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Overstaffing production in underground coal mining is not convenient for daily management, and incomplete information of coal miners hinders the rescue process of firefighters during mine accidents. To address this safety sustainability issue, a novel face recognition method based on an improved multiscale neural network is proposed in this paper. A new depthwise separable (DS)-inception block is designed and a joint supervised loss function based on center loss theory is developed to construct a new multiscale model. The miniers can be recognized in the harsh underground environment during the life rescue. Experimental results show that the accuracy, recall and F1-score indexes of the proposed method for the miner face recognition in the underground mining environment are 97.26%, 94.17% and 95.42%, respectively. Transfer model with joint supervised loss can effectively improve the recognition accuracy by about 0.5–1.5%. In addition, the average recognition accuracy of the proposed face recognition method achieves to 91.34% and the miss detection rate is less than 5% in the dugout tunnel of coal mine.

In order to address the problems of insufficient load capacity and rotor vibration, an active fluid-film bearing lubricated with magnetorheological fluid (MRF) is proposed. First, the geometry of the MRF fluid-film bearing is designed and its intelligent lubrication mechanism is analyzed to clarify its advantages. In addition, mathematical model of MRF fluid-film bearing-rotor system is derived, and FEM model is utilized to obtain stiffness and damping coefficients to supplement mathematical model. Moreover, an improved gray wolf optimization (IGWO) algorithm is developed to tune the PID controller parameters. The validity of the proposed method is verified by numerical simulation. Furthermore, the simulation results show that with the increasing of current magnitude, the orbits of shaft center decrease. Under the presence of magnetic fields, the shaft center orbits of the MRF bearing can converge to a point, and therefore this bearing has ability to suppress rotor vibration. Finally, IGWO-PID controller has better response characteristics than GWO, PSO, and GA algorithms, and hence the IGWO algorithm can find the more appropriate PID controller parameters, that the validity of the improved algorithm is further proved. Therefore, the active bearing and its research findings provide new reference for MRF vibration control in the field of journal bearing lubrication.

As one of the main pieces of equipment in coal transportation, the belt conveyor with its detection system is an important area of research for the development of intelligent mines. Occurrences of non-coal foreign objects making contact with belts are common in complex production environments and with improper human operation. In order to avoid major safety accidents caused by scratches, deviation, and the breakage of belts, a foreign object detection method is proposed for belt conveyors in this work. Firstly, a foreign object image dataset is collected and established, and an IAT image enhancement module and an attention mechanism for CBAM are introduced to enhance the image data sample. Moreover, to predict the angle information of foreign objects with large aspect ratios, a rotating decoupling head is designed and a MO-YOLOX network structure is constructed. Some experiments are carried out with the belt conveyor in the mine’s intelligent mining equipment laboratory, and different foreign objects are analyzed. The experimental results show that the accuracy, recall, and mAP50 of the proposed rotating frame foreign object detection method reach 93.87%, 93.69%, and 93.68%, respectively, and the average inference time for foreign object detection is 25 ms.

Extraction of the laser fringe center line is a key step in the 3D reconstruction of linear structured light, the accuracy of which is directly related to the quality of the 3D model. A laser center line extraction method based on an improved gray center of gravity method is proposed to solve the problem of low extraction accuracy. Firstly, a smoothing method is used to eliminate the flat top of the laser line, and the Gaussian curve is adopted to fit the peak position of the curve. Then, the gray threshold is set to automatically extract the laser linewidth, and based on the window opening, the grayscale center of gravity method is improved to extract the coordinates of the center pixel for the second time. Finally, experiments show that the average absolute error of the improved laser line extraction method is 0.026 pixels, which is 2.3 times lower than the gray center of gravity method, 1.9 times lower than the curve fitting method, and the standard error can reach 0.005 pixels. Compared with the gray center of gravity method and the curve fitting method, the influence of gray value change on the center line extraction is more fully considered, and the center of the light strip can be extracted more accurately, achieving sub-pixel accuracy.

During the operation of the guide rail pair, the accuracy of the guide rail pair is decreased by friction and wear, and the overall performance of the machine tool is directly affected. The influence of surface micro-features of the slider raceway on the dynamic friction factor of the guide rail pair is analyzed in this paper. The relationship between the geometric characteristics of the surface micro-features and the dynamic friction factor is studied, and a prediction model of the dynamic friction factor is established. Meanwhile, the correctness and rationality of the predicted model is verified by the orthogonal experiments of the friction force. It is found that the dynamic friction factor increases with the increase of the groove depth, the height of the peaks and peak–valleys on the surface of the slider raceway. The above research provides a basis for the study of the friction and wear characteristics of guide rail pairs and lays a foundation for improving its friction and wear performance.

Due to the poor lighting conditions and the presence of a large amount of suspended dust in coal mines, obtained video has problems with uneven lighting and low differentiation of facial features. In order to address these problems, an improved image enhancement method is proposed. Firstly, the characteristics of underground coal mine images are analyzed, and median filtering is selected for noise removal. Then, the gamma function and fractional order operator are introduced, and an image enhancement algorithm based on particle swarm optimization is proposed. Finally, several experiments are conducted, and the results show that the proposed improved algorithm outperforms classical image enhancement algorithms, such as MSR, CLAHE and HF. Compared with the original image, the evaluation metrics of the enhanced Yale face images, including average local standard deviation, average gradient, information entropy and contrast, are improved by 113.1%, 63.8%, 22.8% and 24.1%, respectively. Moreover, the proposed algorithm achieves a superior enhancement effect in the simulated coal mine environment.

To reduce engine vibration, a semi-active controlled magnetorheological suspension is designed. First, the magnetic circuit of the new magnetorheological suspension is simulated. Furthermore, the non-parametric forward and inverse dynamic models of the magnetorheological suspension with the Elman neural network are established, where the modeling results and accuracy are analyzed. Second, according to the characteristics of semi-active vibration control of engine suspension, an improved fruit fly optimized proportional-integral-differential (PID) controller is proposed. Compared with the original fruit fly optimized PID controller and particle swarm optimization PID controller, the control strategies based on the proposed methods are simulated by MATLAB. Then, a vibration control experiment is carried out under different control strategies. The simulation and experiment results show that the PID controller based on the improved fruit fly optimization algorithm has the advantages of short adjustment time and fast dynamic response.

A complex stratum formed due to the influence of internal and external dynamic geological processes will lead to extremely complex mining conditions in deep exploration and development of oil, gas, coal and other resources, processes mainly threatened by disasters such as coal and gas conflict, mine water inrush, and rock burst. Combined with formation identification and measurement while drilling technology, the drilling level of underground drilling robot in coal mines is constantly developing. In order to prevent coal mine accidents and achieve safe and efficient mining, efficient and accurate drilling is the key, and should be based on research on the influence of complex stratum on the drilling trajectory. In order to comprehensively and systematically summarize the research on the influence of a complex stratum on drilling tool mechanics, this paper describes the history and current situation of complex stratum exploration, measurement while drilling technology, borehole bending conditions, stress analysis of complex coal seams on drilling tools, formation force theory and method, and geosteering drilling technology. In addition, the research and application of directional drilling technology in gas control, water hazard prevention and geological anomaly detection are also discussed.

In order to improve the response characteristics of magnetorheological fluid brake (MRB) and reduce the braking fluctuation rate, an improved grey wolf optimization algorithm was proposed to adjust the parameters of the proportion integration differentiation (PID) controller. Firstly, an MRB system was designed and constructed, and its transfer function was determined. Moreover, by adopting the iterative method of logistic curve, an enhanced grey wolf optimization algorithm (EGWOA) was presented. Using the EGWOA, the parameters of the PID controller were optimized to improve the control performance of the system. Finally, the simulation and experiment were carried out. The results showed that EGWOA has a faster response output and overall better performance without overshoot compared with the conventional PID and grey wolf optimization algorithm (GWOA) PID controller.

Owing to some of its specific advantages, magnetorheological fluid (MRF) has drawn significant attention in a broad range of modern precision machining fields. With the diversification and increase in demand, many novel structural configurations and processing methods have been applied to mechanical machining equipment. Although different applications using MRF have been proposed in the existing literature, the classification, latest approaches, and further trend are not understood clearly for the machining field. Therefore, the current applications such as machining auxiliary equipment and surface polishing equipment that used MRF are summarized from 2016 to 2020, in this article. Especially, some detailed structures of equipment are investigated, and relative limitations are analyzed based on the characteristics of MRF. Finally, in view of the current equipment, advantages and defects are briefly reported; the developing trends of modern precision machining with MRF are discussed. Therefore, in the state-of-the-art review, the significant role of MRF in the machining field is emphasized, which paves the way to innovative development and market selection.

Magnetorheological fluid (MRF) is a kind of smart materials with rheological behavior change by means of external magnetic field application, which has been widely adopted in many complex systems of different technical fields. In this work, the state-of-the-art MRF based devices are reviewed according to structural configurations reported from 2018 to 2020. Based on the rheological characteristic, the MRF has a variety of operational modes, such as flow mode, shear mode, squeeze mode and pinch mode, and has unique advantages in some special practical applications. With reference to these operational modes, improved engineering mechanical devices with MRF are summarized, including brakes, clutches, dampers, and mounts proposed over these 3 years. Furthermore, some new medical devices using the MRF are also investigated, such as surgical assistive devices and artificial limbs. In particular, some outstanding advances on the structural innovations and application superiority of these devices are introduced in detail. Finally, an overview of the significant issues that occur in the MRF based devices is reported, and the developing trends for the devices using the MRF are discussed.

In order to solve the problem of reciprocating motion in no beam supported mining machines, putting energy saving as a starting point in Coal Bed Methane (CBM) exploitation, this paper designs a completely non-circular gear automatic reversing vertical drainage machine based on the theory of non-circular gear transmission. In the field of CBM exploitation, the use of non-circular gears is an attempt at an innovation. First of all, according to the working conditions of the pump and use requirements, a scheme is established whereby the one-way rotary motion of the motor is changed into reciprocating motion so that it could drive the oil pumping rod to achieve the upper and lower mining. Secondly, this paper has designed a new type non-circular gear reversing box as the core component to replace the traditional four beam linkage mechanism and also provides elaborate calculations. Finally, the movement simulation of the non-circular gear reversing gear system is completed. Comparing the motion simulation results with the theoretical ones, the correctness of our theoretical analysis can be verified. Compared with the traditional devices, the new coal seam gas drainage machine model design has nearly 11% higher efficiency, which has obvious energy saving effects and reduces the cost of mining coal seam gas.