Search Results (59)

The conical pick is an essential component of roadheaders used for cutting rock. During the rock-breaking process, these picks interact with the rock, resulting in self-rotation, which enhances the wear uniformity of conical picks, thereby prolonging their service life. Since the phenomenon of self-rotation is generated passively by random contact forces with the rock surface, it is challenging to quantitatively measure the extent of self-rotatory speed. In order to investigate the correlation between the self-rotatory speed of conical picks and wear, this article establishes various self-rotatory speeds for vertical rock-breaking wear experiments involving conical picks. It analyzes the relationship between quantitative parameters, such as the equivalent stress and wear, through simulation. The results of the study indicate that the optimal self-rotatory speed of the conical pick is 16 rpm when it is rotated vertically to break the rock, resulting in minimal wear. When the equivalent stress and Mohr–Coulomb safety factor are optimized, it is essential to consider the changes in normal force and the variation in the area affected by the safety factor. This leads to an increase in wear as the cutting distance increases, indicating that a higher self-rotatory speed does not necessarily improve the wear performance of conical picks. Full article

In multidisciplinary design optimization (MDO) of high-end equipment, parameter uncertainty significantly undermines performance robustness. Existing methods are limited in convergence efficiency and in controlling uncertainty propagation. To address this gap, we propose a multidisciplinary robust collaborative optimization method under parameter uncertainty (MRCO-PU). The approach augments traditional Collaborative Optimization (CO) with a collaborative optimization method based on weight distribution difference information (CO-WDDI) to accelerate cross-disciplinary convergence. It also integrates a double-layer EI–Kriging robust optimization model to enhance robustness under complex coupling and small-sample conditions. The MRCO-PU method targets single-objective, strongly coupled, multi-constraint MDO problems with high per-evaluation cost. The method was validated on a mathematical case and on a cantilever roadheader cutting-head case. In the mathematical case, the robust feasibility of the constraints increased from 0.49 to 1.00. In the engineering case, the specific energy consumption decreased by 6.3% under the premise of fully satisfying the robust feasibility of the constraints, leading to operational cost minimization under uncertainty. This work provides an effective approach to multidisciplinary robust optimization for high-end equipment. Full article

Microwave irradiation of rocks can reduce the strength of rocks and ease their subsequent excavation. Exploring the combination of microwave and cutting tools for rock breaking under different conditions is important to the practical engineering application of microwaves. Based on a true triaxial microwave-assisted dual-mode mechanical rock-breaking test system, high-power microwave irradiation of rocks was investigated under different true triaxial stresses, durations of microwave irradiation, and cutting tool conditions such as mechanical drilling tools and tunnel boring machine (TBM) hobs. This research provides important data support for improving the rock-breaking efficiency of mine mining and tunneling as well as mechanical cutting tools and TBM hobs. In this experiment, Chifeng basalt with a relatively high strength was adopted as the research object. A 15 kW (2.45-GHz) open high-power microwave device was used to irradiate 200 mm × 200 mm × 200 mm cubic Chifeng basalt samples under conditions of different burial depths, and a cone drill bit was used for staged excavation. After microwave irradiation of Chifeng basalt measuring 400 mm × 400 mm × 400 mm, a 4-inch (102 mm) rotary cutter was employed to conduct round-by-circle cutting and rock-breaking tests in the microwave irradiation area. The results show that under true triaxial stress, the law of rock breaking by microwave irradiation combined with cone drill bits is as follows: the cutting force shows a trend of increasing–decreasing–increasing again–decreasing again. After microwave irradiation combined with hob cutting, the effective range of the influence of the hob is within the third cutting circle, with a range of diameters of approximately 200 mm. The results also indicate that the open microwave device can pre-crack rocks under deep stress, and there is obvious crack propagation. This research has good applicability to microwave-combined cantilever road-headers and TBM as well as in the mining field, and has a promising development prospect. Full article

Aiming at the complex construction environment and autonomous navigation challenges in underground coal mine roadways, this paper proposes a path navigation and deviation correction control method for tracked roadheaders in confined roadway spaces. First, a two-dimensional planar grid model of the working scenario was constructed, with dimensionality reduction in the roadway model achieved through a heading reference influence degree threshold of the tracked roadheaders. Based on the kinematics theory of tracked roadheaders, kinematic and dynamic models for deviation correction in fully mechanized excavation roadways were established. Subsequently, a path planning and tracking correction algorithm was developed, along with a heading deviation correction control algorithm based on fuzzy neural network PID. Online optimization of the particle swarm algorithm was realized through crossover-mutation operations, enabling optimal strategy solving for construction path planning and precise control of travel deviation correction. Finally, simulation experiments evaluating algorithm performance and comparative simulations of control algorithms validated the feasibility and superiority of the proposed method. This research provides strategic guidance and theoretical foundations for rapid precision deployment and intelligent deviation correction control of tracked engineering vehicles in confined underground coal mine spaces. Full article

Aiming at the problem of a full-width horizontal-axis roadheader being prone to diverge from the preset trajectory of the tunnel, a deviation correction control method based on particle swarm optimization–backpropagation (PSO-BP) neural network proportional–integral–derivative (PID) control is proposed. The track error model of the walking system and the transfer function model of the deviation correction control are established. The PSO-BP PID controller is designed; the beginning weights of BP are enhanced by the PSO, and the BP receives the optimal weights to instinctively adapt the PID parameters. An experiment on deviation correction control of the roadheader was carried out. The experimental results indicate that the maximum steady-state error of PSO-BP PID for deflection angle and angular velocity is reduced by 41.03% and 44.93%, respectively, compared with BP PID, and the average rise time for deflection angle and angular velocity is reduced by 75.76%. Full article

We propose a trustworthy load prediction method for a cantilever roadheader robot without imputation. Specifically, we design a load-trustworthy-boosting (LTB) algorithm for coal and rock cutting loads that accounts for missing data in complex underground environments. We introduce a trustworthy decision tree that integrates mixed-integer programming (MIP) and Missing Incorporated in Attributes (MIA) as the base predictor, which can handle missing data, thereby accelerating load prediction and improving prediction accuracy. Furthermore, we utilize boosting techniques to enhance the prediction performance of the base predictor by incorporating cutting safety–trust constraints during the prediction process. We derive the convergence of the algorithm theoretically and verify the accuracy and reliability of the algorithm through experiments. The experimental results show that the proposed algorithm is superior to state-of-the-art load prediction algorithms both without and with missing data considered. This method can provide a reliable decision-making basis for underground unmanned intelligent excavation. Full article

The selection of mining cutting tools used on the cutting heads of roadheaders and shearers in hard coal mines is primarily based on the uniaxial compressive strength (UCS) of the rock. However, selecting cutting tools solely on the basis of a single parameter characterizing the rock has proven to be insufficient. Therefore, the aim of the presented study was to develop guidelines for the selection of cutting tools with appropriate protective coatings on the working parts, based not only on the mechanical strength properties of rocks, but also on their abrasivity. For the study, twelve rock samples were collected from five different Polish hard coal mines. For each rock type, the UCS (uniaxial compressive strength), BTS (Brazilian tensile strength), and chemical composition (determined using wavelength-dispersive X-ray fluorescence, WD-XRF) were measured, along with the rock abrasivity index Wz, determined using a proprietary method developed at the AGH University of Krakow. The test results were compared with the calculated specific pick wear, defined as the number of picks consumed (replaced) per 1000 m³ of excavated material. As a result, a classification of rocks based on their UCS and abrasivity was developed, along with recommendations for selecting conical picks with suitable protective coatings on the working parts. Full article

This study reports a CFD investigation of spray-based dust suppression strategies in mining tunnels, focusing on the dynamic operation of roadheaders, onboard spraying systems, and water curtains. The simulations assess how these systems affect airflow patterns, velocity distributions, and pressure variations under various operating conditions. The results indicate that cutterhead sprays produce conical dispersion patterns directed toward the rear of the tunnel under forced ventilation, while transfer point sprays establish localized zones of extended residence time, with stable droplet distributions achieved in 3.5 s. Spray activation markedly increases local air velocity, with peak values near the cutterhead rising from 0.88 m/s to 32.29 m/s. Meanwhile, water curtains, modeled as porous media, induce stepwise pressure drops from 186.89 Pa to 91.15 Pa. These findings underscore the distinct effects of spraying and water curtain systems on tunnel ventilation and offer valuable insights for the design and optimization of airflow control and dust suppression in underground mining environments. Full article

In the application of digital twin technology for the heading workface in coal mining, real-time state data will be transmitted to the remote control platform through a gateway device. This cross-system and cross-software data transmission method inevitably introduces transmission delays, resulting in a certain spatiotemporal discrepancy in the virtual model control for the remote control of the physical equipment. In this paper, by analyzing the operational process of the cantilever roadheader, a state evolution dynamics model construction method for the cantilever roadheader is proposed, which includes three stages, the discretization of the operating state based on the cutting path, event-driven graph construction of the cutting state evolution, and real-time data-driven dynamics evolution, so to continuously monitor, analyze, and adjust the operational dynamics of the cantilever roadheader based on real-time state data, thus improving the efficiency, performance, and adaptability. The construction of the model provides a theoretical basis and technical support for the construction and alignment of the digital twin multidimensional model of the cantilever roadheader. Full article

In this study, a series of rock cutting tests was conducted using a conical pick to investigate the effect of joints on roadheader performance. Tests were performed on intact rock and jointed rock mass specimens with three different joint spacings. The results indicate that cuttability is enhanced in jointed rock mass compared to intact rock due to the influence of joints on fracture mechanics. When cutting perpendicular to the joint plane, joints shorten the fracture path for rock chip formation, reducing the cutting force (FC). In parallel cutting, the joint plane acts as a barrier to side-crack propagation, leading to a further reduction in FC. The FC and specific energy (SE) were generally lower in parallel cutting than in perpendicular cutting. However, when the cutting depth exceeded 0.2 times the joint spacing and the line spacing surpassed 0.4 times the joint spacing, this trend reversed. This occurred because joints hindered the interaction between adjacent cuts, causing a transition to an unrelieved cutting mode. Additionally, FC and SE increased with joint spacing. When joint spacing reached ten times the cutting depth, their values approached those of intact rock. This suggests that the joint effect becomes negligible. These findings provide a better understanding of the effect of joints on roadheader performance. Full article

The working environment at coal mining faces is harsh, leading to high failure rates and significant maintenance issues with roadheaders. This study explores multi-layer dimensionality reduction of vibration signal features in complex environments to enhance the differentiation of different operational states of a roadheader, thereby achieving fault recognition of key components. Concurrently, reducing dimensionality in manifold spaces positively influences operational state differentiation. Therefore, this paper integrates manifold learning to conduct multi-sensor and multi-layer data mining to enhance the differential phenotypes between faults of key components of the roadheader. Initially, we constructed multiple status-reference sample sets for each sensor individually, forming multiple manifolds at different spatial points, and utilizing locality-preserving projections (LPP) to extract low-dimensional manifold features. Further fusion of low-dimensional features from multiple sensors was used to elevate samples, constructing an enhanced spatial pseudo-manifold. Finally, we used LPP to re-reduce the enhanced sensitive feature set from multiple vibration sensors, establishing a dual-layer sensitive feature enhancement learning model. Conducting fault recognition analysis on experimental vibration signals, using k-nearest neighbors (KNN) to classify the enhanced feature set, we achieved a recognition success rate of 98.75% for samples, proving the method’s feasibility in fault recognition under complex loads. Full article

This paper proposes a cutting trajectory planning method for boom-type roadheaders using an improved Nondominated Sorting Genetic Algorithm II (NSGA-II) with an elitist strategy. Existing methods often overlook constraints related to cutterhead dimensions and target sections, affecting section formation quality. We develop a kinematic model for coordinate transformations and design a simplified cutterhead and constraint model to generate feasible cutting points. Bi-objective functions—minimizing cutting trajectory length and turning angle—are formulated as a bi-objective traveling salesman problem (BO-TSP) with adjacency constraints. NSGA-II is adapted with enhancements in adjacency constraint handling, population initialization, and genetic operations. Simulations and experiments demonstrate significant improvements in convergence speed and computation time. Virtual cutting experiments confirm trajectory feasibility under varying postures, achieving high formation quality. A comparison of planned and tracked trajectories shows a maximum deviation of 23.879 mm, supporting autonomous cutting control. This method advances cutting trajectory planning for roadway section formation and autonomous roadheader control. Full article

This work proposes a novel multi-camera system-based method for relative pose estimation and virtual–physical collision detection for anchor digging equipment. It is dedicated to addressing the critical challenges of achieving accurate relative pose estimation and reliable collision detection between multiple devices during collaborative operations in coal mines. The key innovation is that the multi-camera multi-target system is established to collect images, and the relative pose estimation is completed by the EPNP (Efficient Perspective N-Point) algorithm based on multiple infrared LED targets. At the same time, combined with the characteristics of a roadheader and anchor drilling machine, AABB (Axis Alignment Bounding Box) with a simple structure and convex hull with a strong wrapping are selected to create the mixed hierarchical bounding box, and the collision detection is carried out by combining SAT (Split Axis Theorem) and GJK (Gilbert–Johnson–Keerthi) algorithms. The experimental results show that the relative pose estimation error of the multi-camera system is within 20 mm, with an angular error within 1.002°. The position error in the X-axis direction is within 1.160 mm, and the maximum deviation in the Y-axis direction is within 0.957 mm in the virtual–physical space. Compared with the existing methods, our method integrates digital twin technology, and has a simple system structure, which can meet the requirements of relative attitude estimation and collision detection between equipment in the process of heading face operation, and at the same time improve the system performance. Full article

A positioning method for a roadheader based on fiber-optic strap-down inertial navigation and binocular vision is proposed to address the issue of low measurement accuracy of the mining machine position caused by single-sensor methods in underground coal mines. A vision system for the mining machine position is constructed based on the four-point target fixed on the body of the roadheader, and the position and attitude information of the roadheader are obtained by combining the inertial navigation on the body. To deal with the problem of position detection inaccuracies caused by the accumulation of errors in inertial navigation measurements over time and disturbances from body vibrations to the combined positioning system, an Adaptive Derivative Unscented Kalman Filtering (ADUKF) algorithm is proposed, which can suppress the impact of process variance uncertainties on the filtering. The simulation results demonstrate that, compared to the Unscented Kalman Filtering algorithm, the position errors in the three directions are reduced by 20%, 20.68%, and 28.57%, respectively. Experiments demonstrate that the method can compensate for the limitations of single-measurement methods and meet the positioning accuracy requirements for underground mining standards. Full article

Safe path planning is essential for the autonomous operation of robotic roadheader in narrow underground tunnels, where limited perception and the robot’s geometric constraints present significant challenges. Traditional path planning methods often fail to address these issues. This paper proposes a collision prediction-integrated path planning method tailored for robotic roadheader in confined environments. The method comprises two components: collision prediction and path planning. A collision prediction model based on artificial potential fields is developed, considering the non-convex shape of the roadheader and enhancing scalability. By utilizing tunnel design information, a composite potential field model is created for both obstacles and the roadheader, enabling real-time collision forecasting. The A* algorithm is modified to incorporate the robot’s motion constraints, using a segmented weighted heuristic function based on collision predictions. Path smoothness is achieved through Bézier curve smoothing. Experimental results in both obstacle-free and obstacle-laden scenarios show that the proposed method outperforms traditional approaches in terms of computational efficiency, path length, and smoothness, ensuring safe, efficient navigation in narrow tunnels. Full article