

Coal-gangue recognition via multi-branch convolutional neural network based on MFCC in noisy environment.

Traditional coal-gangue recognition methods usually do not consider the impact of equipment noise, which severely limits its adaptability and recognition accuracy. This paper mainly studies the more accurate recognition of coal-gangue in the noise site environment with the operation of shearer, conveyor, transfer machine and other device in the process of top coal caving. Mel Frequency Cepstrum Coefficients (MFCC) smoothing method was introduced to express the intrinsic feature of sound pressure more clearly in the coal-gangue recognition site. Then, a multi-branch convolution neural network (MBCNN) model with three branches was developed, and the smoothed MFCC feature was incorporated into this model to realize the recognition of falling coal and gangue in noisy environment. The sound pressure signal datasets under the operation of different device were constructed through a great deal of laboratory and site data acquisition. Comparative experiments were carried out on noiseless dataset, single noise dataset and simulated site dataset, and the results show that our method can provide higher correct recognition accuracy and better robustness. The proposed coal-gangue recognition approach based on MBCNN and MFCC smoothing can not only recognize the state of falling coal or gangue, but also recognize the operational state of site device.

Effect of Gas Input Conditions and Ultrasound on the Dynamic Behavior of Flotation Bubbles.

Ultrasonic flotation is useful for fine low-rank coal purification; however, the efficiency of ultrasonic flotation still needs to be improved. Because the dynamic behavior of flotation bubbles has significant effects on their flotation efficiency, it was investigated under different gas input conditions with and without ultrasound using the volume of fluid method and h-speed imaging. The results indicated that the gas input method can influence the final kinetic behavior of the flotation bubbles by changing the morphology of the initial bubble. With an increase in the size and aspect ratio of the bubble, the bubble deformation and velocity increased, and the range of motion of the bubble increased and then decreased. Meanwhile, the size of the bubble increased with an increase in the thickness of the vibrating plate of the ultrasonic transducer owing to the aggregation of the bubbles under the influence of ultrasound.

Biomimetic superelastic sodium alginate-based sponges with porous sandwich-like architectures.

Design and fabrication of structurally optimized three-dimensional porous materials are highly desirable for engineering applications. Herein, through a facile bidirectional freezing technique, we prepared superelastic biomass sponges in air and underwater, which possess biomimetic porous sandwich-like architectures with lamellar layers interconnected by porous microstructures, similar to the structure of rice stems. This distinctive architecture was obtained by incorporating Typha orientalis fibers (TOFs) and graphene oxide (GO) nanosheets into sodium alginate (SA) matrix, in which SA flakes and GO nanosheets were intimately grown along TOFs. The porous sandwich-like microstructure allows stress to be distributed throughout the lamellar to avoid stress concentration and endows SA/TOFs/GO sponge with excellent mechanical compressibility and recoverability. Especially, underwater superelasticity and superoleophobicity of the sponge facilitates removal of water-miscible contaminants or oil/water separation with high efficiency. This novel strategy for the design biomimetic architecture of superelastic biomass sponge can promote its application for protecting environment.

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm.

In the present work, the working state of the crane leg is analyzed and discussed, and its structure is optimized. SolidWorks software is used for modeling; ANSYS software is used for finite element analysis. First of all, the constrained finite element method (CFEM) is used to analyze the linear eigenvalue buckling and geometric nonlinear buckling of outriggers with different cross-section shapes. Prove that the curved leg has certain advantages in buckling. At the same time, analyzing the leg along a different path of buckling condition and stress changes provide the basis for the design of the subsequent reinforcement. After selecting the best cross-section shape of the outrigger, the agent-based multi-island genetic algorithm is used to optimize the structural parameters of the outrigger under the transverse stiffened plate reinforced structure and the longitudinally stiffened plate reinforced structure respectively. It is proved that the outrigger with the transverse stiffened plate has a significant effect in improving the bearing capacity and in the lightweight of the structure. Finally, the gap between the movable leg and the fixed leg was changed, the stress of different gaps was analyzed by using the finite element method, and the appropriate gap value was selected according to the high-order fitting curve.

Rule-based expert system to assess caving output ratio in top coal caving.

Coal mining professionals in coal mining have recognized that the assessment of top coal release rate can not only improve the recovery rate of top coal, but also improve the quality of coal. But the process was often performed using a manual-based operation mode, which intensifies workload and difficulty, and is at risk of human errors. The study designs a assessment system to give the caving output ratio in top coal caving as accurately as possible based on the parameters adaptive Takagi-Sugeno (T-S) fuzzy system and the Levenberg-Marquardt (LM) algorithm. The main goal of the adaptive parameters based on LM algorithm is to construct its damping factor in the light of lowering of the objective function which is as taken as the index of termination iteration. The performance of the system is evaluated by Pearson correlation coefficient, Coefficient of Determination and relative error where the results of the Takagi-Sugeno method and the parameters adaptive Takagi-Sugeno method are compared to make the evaluation more robust and comprehensive.

The design and analysis of a new slipper-type hydraulic support.

To improve the safety and the stability of the support under mines and reduce the cost, we design a new slipper-type hydraulic support with energy-efficiency and high reliability. To study its dynamics, we build a reverse kinematics model. We analyze the motion and the force for each component of the new support with a simulation in Matlab/Simulink. The results show that it has appropriate structures with the required four-bar linkages. To compare the performance between the new slipper-type support and the traditional support, we design their mechanics models, deduce their mechanics relations and obtain the force curves for each component of both supports under the same loads. The results prove that the new slipper-type support has less demand on oil pressure for the hydraulic cylinder when working at middle and high positions and it has a larger supporting force and a higher supporting stability which would be more energy-efficient.