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Dust accumulation is severe during coal mine excavation. Currently, research on the dust settlement law and optimization under mixed air flow control in fully mechanized excavation faces is not in-depth enough. Based on a hybrid air flow control system and relying on the fully mechanized excavation face of Shaanxi Coal Group Shenmu Ningtiaota Mining Co., Ltd., the influence of mixed air flow control parameters such as the distance from the pressure air outlet to the working face, the right angle of the pressure air outlet, the pressure air outlet diameter, the distance from the extraction air outlet to the working face, and the pressure extraction ratio on the dust settlement law is analyzed. As the distance between the pressure air outlet and the working face increases, the proportion of large particle dust in the cross-section of the personnel breathing zone on the return air sides and the driver's location first increases, then decreases, and then increases again. The proportion of small particle dust increases. As the right deviation angle of the air inlet increases, the proportion of large particle dust in the personnel breathing zone section on the return air sides and the driver's location changes significantly. As the diameter of the air inlet increases, the proportion of small particle dust in the driver's location section first increases, then decreases, and then increases again. The proportion of large particle dust in the personnel breathing zone section on the return air side first increases and then decreases. As the distance between the extraction air outlet and the working face increases, the proportion of large particle dust at the driver's location section first increases and then decreases. The proportion of small particle dust first increases and then decreases and then increases again. The particle size distribution of dust at the personnel breathing zone section on the return air side does not change much. As the pressure-pumping ratio increases, the proportion of small particle dust in the cross-section of the personnel breathing zone on return air sides and the driver's location decreases. Taking the above air flow control parameters as independent variables, the average concentration of total dust in the personnel breathing zone on the return air side and the average concentration of exhaled dust at the driver's location are the optimization objectives. A dust settlement optimization regression model is established, and the particle swarm optimization algorithm is used to solve the model. The optimal air flow control scheme is obtained. The distance between the pressure air outlet and the working face is 8.9 meters, the right angle of the compressed air outlet is 14.8°, the diameter of the compressed air outlet is 0.9 meters, the distance between the extraction air outlet and the working face is 4.3 meters, and the pressure-pumping ratio is 1.1. The experimental platform for dust settlement under wind flow control is built. The experimental results show that the error between the test values and the simulated values of the dust settlement optimization regression model is within 13%, which verifies the accuracy of the model. The optimized dust with particle sizes of 71-100 μm is significantly affected by the wind flow regulation parameters and settles in front of the roadheader. After optimization, the average dust concentration of total dust in the personnel breathing zone on the return air side and the average dust concentration at the driver's location decrease by 47.4% and 42.4%, respectively, indicating a significant dust reduction effect.

Based on the principle of light scattering, measuring dust concentration can only be done manually at fixed times and locations, with poor real-time performance. It can only detect dust mass concentration and cannot provide a range of particle size distribution. At present, research on dust particle detection based on image analysis mainly focuses on unilateral research on dust mass concentration or particle size distribution. It cannot achieve simultaneous detection of dust mass concentration and particle size distribution range. In order to solve the above problems, a method for detecting dust particles in excavation working face based on image analysis is proposed. It explores the relationship between image features and dust mass concentration and particle size distribution. By using a dust sample collection and image acquisition device, dust particle images are collected and the dust mass concentration at the time of image acquisition is obtained. An image processing algorithm for dust samples, is developed to extract parameters related to grayscale features, texture features, and geometric features of the image. The correlation analysis between the extracted image features and the measured dust mass concentration is performed, and the image features with high correlation is selected as parameters to establish a regression mathematical model. The method extracts the number of pixels in the dust particle object. Combining with the conversion coefficient, the method calculates the size and distribution range of the dust particle based on the geometric equivalent area diameter. The experimental results show that the average relative error between the measured dust mass concentration and the calculated values of the established image feature multiple nonlinear regression model mathematical model is 12.37%. The maximum relative error between the standard measured particle size and the geometric equivalent area size obtained from the particle size distribution is 8.63%, and the average relative error is 6.37%. This verifies the accuracy of the image feature based dust mass concentration regression mathematical model and the geometric equivalent area diameter distribution mathematical model.

Linear permanent magnet vernier generators offer a high capability of force density, making them appealing configurations for wave energy harvesting systems. In absolute terms, the performance of these machines is significantly influenced by the selection of slot/pole combinations based on the magnetic gearing effect. For the first time, this paper aims to investigate the impact of different gear ratios on a wide array of linear primary permanent magnet vernier machines (LPPMVMs) with different slot/pole combinations based on fair criteria to offer a more comprehensive understanding of gear ratio selection. To find the optimal number of slots and poles, the response surface methodology is adopted to obtain a robust design and make a fair comparison among LPPMVMs with optimum design characteristics using a cost‐effective approach for the fast and reliable optimisation process. The higher gear ratios result in higher thrust force capability. This will help establishing a new route toward faster develpment of advanced LPPMVMs. The power loss models of LPPMVMs are studied to predict their steady‐state and transient thermal behaviours, verifying their stability and safety, while a simple external forced convection method can be utilised. To verify the model, finite element analysis is exploited to confirm the electromagnetic and thermal analysis results and provide a more exhaustive investigation. [ABSTRACT FROM AUTHOR]