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Scraper conveyor is the most important transportation equipment in the comprehensive mining equipment, and the chain drive system is its core subsystem, its dynamic characteristics will significantly affect the efficiency of coal transportation in the comprehensive mining face. In this paper, the dynamic characteristics of chain drive system when impacted by falling coal are investigated by means of test. The impact test bench of scraper conveyor was set up to analyze the effects of chain speed, impact height and impact load mass on the dynamic characteristics of the chain drive system of scraper conveyor under the working conditions of unloaded and loaded. The results show that the longitudinal vibration of the scraper conveyor is most obvious when it is impacted by the falling coal, and the chain speed, impact height and impact load mass of the scraper conveyor all play an excitation role on the vibration of the chain drive system, and the vibration of the chain ring is the most intense in the chain drive system, and the loaded coal pile conveyed on the scraper conveyor plays an inhibiting role on the vibration of the chain drive system. This study can help to identify the location where the scraper conveyor fails first in the impact condition, so as to provide a basis for its structural design and improvement, which is of great significance for the stable operation and structural optimization of the scraper conveyor., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

To study the influence of the gangue content of coal gangue particles on the vibration signal of the tail beam under sliding condition, this paper combines three-dimensional(3D) laser scanning technology with the finite element method, establishes a finite element model of the real shape of coal gangue particles and the hydraulic support in top coal caving in LS-DYNA, analyzes the influence of gangue content on some characteristics of the acceleration signal on the tail beam in the time and frequency domains, and then studies the influence of the size and total mass of the rock, and the angle of the tail beam on the characteristics. The following conclusions are obtained: when the coal gangue particles slip on the tail beam, an increase in gangue content significantly improves the effective value of the acceleration signal of the tail beam in the time domain and the average power and average amplitude in the frequency domain. With different sizes, total masses, and tail beam angles, the increase in gangue content always causes an increase in acceleration signal characteristics. In terms of the influence of various factors on the same gangue content, at the same total mass, the larger the rock mass size is, the faster the characteristic value increases with the increase in gangue content. The greater the total mass, the greater the value of the acceleration signal characteristics. A smaller angle between the tail beam and the ground increases the value of each characteristic. The results of this study provide a reference for further research on coal gangue identification based on vibrations., Competing Interests: The authors have declared that no competing interests exist.

The mechanism of cutting process of roadheader with cutting head was researched, and the influences of properties of coal and rock on cutting load were deeply analyzed. Aimed at the defects of traditional calculation method of cutting load on fully expressing the complex cutting process of cutting head, the method of finite element simulation was proposed to simulate the dynamic cutting process. Aimed at the characteristics of coal and rock which affect the cutting load, several simulations with different firmness coefficient were taken repeatedly, and the relationship between three-axis force and firmness coefficient was derived. A comparative analysis of cutting pick load between simulation results and theoretical formula was carried out, and a consistency was achieved. Then cutting process with a total cutting head was carried out on this basis. The results show that the simulation analysis not only provides a reliable guarantee for the accurate calculation of the cutting head load and improves the efficiency of the cutting head cutting test but also offers a basis for selection of cutting head with different geological conditions of coal or rock.

The scraper conveyor, essential for mechanized mining, operates in harsh underground environments and is subjected to severe impact loads from coal and rock falls. Such conditions can cause chain jamming, breakage, and other malfunctions, necessitating a detailed study of the system's dynamic behavior under impact conditions. This study investigates the dynamic characteristics of a scraper conveyor's chain drive system using a coupled ADAMS-EDEM simulation model. The model analyzes the effects of loaded coal piles on the conveyor's dynamics during normal and impact conditions. Simulations show that loaded coal piles excite the scraper's acceleration and sprocket rotation, with the greatest impact in the scraper's running direction. Longitudinal impact and contact forces on the chain ring are more significant than in other directions under both no-load and loaded conditions. A strong linear relationship exists between the falling coal mass and longitudinal impact force. The coal pile causes prominent longitudinal vibration excitation while inhibiting the overall vibration of the chain drive system to some extent. The findings provide insights for identifying failure-prone areas under impact conditions and offer theoretical guidance for optimizing scraper conveyor design. This enhances mining efficiency and safety in coal operations. [ABSTRACT FROM AUTHOR]

To address the lightweight and real-time issues of coal sorting detection, an intelligent detection method for coal and gangue, Our-v8, was proposed based on improved YOLOv8. Images of coal and gangue with different densities under two diverse lighting environments were collected. Then the Laplacian image enhancement algorithm was proposed to improve the training data quality, sharpening contours and boosting feature extraction; the CBAM attention mechanism was introduced to prioritize crucial features, enhancing more accurate feature extraction ability; and the EIOU loss function was added to refine box regression, further improving detection accuracy. The experimental results showed that Our-v8 for detecting coal and gangue in a halogen lamp lighting environment achieved excellent performance with a mean average precision (mAP) of 99.5%, was lightweight with FLOPs of 29.7, Param of 12.8, and a size of only 22.1 MB. Additionally, Our-v8 can provide accurate location information for coal and gangue, making it ideal for real-time coal sorting applications. [ABSTRACT FROM AUTHOR]

The problems of insufficient recognition accuracy, poor real‐time performance and lack of consideration of actual working conditions in the process of intelligent construction of coal mines make this technology still in the research stage and not applied in practical engineering. The purpose of this paper is to establish an accurate and real‐time recognition model, which can quickly distinguish the vibration acceleration signals of coal and gangue under the influence of external factors such as impact position, velocity, and direction by using the different physical properties of coal and gangue particles. Therefore, the accuracy and real‐time of coal gangue recognition model established by different convolutional neural networks (CNN) structures and different position signal input are studied. First, to meet the real‐time requirements, an original CNN recognition model composed of single convolution layer and single pooling layer is established, and the data collected by seven sensors are input in the form of two‐dimensional matrix. However, the stability of the training and test results is insufficient. To solve this problem, once improved CNN (OI‐CNN) recognition model with multiconvolution layers and multipooling layers is built by deepening the network. The experimental results show that the stability and accuracy are improved, but the real‐time performance is poor. Furthermore, through parameter adjustment, the OI‐CNN is changed to the twice improved CNN (TI‐CNN), and the sensor data at different positions are input in the form of one‐dimensional vectors. The results show that the accuracy and real‐time performance of the TI‐CNN coal gangue recognition model are further improved. Finally, according to the research purpose of this paper, the weights of CNN indexes are given, and a multi‐index comprehensive evaluation system (MICES) is established. With the original CNN recognition model as the control, the OI‐CNN recognition model and the TI‐CNN recognition model at different positions are quantitatively compared to obtain the comprehensive evaluation scores of each model. The results show that the MICES of the coal gangue recognition model established based on the TI‐CNN structure and the data input of a single position sensor is the highest, while the sensor position has little effect on the recognition results. [ABSTRACT FROM AUTHOR]

Shearer is an essential equipment in mechanized coal mining process. Roof cutting often turns up for shearer during working process, leading to extra vibration on shearer and reducing its service life. Coal and rock interface recognition is a fundamental technical way for shearer to avoid continuous roof cutting. In this paper, an effective method for coal and rock interface is proposed and it is mainly based on the cutting loads on shearer drum in three different kinds of working states. The constitutions of cutting force on shearer drum are analyzed under conditions of different proportions of rock thickness in the cutting range and then model for calculation of cutting force in the coal–rock mixed seam are proposed which is a function of rock proportion in the cutting range. To verify the model, hard roof with different material strengths and different interfaces are established with the numerical method and rock proportions in the cutting range are derived based on the mentioned method. In terms of the situations where rock material properties are close to coal and the results are obtained with lower accuracy, enlarging the difference of rock proportions in the second and third states is proposed and the relations between the recognition accuracy and the differences of rock proportions in different states are explored as well. The results show that the estimation method works well with qualititative analysis of coal and roof interface even if coal and rock material properties are various and not able to be known in advance. In addition, the adjustment height of shearer drum is the important factors highly related with the estimation accuracy and it would be helpful for accuracy improvement in conditions where the material properties of coal and roof are closer to each other or larger roof cutting thickness happens in coal mining. The method provides the possibility for qualititative analysis of coal and roof interface with easy accessibility and wide adaptability. [ABSTRACT FROM AUTHOR]

Top coal caving in fully mechanized caving mining will cause an irregular impact on the caving mechanism of hydraulic support. The vibration response of the caving mechanism varies under different forms of impact. This response difference is a prerequisite for new coal rock identification technology in intelligent mining. Therefore, this work studies the difference in vibration response of the caving mechanism under different forms of impact. An innovative mechanical–hydraulic coupling system model of the caving mechanism impact by coal rock is established. The metal plate impact test proved the significant difference in vibration response of the caving mechanism under coal rock impact of different materials. Afterward, a more improved mechanical–hydraulic co-simulation model analyzed the difference in the vibration response of the caving mechanism under different rock materials, volumes, velocities and impact positions. The results show that the vibration response is more intense under rock impact than under coal impact. A lower position, a faster velocity and a larger volume correspond to a more noticeable response difference in the caving mechanism. The vibration and fault sensitive areas of the caving mechanism are determined. This study has a reference significance for improving the caving mechanism's structural design and failure prevention. The conclusions provide guidance for a new intelligent coal rock identification technology based on vibration signals. [ABSTRACT FROM AUTHOR]

In longwall top coal caving (LTCC), due to the fracture and migration of top coal, the roof will break and collapse, which causes serious impact damage to hydraulic support. Therefore, we aimed to reveal the relationship between the roof instability effect and the bearing characteristics of hydraulic support in the LTCC face. Based on the occurrence conditions of the 08 mining area in the Shilawusu Coal Mine, the instability model of the upper immediate roof was established, and the working resistance of hydraulic support was derived. Secondly, the dynamic coupling model of roof-top coal-hydraulic support was established in LS-DYNA, and the crushing degree of top coal and the bearing characteristics of the hydraulic support in different roof instability fields were analyzed. The results show that the main factors affecting the working resistance of hydraulic support are the fracture position of the upper immediate roof, the acting force of the lower immediate roof, and the distribution of the gangue in the goaf. The rotary instability of the upper immediate roof at the coal wall brings serious impact effects, resulting in fractures in front of the coal wall and a large amount of crushed coal concentrated at the front end of the canopy. The crushing degree of top coal significantly impacts the canopy, especially the back end of the canopy and the hinged pin shaft, which is prone to bending fracture. The research results can provide references and experience for the stability control of roof strata and the structural optimization of hydraulic support. [ABSTRACT FROM AUTHOR]

In the process of top coal caving, coal gangue particles may impact on various parts of the hydraulic support. However, at present, the contact mechanism between coal gangue and hydraulic support is not entirely clear. Therefore, this paper first constructed the accurate mathematical model of the hydraulic cylinder equivalent spring stiffness forming by the equivalent series of different parts of emulsion and hydraulic cylinder, and then built the mesh model of the coal gangue particles and the support's force transmission components; on this basis, the rigid–flexible coupling impact contact dynamic model between coal gangue and hydraulic support was established. After deducing contact parameters and setting impact mode, contact simulations were carried out for coal particles impacting at the different parts of the support and coal/gangue particles impacting at the same component of the support, and the contact response difference in the support induced by the difference in impacted component and coal/gangue properties was compared and studied. The results show that the number of collisions, contact force, velocity and acceleration of impacted part are different when the same single coal particle impact different parts of the support. Various contact responses during gangue impact are more than 40% larger than that of coal, and the difference ratio can even reach 190%. [ABSTRACT FROM AUTHOR]

In the process of top coal caving mining, the caving time and the tail beam swing angle have an important impact on the evolution of the coal gangue boundary, which determines the top coal recovery rate and gangue content rate. Therefore, it is necessary to study the influence of the caving time and the tail beam swing angle on the top coal caving effect. For this purpose, based on Hertz–Mindlin contact theory, this paper established a simulation model of top coal caving and carried out a coal caving simulation with different caving times and tail beam swing angles. In the process of coal caving, under a specific tail beam swing angle and different caving times, this work studied the evolution characteristics of the coal gangue boundary. A simulation model of coal caving with variable time is established, and the influence mechanism of time on the coal caving effect is analyzed. Then, the evolution characteristics of the boundary are studied under different tail beam swing angles and the same caving time. A simulation model of coal caving with variable angles is established, and the influence mechanism of the tail beam swing angle on the coal caving effect is analyzed. Finally, the effects of caving time and tail beam swing angle on coal gangue discharge are studied, and the effect of coal gangue release under different working conditions is analyzed. The boundary data and the discharge data are extracted through the simulation, and contrast curves are drawn. The results show a limit position of the coal gangue boundary under the fixed working condition, which is the middle line position of the coal caving outlet. When the coal gangue boundary does not reach the limit position, there are two characteristics. First, the greater the tail beam swing angle is, the faster the deformation speed of the coal gangue boundary is. At the same caving time, the position of the coal gangue boundary will be closer to the coal caving outlet, which leads to excessive mixing of coal and gangue. Second, the longer the drawing time, the greater the deformation of the coal gangue boundary, and the easier the coal gangue is mixed, resulting in an increase in the gangue content of the discharged coal. When the coal gangue boundary reaches the limit position, the boundary will be basically stable near the top of the coal caving outlet. The limit position and shape of the coal gangue boundary are mainly affected by the density difference of coal gangue particles but not by the coal caving time and the tail beam swing angle. After the end of coal caving, the coal gangue boundary finally presents a double arch structure. The research in this paper has important reference significance for the selection of caving time and tail beam swing angle and further research. [ABSTRACT FROM AUTHOR]

The research on coal gangue "category" recognition via single classification algorithm for single-channel signal data shows that the classification and recognition capabilities of different algorithms on different channel signals and data types exhibit significant differences. In order to improve coal gangue classification and recognition effect, a coal gangue classification and recognition method of "multi-information fusion" based on the "parallel voting system (PVS)" was proposed in this study. The joint judgment of coal gangue "category" was completed through the combination of multiple algorithms or channel signal data with stronger recognition ability according to the voting principle of "the minority is subordinate to the majority". Based on the signal characteristics data obtained from the impact-slip test between coal gangue and the hydraulic support, three different modes of PVS-based coal gangue classification and recognition, namely, channel signal data PVS (SDPVS), algorithm PVS (APVS), and algorithm and channel signal data combination double PVS (algorithm-data double parallel, A&SDPVS), were respectively investigated herein. The influence of signals combination mode, algorithms matching mode as well as combined mode of signals and algorithms on coal gangue "category" voting recognition accuracy was studied. The research results show that for the SDPVS when a single algorithm with higher recognition accuracy and its corresponding multiple channel signal data with higher recognition accuracy were selected and for the A&SDPVS when the multiple "Recognition combination of single algorithm and single channel signal data" with higher recognition accuracy was selected, coal gangue classification and recognition effect could be improved. PVS-based coal gangue "category" recognition accuracy could reach up to 97.5%, which effectively improved coal gangue classification and recognition ability; moreover, the effectiveness of the multi-information fusion method proposed in this study was proven. [Display omitted] • Proposed three coal gangue "category" voting recognition methods and recognition processes. • Studied influence of signals and algorithms combination modes on voting recognition accuracy. • SDPVS and A&SDPVS can effectively improve recognition accuracy even to more than 97%, but APVS can't. [ABSTRACT FROM AUTHOR]

In top coal caving mining, common impact occurs between coal gangue particles and tail beam. Little attention has been paid to the effects of coal gangue particles failure on impact force and tail beam response theoretically, numerically, and experimentally. This paper aims to reveal the influence of coal gangue particles failure on the impact effect of tail beam. First, this paper incorporates the theory of rock failure and energy consumption to assess the impact process of coal gangue particles on the tail beam. A new model to simulate the actual failure conditions of rock particles was developed: the brittle damage-fracture particle model. By comparing damage phenomena and simulation data, the brittle damage-fracture particle model was proved to be correct. Based on this model, a dynamic simulation of brittle coal gangue particles impacting the tail beam was conducted. Then, the dynamic responses of the particles and tail beam were analyzed. The results show that particle failure significantly affects the impact force and dynamic response of the tail beam. The impact effects of coal and gangue particles on the tail beam and their failure energy consumption also differed significantly. This paper stresses the importance of coal gangue particle failure conditions for research on top coal caving mining. Theoretical support is provided for the research of coal gangue identification technology based on the tail beam vibration signal. [ABSTRACT FROM AUTHOR]

Advancing of the intelligent fully mechanized caving mining technology (IFMCMT) is the fundamental method to improve the output of coal resources. Accurate identification of coal gangue is the necessary condition for the realization of IFMCMT. To achieve coal gangue recognition, Internet of Things (IoT) technology and impact-slip contact characteristics based method for coal gangue "category" recognition is proposed in this paper. An IoT recognition system is constructed, then impact-slip test bed between coal gangue mixture and the hydraulic support is designed. Secondly, coal gangue "category" recognition parameters are discussed, hereby multi-dimensional contact characteristic information acquisition system is constructed. After that, impact-slip tests were carried out to extract and process the multi-source and multi-azimuth signals, and three kinds of data samples were obtained. Finally, 10 kinds of classification algorithms were selected for random classification recognition of coal gangue "caving category" and "shut down category". Coal gangue "category" recognition ability by algorithms, signal types and data types is compared, which provides the theoretical basis for further classification recognition effect improving research. Research show that coal gangue "category" random recognition accuracy can reach to 0.935 (Define the range of recognition accuracy as 1), which proves the effectiveness of "category" by IoT system and impact-slip contact characteristics. Coal gangue "category" recognition. [Display omitted] • Proposed a coal gangue recognition method based on impact-slip contact tests and IoT system. • Impact-slip test equipment between coal gangue mixture and the hydraulic support is put forward. • Multi-dimensional effective contact characteristic parameters for recognition are determined. • A multi-source and multi-azimuth information acquisition system is constructed. • Formulated coal gangue recognition procedure and realize coal gangue recognition. [ABSTRACT FROM AUTHOR]

Impact contact behaviors with different velocities, direction and contact states occurred in the process of coal drawing between coal gangue particles and the hydraulic support greatly increase the difficulty of coal gangue recognition in top coal caving. In order to finally realize coal gangue recognition in top coal caving, this paper studied the impact behavior of a single particle coal gangue and the metal plate at any position and the problem of the identification of coal gangue particles. First, the any position impacting test bench and test system is constructed, in which multipoint acceleration information acquisition space is built. Second, 2400 groups of random impact tests between coal gangue particle and the metal plate are conducted. Third, while each impact test was going on, acceleration signals in the seven different positions of the metal plate were collected. Forth, after all the impact tests are completed, signals are processed by segmentation and re-sorted by randomization. Then, the method of signals serial splicing is proposed to process the different position standardized signals obtained in each group of impact test, and coal gangue recognition is proposed based on processed signal data and SVM algorithm. After that, the effect of parameters on coal gangue recognition accuracy of SVM algorithm is studied, and the corresponding parameter settings of SVM are accordingly determined. Finally, coal gangue recognition was conducted by using SVM based on different data samples, the influence law of the training set data set expansion method and the test set data matching relationship, the number of tandem sensors and matching relationship, and the number of training set samples on coal gangue recognition accuracy were studied. The study will serve as the research basis for the application of SVM and signals serial splicing method in coal gangue recognition. [ABSTRACT FROM AUTHOR]

There are various forms of clearance at the connection of various parts of the hydraulic support. However, the influence of clearance has been ignored in various related research studies of the hydraulic support. In order to clearly grasp the accurate impact contact response law between coal gangue and the hydraulic support, the radial clearance in the pin shaft connection structure of the tail beam is considered for the first time in this paper. By constructing the theoretical contact model of the pin shaft connection, the difficulty of studying the interaction between coal gangue and the hydraulic support through theoretical solution is proved. On this basis, the finite element contact simulation analysis method is proposed to study the impact contact behavior between coal gangue and the tail beam. This paper constructed the finite element impacting simulation model between coal gangue and the radial clearance-contained tail beam structure and carried out impact contact simulation between coal gangue and the multiple clearance-contained tail beam structure as well as the changing clearance-contained tail beam structure, respectively, and contact responses of the tail beam structure such as the spring stress, the pin shaft test point stress, acceleration, and velocity of the tail beam test point under different working conditions are obtained. The influence law of clearance on different contact responses is studied, and the differences of contact responses after coal gangue impact between two clearance-contained tail beam structures and three clearance-contained tail beam structures are compared and analyzed. Research results show that, in the condition of multiclearance, the amplitude of each contact response when gangue is impacted is greater than that of coal. When the radial clearance of the connection unit increases from 0 to 0.25 mm, the overall fluctuation amplitude of the contact responses decreases. In 3-clearance state, increase of the radial clearance size of the connection unit will lead to the increase of the spring stress, the stress of the pin shaft test point, and the velocity of the tail beam test point gradually and the decrease of the acceleration of the tail beam test point. Throughout the research, the vibration response of the pin shaft can be taken as coal gangue recognition parameter. The work provides a theoretical basis for the study of the influence law of clearance on hydraulic support and provides a reference for the study of contact behavior between coal gangue and the hydraulic support. [ABSTRACT FROM AUTHOR]

The extremely poor loading performance of a thin coal shearer drum affects the mining efficiency in thin seam mining seriously on account of the restriction by the complicated mining environment and seam thickness. The coal loading performance of the drum is influenced by several complex factors, such as motion parameters and structural parameters, including the structure and form of the hub. The form of the drum hub is cylindrical in general, and in order to study the influence of the hub form on the coal loading rate of the drum, seven drums with different hub forms and structures were designed. The influence of the complexity of hub structures on the coal loading performance was studied by discrete element method (DEM) simulation in this paper. The change curves with the research object of different drums, such as coal loading rate, velocity field distribution, and contact force between fallen coal particles, were obtained. The results showed that the conical hub drum can improve the coal loading performance than the cylindrical hub drum, and the curve-shaped hub drum had a more obvious promotion on the coal loading performance. The coal loading rate increased first and then decreased with the increase of hub cone angle. Compared with the conical hub drum, the curve-shaped hub drum can not only improve the coal loading rate, but also has a larger space containing coal. This study has proposed a drum with a new form hub which could increase the coal loading rate, and the methods and conclusions provide the guidance for drum hub design. [ABSTRACT FROM AUTHOR]

To improve the safety and the stability of the support under mines and reduce the cost, we design a new slipper-type hydraulic support with energy-efficiency and high reliability. To study its dynamics, we build a reverse kinematics model. We analyze the motion and the force for each component of the new support with a simulation in Matlab/Simulink. The results show that it has appropriate structures with the required four-bar linkages. To compare the performance between the new slipper-type support and the traditional support, we design their mechanics models, deduce their mechanics relations and obtain the force curves for each component of both supports under the same loads. The results prove that the new slipper-type support has less demand on oil pressure for the hydraulic cylinder when working at middle and high positions and it has a larger supporting force and a higher supporting stability which would be more energy-efficient. [ABSTRACT FROM AUTHOR]

To explore how the cutting parameters affect the conical pick’s cutting force in coal cutting process, some simulation tests were carried with EDEM based on analysis of coal cutting process of conical pick and micro mechanical characteristic of coal particles. In this paper, traction speed, drum angular velocity, and installation angle of conical pick were considered as the main coal cutting parameters. The discrete element simulations were conducted under 7 sets of various cutting parameters, which were determined in the range of empirical parameters. From the results of the simulation tests, it can be concluded that the fragmentation of coal particles appears in a compacted, squeezed, and crumbling state in coal cutting process; the traction speed has the greatest impact on the conical pick’s cutting force and cutting force fluctuation and the influence of drum angular velocity and installation angle reduce in turn; the force and force fluctuation tend to decrease and obviously increase, respectively, with the increase of drum angular velocity and traction speed; and they will reach the minimum when the pick’s installation angle is 45° under certain traction speed and drum angular velocity. [ABSTRACT FROM AUTHOR]

Top coal caving is an important way of thick coal seam mining. The current coal gangue identification technology is not mature, resulting in a low degree of automation of coal caving. The current numerical simulation pays little attention to the real shape of rocks. This paper aims to reveal the vibration response of the tail beam under the action of real shape coal gangue particles. First, the real shape rock and hydraulic support model are established, and the relationship between the Rock Mixed Ratio (RMR) and the vibration signal characteristics during the impact process are studied. The influence of falling velocity and coal strength on this relationship are analyzed. Finally, the influence of motion mode on this relationship is analyzed and discussed. The numerical results show that the increase of the RMR can significantly enhance the velocity and acceleration signals of the tail beam, and the signals caused by different RMR are still different under different velocities and strengths. The best recognition effect can be obtained when the coal gangue particles slip on the hydraulic support, and the effect is the the worst when the coal gangue particles impact upon and roll on the hydraulic support. The conclusion provides directions for further study of coal gangue identification based on vibration. [ABSTRACT FROM AUTHOR]

The poor loading performance of shearer drums restricts the development and production efficiency of coal in thin coal seams. Changing operation and structural parameters can improve the drum's loading performance to some extent, but the effect is not obvious. A two-segment differential rotational speed drum (TDRSD) was proposed after analyzing the drum's influence mechanism on coal particles. To further reveal the drum's coal loading principle, the velocity, particles distribution, and loading rate were analyzed. The effect of the matching relationship of the rotational speed and helix angle between the front and rear drum are also discussed. The results show that a lower front drum rotational speed had a positive impact on improving the loading performance, and the loading rate first increases and then decreases with the increase in rear drum rotational speed. The optimal loading performance was obtained in the range 60–67.5 rpm. The front drum's helix angle had no evident effect on loading performance, and the loading rate increase with the increase in the rear drum's helix angle. The results provide a reference and guidance for operation parameters selection, structure design, and drum optimization. [ABSTRACT FROM AUTHOR]

• The construction process from eigenvector to eigenmatrix is realized. • A multi-layer time domain feature extraction method is proposed. • A method of eigenmatrices series based on multi-layer processing data is proposed. • A method of feature fusion based on cross-optimal selection (FFCOS) was proposed. Accurate and rapid recognition of coal gangue is an important link to realize automatic mining, which is helpful to improve the efficiency of coal mining and the safety of mining workers. Relevant studies have confirmed the effectiveness of coal gangue recognition based on tail beam vibration signal, but the recognition accuracy of a single point source vibration signal of tail beam is slightly low. In order to improve the practicability of coal gangue recognition method based on tail beam vibration signal, this paper takes the single source tail beam vibration signal as the object, improves the coverage of tail beam vibration characteristics by conducting experiments and extracting multiple vibration signals at different positions, and conducts the research on coal gangue recognition technology by multi-layer time domain feature processing and cross-optimal fusion of multiple signals. Firstly, through analysis of classification algorithm ability and coal gangue recognition principle, the coal gangue recognition process is formulated and the classification model is constructed. Then, based on the two data samples of a single signal eigenvector and multi-signal eigenmatrix obtained by Direct Data Statistics (DDS), the recognition research is carried out, and the recognition effectiveness of the eigenmatrix is verified. Based on this conclusion, the three-layers eigenmatrix data samples of DDS, EMD Data Statistics (EDS) and HHT Data Statistics (HDS) are obtained by multi-layer time domain feature processing, and the coal gangue recognition based on multi-layer eigenmatrix is carried out respectively. DDS is the most accurate signal processing method. On this basis, the construction method of DDS + EDS and DDS + HDS recognition eigenmatrix based on array series is studied, and the recognition ability of DDS + HDS recognition eigenmatrix construction method and Logic Regression algorithm is proved. Recognition accuracy based on DDS + HDS recognition eigenmatrix and Logic Regression algorithm is up to 95.25 %. Finally, in order to further improve the recognition accuracy and response speed, this paper proposes a method of feature fusion based on cross-optimal selection (FFCOS). Features of DDS and HDS are sorted by recognition sensitivity, and then cross-selected and fused according to this sort. The results show that the recognition accuracy of the serial construction method of DDS + HDS recognition eigenmatriX array and the Logistic Regression algorithm can reach 97 %, which proves the effectiveness of the FFCOS method and realizes the accurate recognition of coal gangue based on the vibration signal of single source tail beam. [ABSTRACT FROM AUTHOR]