As key coal mining equipment, the shearer is crucial for improving adaptability to complex conditions, extending service life, and reducing failure rates—key to enhancing coal production economic benefits. Using the transmission system model, dynamic bearing contact forces, vibration acceleration at virtual measurement points, and vibration levels in gangue/pure coal conditions are analyzed. The reliability and accuracy of the finite element analysis for the cutting unit's vibration characteristics were validated via bench test comparison. The vibration-data-equipped housing is input into acoustic boundary element simulation; combined with the built model, noise variations at different sound field response points with gear face width and bottom clearance coefficient are derived. Results show high-order modal analysis confirms no system resonance risk. When the motor gear face width is 74mm, planetary gear train face width 140mm, and bottom clearance coefficient 0.4, the gears exhibit excellent load-bearing capacity, stability, and low vibration/noise.

In certain mining areas, bauxite ore exhibits high and uneven hardness, causing frequent overloads in the cutting heads of bauxite mining equipment and challenging the dynamic performance and reliability of its gear transmission system. To investigate the influence of macro-geometric parameters, a dynamic model was built using MASTA software (version 13.0.1). This study systematically analyzed the effects of pressure angle, face width, and bottom clearance coefficient on gear meshing characteristics, service life, and vibration noise under various loads. A preferred set of parameters was determined and validated through vibration and noise tests. The results show that increasing the pressure angle and face width improves gear meshing and fatigue life, while the bottom clearance coefficient has an optimal value of 0.4. Increasing the bottom clearance coefficient exacerbates vibration and noise, with other parameters causing fluctuations under different conditions. The optimal parameters of 23° pressure angle, 75 mm face width, and 0.4 bottom clearance coefficient effectively reduce vibration and noise, providing a theoretical and practical basis for improving the cutting transmission system.

During fully mechanized coal mining, hydraulic supports are prone to posture variations such as pitching, tilting, and twisting, which directly impact their support performance, coordination with shearers, and the overall operational stability of the working face. Existing posture detection methods often exhibit limitations in positioning accuracy, long-term stability, and hardware complexity. To address these challenges, this paper proposes an integrated LiDAR-binocular camera detection system. By quantifying the effects of target surface material, distance, angle, and environmental factors on LiDAR performance, a robust target recognition model is developed. Integrating this with binocular distortion correction, image segmentation, and circle detection algorithms, high-precision target localization and posture estimation are achieved. Finally, static and dynamic accuracy tests were conducted on a hydraulic support experimental platform using the MARS motion capture system. The results demonstrate that the proposed method effectively meets the requirements for hydraulic support posture detection in the complex environment of fully mechanized mining faces.

Underground bauxite comprehensive mechanized mining has attracted growing attention, yet regional differences in bauxite characteristics challenge its applicability and economic efficiency. The conical pick, a key cutting tool for this mining method, has cutting load characteristics that directly impact the cutting mechanism’s efficiency and reliability. Three typical bauxite samples from different mining areas were selected as research objects. After testing their composition and firmness coefficients, a linear cutting test bench was used to measure their tri-axial cutting forces at various cutting depths. Regression analysis and the linear fitting of cutting coefficients were conducted to study cutting force and normal force (two core cutting loads). The results show that power functions effectively describe the relationships between the cutting force, normal force, fluctuation coefficient and cutting depth. As the bauxite firmness coefficient and cutting depth rise, the cutting force peak value, fluctuation amplitude and frequency all increase. Excessively high or low cutting coefficients reduce the cutting efficiency; only when both the cutting coefficient and the depth are in an optimal range can the cutting efficiency reach its maximum.

Pre-grooving is an effective means of facilitating hard-rock cutting with conical picks, reducing pick wear, and improving rock-cutting efficiency. However, research on the effects of matching cutting parameters with kerf parameters on rock-cutting performance remains limited. Using granite with a strength exceeding 130 MPa, this paper establishes a model of rock cutting by conical pick by employing the discrete element method (DEM) and verifies the validity of the model by rock-cutting tests. Based on the DEM, the effects of cutting depth, kerf spacing, and kerf depth on mean cutting force, rock fragmentation volume, and specific energy of pick cutting rock are numerically investigated, and the response surface method is used to determine the significance of each factor for the respective performance indicators. The results show that both cutting depth and kerf depth affect the critical kerf spacing. When the kerf spacing does not exceed its critical value, mean cutting force and rock fragmentation volume increase with increasing kerf spacing, whereas specific energy decreases. Therefore, an excessively small kerf spacing is not conducive to increasing the rock fragmentation volume of the conical pick. Increasing the kerf depth facilitates rock breaking by the conical pick. Cutting depth has the most significant effect on mean cutting force, followed by kerf spacing. Cutting depth also has the greatest effect on rock fragmentation volume, followed by the interaction between cutting depth and kerf spacing, while kerf spacing and kerf depth also exert some influence. Specific energy is most strongly affected by kerf depth, followed by cutting depth and the interaction between cutting depth and kerf spacing. These findings provide guidance for the rational matching of cutting and kerf parameters in pre-grooving assisting conical picks cutting hard rock.