In underground backfilling technology, long-distance pipeline transportation of gangue slurry is prone to problems such as sedimentation and blockage. At present, point-based acquisition and local observation methods are mostly used to monitor the pipeline transportation state, which makes it difficult to achieve continuous coverage and accurate localization of anomalies along long-distance pipelines. To address this problem, Distributed Acoustic Sensing (DAS) based on phase-sensitive optical time-domain reflectometry was adopted to achieve full-field continuous monitoring of blockage conditions in gangue slurry transportation pipelines. A gangue slurry transportation pipeline blockage experimental platform was established to simulate normal transportation as well as blockage conditions of 20%, 40%, and 60%. DAS optical fiber was used to collect vibration signals along the pipeline. A dual-branch identification model was constructed using One-Dimensional Convolutional Neural Network (1DCNN), Long Short-Term Memory (LSTM), and Cross Attention (CA) mechanism. The energy and power spectral density of DAS vibration signals were used as features to classify pipeline blockage conditions. The experimental results showed that the model achieved accuracy, recall, and F1 score of 91.27%, 93.10%, and 92.28% for normal pipeline conditions, and 92.72%, 92.06%, and 92.39% for different blockage conditions, respectively. The performance was superior to that of DAS vibration signal identification models such as multi-scale convolution combined with a hidden Markov model. Based on the proposed method, a DAS monitoring and intelligent identification system for gangue slurry transportation pipeline blockage was developed, which realized visualization of vibration signal feature analysis and a B/S network service application for pipeline blockage identification.
To address the problems of low system reliability and high maintenance costs caused by reliance on mechanical position sensors in permanent magnet external rotor hoists, a sensorless control strategy integrating multibody dynamics modeling for permanent magnet external rotor hoists under time-varying load was proposed. First, a mathematical model of the permanent magnet external rotor hoist was established, and the pulsating high-frequency signal injection method was theoretically analyzed. Second, a phase-locked loop position observer was used to dynamically track the rotor position, and a sensorless control system was constructed. Then, a multibody dynamics model of the hoist was established using RecurDyn software, including the elastic deformation of the wire rope and the drum winding effect, to accurately characterize the time-varying characteristics of the system load. Finally, an electromechanical coupling co-simulation model based on Matlab/Simulink and RecurDyn was established, and the proposed sensorless control system was experimentally verified using a physical verification platform. The results showed that under the time-varying load torque condition of the hoist, the proposed sensorless control strategy controlled the speed tracking error within ±0.2 r/min and the rotor position observation error below 0.01 rad. It showed good rotor position tracking accuracy and speed tracking performance throughout the entire operating cycle of the permanent magnet external rotor hoist.
The spontaneous combustion process of coal is influenced by multiple factors.Existing studies mainly investigate coal spontaneous combustion characteristics from aspects such as coal metamorphic degree,oxygen concentration,air supply rate,air humidity,particle size,and moisture content rate.However,the sulfur content in coal is also one of the important factors affecting coal spontaneous combustion.To investigate the effects of sulfur content on the spontaneous combustion characteristics and oxidation kinetic parameters of anthracite,oxidation processes of five coal samples with different sulfur contents were tested using a programmed temperature-rise experiment system with a tube furnace.The effects of different sulfur contents on CO and CO2 gas release characteristics and characteristic temperatures of spontaneous combustion during the low-temperature oxidation process of coal were quantitatively analyzed.By calculating the oxygen consumption rates of coal samples with different sulfur contents under different temperature conditions,the variation pattern of the oxygen consumption rate with temperature was quantitatively examined.Based on chemical reaction kinetics,the apparent activation energies of coal samples under different sulfur contents were calculated,and the variation pattern of apparent activation energy with sulfur content was quantitatively analyzed.The results showed that when the sulfur content remained constant,the concentrations of CO and CO2 and the oxygen consumption rate increased exponentially with increasing temperature,while the apparent activation energy gradually decreased.With increasing sulfur content,the concentrations of CO and CO2 and the oxygen consumption rate at each temperature point first increased and then decreased,reaching maximum values at a sulfur content of 5.14％.In contrast,the characteristic temperature of spontaneous combustion and the apparent activation energy showed opposite trends and reached minimum values at a sulfur content of 5.14％,at which point the coal sample exhibited the strongest spontaneous combustion tendency.Therefore,the critical sulfur content affecting the spontaneous combustion tendency of anthracite was 5.14％.
CO released from the oxidation of residual coal in goaf areas causes CO exceedance in the return air corner of coal mines,and clarifying the critical thresholds for CO exceedance in the return air corner and establishing a graded early warning index system are of great significance for the early warning of coal spontaneous combustion in goaf areas.To achieve accurate early warning of coal spontaneous combustion disasters in coal mine goaf areas,a medium-rank bituminous coal was taken as an example,and the oxidation characteristics of coal and the generation patterns of indicator gases under ambient temperature and heating conditions were systematically analyzed by combining laboratory experiments and field observations.Experimental results indicated that coal exhibited a hysteresis phenomenon of O2 consumption and CO generation at ambient temperature,and the background CO volume fraction generated by ambient-temperature oxidation was determined to be 18×10-6.During the heating oxidation stage,the oxygen consumption rate and CO generation rate showed a significant increasing turning point with a sharp increase at 70 ℃,and the characteristic gas C2H4 began to appear at 100 ℃.Based on these results,the low-temperature oxidation process of coal was divided into three stages,namely slow oxidation(30-70 ℃),accelerated oxidation(70-100 ℃),and intense oxidation(＞100 ℃).By integrating experimental data with historical field monitoring data,a four-level early warning index system for coal spontaneous combustion was established with the CO concentration in the return air corner as the core indicator,which provided a theoretical basis and practical guidance for early identification and graded prevention and control of coal spontaneous combustion based on CO concentration in the return air corner.
Coal gangue exhibits complex morphology, rough surfaces, and significant size variations. In dynamic conveying scenarios, it is easily affected by factors such as reflection, occlusion, and motion asynchrony, which lead to breakage or displacement of laser line stripes, resulting in point cloud sampling loss and volume measurement errors. To address this problem, a point cloud volume measurement method for coal gangue based on an improved projection-based integration method was proposed. The Random Sample Consensus (RANSAC) algorithm was used to fit the main plane, and a spatial filtering criterion was applied to effectively remove the conveyor belt background and noise. Initial region growing segmentation was performed based on normal and curvature constraints, and a multi-factor clustering mechanism was introduced to eliminate over-segmentation interference, thereby achieving accurate instance segmentation of adhesive objects. Considering that the vertical scanning perspective of the line-laser camera and the irregular natural morphology of coal gangue caused severe self-occlusion in the bottom region, a bottom surface completion strategy integrating normal foot projection and uniform density filling was proposed, and a closed bottom contour was reconstructed using a two-dimensional concave hull or ellipse fitting. In the traditional projection-based integration process, concave hull boundaries were introduced to eliminate redundant empty grids. The median criterion was applied to remove height outliers, and a radial-sector parallel strategy was adopted to improve overall computational efficiency and noise robustness. The experimental results showed that the overall average relative error of coal gangue volume measurement was only 8.92%, and the qualification rate reached 95.89% under the maximum allowable error standard of 20%. In multi-orientation flipping tests of the same gangue, the average relative error of volume measurement was only 5.7%.
