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With the aim of solving the problem of coal congestion caused by big coal blocks in underground mine scraper conveyors, in this paper we proposed the use of a YOLO-BS (YOLO-Big Size) algorithm to detect the abnormal phenomenon of coal blocks on scraper conveyors. Given the scale of the big coal block targets, the YOLO-BS algorithm replaces the last layer of the YOLOv4 algorithm feature extraction backbone network with the transform module. The YOLO-BS algorithm also deletes the redundant branch which detects small targets in the PAnet module, which reduces the overall number of parameters in the YOLO-BS algorithm. As the up-sampling and down-sampling operations in the PAnet module of the YOLO algorithm can easily cause feature loss, YOLO-BS improves the problem of feature loss and enhances the convergence performance of the model by adding the SimAM space and channel attention mechanism. In addition, to solve the problem of sample imbalance in big coal block data, in this paper, it was shown that the YOLO-BS algorithm selects focal loss as the loss function. In view of the problem that the same lump coal in different locations on the scraper conveyor led to different congestion rates, we conducted research and proposed a formula to calculate the congestion rate. Finally, we collected 12,000 image datasets of coal blocks on the underground scraper conveyor in Daliuta Coal Mine, China, and verified the performance of the method proposed in this paper. The results show that the processing speed of the proposed method can reach 80 fps, and the correct alarm rate can reach 93%. This method meets the real-time and accuracy requirements for the detection of abnormal phenomena in scraper conveyors.

“Three straight and two flat” is the inevitable demand when realizing the intelligent mining of a fully mechanized mining face. To address the crucial technical issue of lacking accurate perception of the shape of the scraper conveyor during intelligent coal mining, a three-dimensional curvature sensor involving fiber Bragg grating (FBG) is used as a perceptive tool to conduct curve reconstruction research based on different local motion frames and to reconstruct the shape of the scraper conveyor. Firstly, the formation process of the ‘S’-shaped bending section of the scraper conveyor during the pushing process is determined. Based on the FBG sensing principle, a mathematical model between the variation in the central wavelength and the strain and curvature is established, and the cubic B-spline interpolation method is employed to continuously process the obtained discrete curvature. Secondly, based on differential geometry, a spatial curve reconstruction algorithm based on the Frenet moving frame is derived, and the shape curve prediction interpolation model is built based on a gated recurrent unit (GRU) model, which reduces the impact of the decrease in curve reconstruction accuracy caused by damage to some grating measuring points. Finally, an experimental platform was designed and built, and sensors with curvature radii of 6 m, 7 m, and 8 m were tested. The experimental results showed that the reconstructed curve was essentially consistent with the actual shape, and the absolute error at the end was about 2 mm. The feasibility of this reconstruction algorithm in engineering has been proven, and this is of great significance in achieving shape curve perception and straightness control for scraper conveyors.

The accurate perception of straightness of a scraper conveyor is important for the construction of intelligent working faces in coal mines. In this paper, we propose a precision compensation model based on rotation error angle to improve the accuracy of the fiber Bragg grating (FBG) curvature sensor of a scraper conveyor. The correctness of the model is verified by theoretical analysis, numerical simulation, and experiments. Finally, the feasibility of the model is analyzed and discussed for field application in a coal mine. When the rotation error angle is within the range of 0~90°, according to the strain of FBG obtained by numerical simulation, the radius of the curvature is inversely calculated by the compensation model. The relative error of each discrete point is within ±0.9%, and the relative error after fitting is less than 0.2%. The experiment shows that the relative error of the curvature radius after fitting according to the theoretical formula is less than ±3%, and the relative error of the curvature radius value obtained by the inverse deduction of each discrete point is less than ±6%, which verifies the correctness and applicability of the compensation model. In addition, the compensation model with the FBG curvature sensor has broad application prospects in coal mine underground conveyors, submarine pipelines and ground pipelines.

The accuracy of straightness monitoring of scraper conveyors seriously restricts the development of unmanned mining technology in underground coal mines. Fiber Bragg grating (FBG) sensors have the characteristics of passive intrinsic safety and have broad application prospects in coal mine underground monitoring technology. In this paper, the motion characteristics between two adjacent Middle Chutes of the scraper were fully analyzed, the mathematical expressions were illustrated, furthermore, a 3D vector sensor is designed and manufactured using FBG sensors. The calibration and testing of the appropriate number of sensors was realized, and the test results showed that the FBG 3D vector sensor we designed can be used to measure the straightness of the scraper conveyor. The research introduces three main contributions: (1) a novel mathematical model characterizing the motion between adjacent scrapers; (2) the design and fabrication of a 3D vector sensor based on FBG technology; and (3) experimental validation through calibration and testing. Results demonstrate that the developed sensor system effectively measures Middle Chutes straightness with accuracy meeting practical application requirements.

During an in-situ operation of machines, used for the exploitation of energy raw materials, a damaging impact of the environment on the components of these machines is experienced. The action of degrading factors is mostly shown in the form of a clear synergistic effect. In particular, this effect can be seen during an exploitation of driving elements of scraper conveyors, used as one of the basic machines in the hard coal mining process. In the article, the subject–matter, connected with an operation of sprockets in scraper conveyors, is presented. Special attention is paid to a mutual reaction of the mineral abrasive and the presence of mine water. The main objective of the research work was a determination of the interactive component of the factor causing an abrasive wear–quartz abrasive connected with the associated action and the factor intensifying electrochemical corrosion–water with and without the NaCl salt content. Experimental tests were conducted in the conditions similar to the reality, with the use of a test rig in the form of a short scraper conveyor. Within the framework of the test abrasive wear rates for the case of the abrasive presence itself and a mixture of the abrasive, salt and water were determined. Based on the obtained results, it appears that there is a synergistic impact of abrasive–corrosive mixtures on the wear of the surface layer of the chain sprockets under testing, and also, the causes of the interactive component values in the function of hardness and maximum strength of the materials under investigation are presented.

The main transmission system of a scraper conveyor direct-driven by the high-power permanent magnet synchronous motor (PMSM) is taken as a study object. With the effect of the nonlinear friction torque caused by the nonuniformity of the transported coal quality in the operation process considered, the torsional vibration bifurcation mechanism and the corresponding control measures for the main transmission system of the scraper conveyor are investigated. Firstly, based on the Lagrange–Maxwell principle, the global electromechanical-coupling dynamic models for the main transmission system of the scraper conveyor are constructed. Secondly, by the Routh–Hurwitz stability criterion, the Hopf bifurcation characteristics of the main transmission system are analyzed to reveal the influence of supercritical bifurcation and subcritical bifurcation on the torsional oscillation of the transmission shafting. Thirdly, in order to suppress the system unstable oscillation caused by the Hopf bifurcation, the motor speed is fed back to construct the nonlinear state feedback controller for the quadrature axis current of the PMSM by the I d = 0 vector control strategy. Similarly, on the basis of the Routh–Hurwitz criterion, the influence of the linear feedback coefficient in the nonlinear state feedback controller on the system bifurcation position is discussed. Meanwhile, by the central manifold theory and canonical form theory, the effect of the square and cubic nonlinear feedback coefficients on the Hopf bifurcation type of the torsional vibration and the amplitude of the stable limit cycle are investigated. Finally, the numerical simulation results show the effectiveness of the designed controller.

For the issue of excessive mass in the chain drive system of long-distance scraper conveyors, this paper proposes a method to optimize the scraper chains by integrating discrete element simulation (DEM) with topological optimization. The aim is to reduce the system’s mass while maintaining its transportation capacity and structural integrity. The SGZ1000 model scraper conveyor with a length of 400 m was selected as the research object. Studies have demonstrated that for 56 × 187 mm scraper chains, a non-equally spaced configuration (6p-8p-6p, where p represents the chain link pitch) outperforms an equally spaced configuration (6p). While ensuring the conveying capacity of the scraper chains, the optimized configuration reduces the number of scrapers in chains of equal length by 11.11%. For a 400 m scraper conveyor, adopting the 6p-8p-6p scraper spacing reduces the number of scrapers by 72 and decreases the mass by 6357.6 kg. Additionally, utilizing topologically optimized scrapers further reduces the total mass by 10,131.4 kg. Compared to the original chain drive system, the optimized scraper chains have reduced the mass by 26.2%, significantly lowering the no-load energy consumption of the long-distance scraper conveyor.

Understanding the friction and wear law of the chain-track interface during the continuous transportation of coal particles by the short-distance scraper conveyor is of great significance for improving the reliability and fault warning capability of the scraper conveyor system of roadway boring equipment. Firstly, the rigid-dissipative coupling model of a short-distance scraper conveyor is constructed. Then, for the accumulation of coal bulk material in the position near the shovel star wheel and the middle of the chain track on the conveying chute, the specific inclination angle of the conveyor is 12°. The scraper chain speed is taken to be 1.32 m/s, 1.72 m/s, and 2.4 m/s, respectively for the combination, which is classified into six working conditions for the study. Finally, the main distribution areas, magnitude sizes, and causes of wear of the upper chain track and scraper chain were obtained, and the coal bulk particle transport characteristics and the relative velocity distribution law of material flow were elucidated. The results show that with the chain speed of 2.4 m/s, a scraper chain can be a smooth transportation of coal bulk material to the end of the machine, and the wear on the chain track on the chain plate is lighter.

Aiming at the problem of serious shutdowns of conveyors caused by abnormal coal flow of scraper conveyors, a coal flow monitoring method based on speckle structured light is proposed. The point cloud data of the coal body on the scraper conveyor is collected through the speckle structured light acquisition system. Then, the proposed PDS-Algorithm (Planar Density Simplification Algorithm) is used to complete the simplification and differentiation of the collected point cloud data, which provides a basis for constructing geometric characteristics of coal flow lineament. This paper uses the processed point cloud data to calculate the volume of the coal mass and monitor the coal flow of the scraper conveyor. Finally, this method is used in the detection of abnormal coal flow of a coal mine scraper conveyor, and the results show that the proposed abnormal flow monitoring method can meet the accuracy and real-time requirements of coal mine abnormal alarms.

To address the challenges of strong electromechanical coupling, nonlinear friction, and poor disturbance rejection in semi-direct-drive scraper conveyor systems under complex coal mining conditions, this paper aims to propose a high-performance drive control strategy that balances dynamic response speed with steady-state operational smoothness. First, an integrated electromechanical coupling dynamic model incorporating Permanent Magnet Synchronous Motor (PMSM) vector control and the time-varying meshing stiffness of a two-stage planetary gear train is established. Subsequently, a Sliding Mode Control (SMC) strategy optimized with a saturation boundary layer is designed and compared with traditional Proportional-Integral (PI) control under multiple operating conditions. Time-frequency domain analysis indicates that SMC significantly enhances the dynamic stiffness of the drive system. Under sudden load change conditions, the speed recovery time is shortened by approximately 76%, and the steady-state error is reduced by 37% compared to PI control. Microscopic characteristic evaluation based on FFT and Total Variation (TV) metrics reveals that SMC achieves active disturbance rejection through spectral broadening of the electromagnetic torque. Crucially, the steady-state cumulative control effort of SMC is equivalent to that of PI, implying no additional mechanical stress burden, while the equivalent dynamic transmission force fluctuation in the mechanical chain is reduced by about 3%. The study confirms that the proposed strategy successfully achieves a synergistic optimization of “macroscopic rapid response” and “microscopic smooth operation,” providing a theoretical basis for the high-precision control of heavy-duty underground transmission equipment.