Shearer Drum Research Articles

Analysis and Improvement of Coal-loading Performance and Reliability of Thin Seam Coal Shearer Drums

The structure of coal shearer drums significantly influences the transportation efficiency and load fluctuations of thin seam coal shearers. To enhance drum efficiency and reliability, this paper proposes a collaborative optimization method based on an improved NSGA-II algorithm. Initially, using the Discrete Element Method (DEM), we analyze the impact of helical blades on transportation performance and investigate novel designs for two types of coal-guiding drums. To optimize dynamic performance, concepts like spatial density and adaptive radius are introduced, proposing an NSGA-II enhancement strategy based on spatial density for the collaborative optimization of drum structure and motion parameters. Finally, the entropy-weighted TOPSIS method is used for subjective evaluation to select the optimal solution. Research findings demonstrate that this collaborative optimization method significantly enhances drum reliability, reducing load fluctuations by 46.34%, increasing transportation efficiency by 7.06%, and decreasing transportation power by 27.31%.

Spatiotemporal spreading characteristics of dust aerosols by coal mining machine cutting and "partition/multi-level composite field" atomization dust purification technology

To locally atomize the spatial confinement of primary dust generated by the shearer cut-off, the CFD-DPM mathematical model was used to simulate and analyze the wind-borne dust transport law, which resulted in the heavily polluted area of primary dust. A multi-level and multi-dimensional coal machine spray system was developed for the polluted area, its atomization effect was verified by using the TAB breakup model. The results show that the heavily polluted area of primary dust is mainly concentrated in the position of fully mechanized mining face Z=24–39 m area of shearer, and the average concentration is 738.2 mg/m³. The average concentration of droplets generated by the multi-level and multi-dimensional shearer spray system at the shearer drum is 0.66 kg/m³, with a percentage of droplets with particle size between 40 and 160 μm exceeding 85 %. The coverage rate of the shearer drum is 95 %. The relationship between droplet concentration and time is consistent with the Boltzmann function fitting model. Following the implementation of the multi-level and multi-dimensional coal machine spray system in the field, it was observed that the average reduction in dust levels was 90.9 % for total dust and 85.7 % for exhaled dust in the synthesized mining face.

Calculation of loads on cutting picks and moments in gears of shearer drums in cutting hard rock inclusions

Calculation of loads on cutting picks and moments in gears of shearer drums in cutting hard rock inclusions

Research on Calculation and Optimization Methods for Tooth Flash Temperature and Meshing Power Loss of the Gear System in Drum Shearer

The operating conditions of the drum shearer are very complex, and its ranging arm gear system often suffers from gear scuffing and wear. Gear scuffing is caused by the adhesive wear, which is due to the instantaneous friction and flash temperature of the tooth surface, and the gear meshing power loss is also caused by tooth surface friction. In order to resist tooth scuffing and improve meshing efficiency of the transmission system, an improved semi-analytical tooth surface flash temperature calculation method was used. The tooth flash temperature status under various working conditions were analyzed in detail. Based on the mechanical model of the shearer drum picks, the load condition of the drum was analyzed. Under these load and boundary conditions, the misalignments of each gear pair in the ranging arm were calculated. The tooth surface load distribution was calculated under the gear misalignments, and then the theoretical tooth surface flash temperature and meshing power loss were determined. Next, the tooth micro-geometry was modified to reduce flash temperature and meshing power loss. The flash temperature distribution pattern of the optimized tooth surface was studied under various working conditions, and the meshing power loss was also obtained. Finally, experiments were conducted to verify the effects of the optimized tooth surface on the friction temperature rise and the effectiveness of the modification method. Tooth surface optimization aimed at reducing tooth surface flash temperature can also effectively reduce meshing power loss, which has a significant effect on gear anti-scuffing and energy saving.

Design of Digital Twin Cutting Experiment System for Shearer.

This study presents an advanced simulated shearer machine cutting experiment system enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to accurately mirror the operational dynamics of actual mining cutters. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature, and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal rock identification research, offering significant insights into the nuances of shearer operation.

Coal falling trajectory and strength analysis of drum of shearer based on a bidirectional coupling method

The cutting and crushing of coal and rock containing gangue is the result of the coupling effect of multiple factors. The geometric parameters of the working mechanism, the kinematic parameters of the shearer, and the physical and mechanical properties of the coal and rock to be cut all affect the cutting and crushing process of the shearer. To study the coal falling trajectory of cutting coal and rock using a spiral drum, optimal cutting parameters were obtained, efficient cutting using a spiral drum was achieved, and analysis of the coal falling trajectory and strength of the drum of a shearer based on bidirectional coupling technology was proposed based on particle discrete element contact theory and virtual prototype technology. The discrete element method multi-flexible body dynamics two-way coupling method was used to obtain cutting and interactive information about the spiral drum for a complex coal seam with gangue. The cutting conditions of the spiral drum under different cutting depths, rotational speeds, and traction speeds were determined. The movement status of coal and rock particles was monitored under different working conditions. Coal falling trajectory equations for the coal and rock particles were compiled under different working conditions, and the coal falling trajectory curve was drawn. The optimal coal loading rate was used as the measurement standard for the coal falling trajectory, and the optimal coal falling trajectory of the drum was obtained through full factor experiments. The load of the drum and pick was extracted, their stress and deformation were analyzed, and fatigue life analysis was performed on the pick with the highest stress. The results indicate that the maximum deformation occurs on the cutting teeth that are cutting hard gangue. The stress of the tooth seat is mainly concentrated at the root of the tooth seat, and its maximum equivalent stress is less than the yield limit value of the selected material. Therefore, the material selection and structural design of the drum are safe and reliable. By building a coal mining machine cutting coal and rock experimental platform and monitoring the working status of the designed spiral drum, it meets the usage requirements. Based on industrial experiments conducted underground, the measured average coal loading rate of the shearer drum was 46.31%, achieving stable operation and verifying that the designed drum of the shearer has an efficient cutting ability.

Optimization design of shearer drum height adjusting mechanism based on particle swarm optimization algorithm

The underground working environment of the shearer is complex and the working conditions are relatively poor. It is necessary to continuously adjust the height of the rocker arm during the operation, improve the operation efficiency, and improve the ability of the shearer to adapt to the more complex coal seam working environment. In order to optimize the structure of the shearer adjustment mechanism, the strength and strength of the adjustment mechanism are improved by increasing the size and angle of the adjustment mechanism and reducing the size and angle. Therefore, an optimized particle group design method is proposed to optimize the drum adjustment mechanism of the shearer. Seven parameters such as large lever, small lever and maximum swing angle are selected as design variables. Under the condition of limiting mining height and rocker length, an optimization model with rolling angle and cylinder stress as objective functions is established. The working characteristics of each part of the coal machine height adjustment mechanism are analyzed. The particle swarm optimization algorithm is used to optimize the key parameters, and the optimization results are verified to ensure their accuracy. The optimization results are compared with the original parameters. The results show that compared with the pre-optimization, the cylinder stroke is shortened by 17.9%, the cylinder length is shortened by 8.94%, the rolling angle is reduced by 2.83%, the cylinder tension is reduced by 12.1%, and the rocker bending moment is increased by 6.83 %, which meets the original design goal. Therefore, the research provides a reference for the optimal design of the coal machine height adjustment system.

Influence of coal cowl parameters on the coal loading process of thin coal seam shearer drum

The low loading rate of the thin coal seam shearer drum is a severe obstacle to the efficient mining of thin seam resources, and the auxiliary drum loading through the cowl is an effective measure to alleviate this situation. However, the working mechanism of the coal cowl still remains unclear. In this paper, with the help of the discrete element method and the modeling experiment method, the effects of coal cowl’s offset distance, tilt angle and wrap angle on the coal loading rate under different loading modes of the drum are investigated; and the significance of various factors and their interactions to the drum coal loading rate is explored by designing response surface experiments. The findings show that a monotonous negative correlation between the offset distance of the coal cowl and the coal loading rate is identified, and that a smaller offset distance can effectively improve the coal loading rate of the drum. The conveying torque is significantly increased, easily inducing the drum choking, coal recycling coal over-crushing. Along with the increasing tilt angle, the rate of ejection loading decreases monotonically, and the rate of pushing loading increases first and then decreases. Coal loading rate is weakly affected by changes in coal cowl’s wrap angle. The results of response surface analysis reveal that the most significant factors affecting the drum’s coal loading rate are tilt angle and offset distance in ejection and pushing loading modes, respectively. The conclusions drawn here offer implications for improving the coal loading performance of the thin coal seam shearer drum, as well as certain guidance on the optimal design of coal cowl parameters.

A numerical simulation study on the distribution of cutting dust and airflow in a fully mechanized mine face based on rotating fluid theory

The turbulent airflow generated by the shearer's rotation has a significant impact on the spread of cutting dust. In this study, the actual shearer drum was used as a physical model, and the MRF method was applied to simulate coal cutting operations with consideration of rotating fluid, accurately reproducing the turbulent airflow generated during cutting. By comparing the different simulation results, it is found that: the wind flow under systematic ventilation is gentle and even, while the cut-off wind flow generated by "inlet" has a great impact on the coal mining area in terms of scope and degree, and the horizontal and vertical dispersion is very strong, with a large amount of wind flow shifting in the range of 17 m < x < 36 m, and the dust mass concentration increasing rapidly; When the MRF method is adopted, the wind flow disperses more gently, and the dust is shifted to the pavement within the ranges of 19 m < x < 25 m and 27 m < x < 36 m, which makes the dust distribution more uniform and continuous in space, and forms a dust belt with high concentration of about 10 m in length on the downwind side of the front drum, which is more in line with the production reality.

Analysis of the Influence of Surrounding Rock State on Working Performance of Cutting Head in Metal Mining

Continuous mining is one of the development goals for metal mines, and the application of coal mining equipment represented by shearers provides a reference for continuous mining. However, rock in metal mines is generally harder than coal, making cutting difficult. Improving the surrounding rock conditions is an important way to improve the applicability of the drum for hard rock cutting. Therefore, this article explores the correlation between drum-cutting performance and surrounding rock boundary conditions, aiming to obtain surrounding rock boundary conditions that can help improve drum-cutting performance. To achieve the goal, a model of a shearer drum and hard rock is established using finite element software. With the model, hard rock cutting was simulated and the stress distribution on rock mass, deformation of rock mass, and drum cutting force during the cutting process under different confining pressures were analyzed. Relations between drum cutting force and confining pressure on rock mass were obtained. Then, drum cutting force under different free surfaces of rock mass are studied and the positions of free surface on rock mass that help to reduce the drum cutting force were summarized. According to the research, when the rock mass is under uniaxial compression, drum cutting force increases with the confining pressure on the rock mass; In addition, the free surfaces on the rock mass are proved to be helpful to reduce the drum cutting force. The research content lays the foundation for the boundary conditions required to reduce drum-cutting force in metal mining.

Research on the Mechanism and Characteristics of Ultrasonically Coupled Mechanical Rock-Breaking Pre-Fracturing Technology

In this paper, we propose an ultrasonically coupled mechanical rock-breaking technology, creatively design an ultrasonically coupled mechanical rock-breaking drum, concurrently develop an ultrasonic cracking simulation method based on test coordination, and study the cracking mechanism and characteristics of ultrasonically pre-broken rock in order to increase the rock-breaking efficiency of shearer drums and lengthen pickaxe service life. To further understand the theory behind ultrasonic-coupled mechanical rock breaking, the operation of a fusion drum and the implications of ultrasonic field theory in a solid medium are first examined. Second, the impact and mechanism of the ultrasonic pre-crushing of the target red sandstone are investigated in conjunction with conducting a rock uniaxial compression test and RFPA2D modeling. Furthermore, an ultrasonic pre-crushing fracturing mechanism test of the target red sandstone further reveals the effect and mechanism of ultrasonic fracturing. The efficacy of ultrasonic-coupled mechanical single-cutter cutting is then investigated using the discrete element cutting model (PFC2D) of red sandstone. The results show that under the action of ultrasonic waves with an excitation frequency of 41 kHz, cracks can effectively be produced inside the rock mass of the target red sandstone, and the cumulative amount of acoustic emission is as high as 513, which reduces the strength of the rock mass and disintegrates its internal structure; the average cut-off force of the purely mechanical rock-breaking mode is 6374 N, and that of ultrasonically coupled rock breaking is 4185 N, which is a reduction of 34.34%, and can be attributed to the fact that ultrasonic waves can loosen the structure of the rock mass. This is explained by the ability of ultrasonic vibrations to weaken the structure of rock. The coupled rock-breaking technology not only simplifies mechanical cutting and rock breaking but the lower force can also reduce a pick-shaped trunnion’s wear failure cycle. This improves the environment for subsequent pick-shaped trunnion cutting and rock breaking and prevents the pick-shaped trunnion from being subjected to high-stress loads for an extended period of time so as to prolong its working life.

Intelligent Identification Method of Shearer Drums Based on Improved YOLOv5s with Dark Channel-Guided Filtering Defogging

In a fully mechanized mining face, there is interference between the hydraulic support face guard and the shearer drum. The two collisions seriously affect coal mine production and personnel safety. The identification of a shearer drum can be affected by fog generated when the shearer drum cuts forward. It is hydraulic support face guard recovery, not the timely block shearer drum, that will also affect the recognition of the shearer drum. Aiming at the above problems, a shearer drum identification method based on improved YOLOv5s with dark channel-guided filtering defogging is proposed. Aiming at the problem of fog interference affecting recognition, the defogging method for dark channel guided filtering is proposed. The optimal value of the scene transmittance function is calculated using guided filtering to achieve a reasonable defogging effect. The Coordinate Attention (CA) mechanism is adopted to improve the backbone network of the YOLOv5s algorithm. The shearer drum features extracted by the C3 module are reallocated by the attention mechanism to the weights of each space and channel. The information propagation of a shearer drum’s features is enhanced by such improvements. Thus, the detection of shearer drum targets in complex backgrounds is improved. S Intersection over Union (SIoU) is used as a loss function to improve the speed and accuracy of the shearer drum. To verify the effectiveness of the improved algorithm, multiple and improved target detection algorithms are compared. The algorithm is deployed at Huangling II mine. The experimental results present that the improved algorithm is superior to most target detection algorithms. In the absence of object obstruction, the improved algorithm achieved 89.3% recognition accuracy and a detection speed of 48.8 frame/s for the shearer drum in the Huangling II mine. The improved YOLOv5s algorithm provides a basis for identifying interference states between the hydraulic support face guard and shearer drum.

Effects of Ni-based composite coatings on failure mechanism and wear resistance of cutting picks on coal shearer machine

The performability and wear resistance of the cutting picks play an important role in the extraction operation of mining machinery especially drum shearers in longwall coal mines. Tungsten carbide tip fracture and removal, and severe wear of the pick body are the major failures that affect the performance of these picks. The coating could be a proper solution for strengthening the coal-cutting tools and extension of their useful life. In this paper, a Ni-based ultrafine coating, NiBSiFeWC, deposited by laser-cladding technique, has been applied to improve the wear resistance and mechanical properties of the coal-cutting picks. All cutting tests were carried out on a drum shearer machine and on a real-scale operation, which makes the study much more realistic and effectively applicable for advanced tools’ developments in mechanized longwall mines. The archived results show that NiBSiFeWC coating reduced the tool wear rate by about 50%.

An evaluating-while-cutting method for interface measurement -based on signals from dynamic contact force

In coal mining industry, direct measurement on rock proportions is difficult due to various rock material properties. Aiming at identification of coal and rock interface, the paper proposed a method by indirect measurement on rock proportions with contact force and some measures to improve the measurement accuracy as well. To establish the measurement model, cutting forces under different kinds of working states are studied with theoretical analysis and the relations between rock proportions and dynamic force are established. For validation, general circumstances with various rock properties and motion parameters in mining process are studied and estimation results of rock proportions in those circumstances are analyzed. Results show that the measurement accuracy is stable even if parameters related with rock properties and drum working parameters are different. Therefore, the mentioned parameters are no longer essential in advance for indirect measurement of rock proportion. In addition, stochastic fragmentation of coal or rock always leads to fluctuation on measurement accuracy. With the improved cluster method, the mean accuracy of this model are close to 90% and sometimes, the measurement accuracy is even more than 95%. The method in this paper is meaningful for identification of coal and rock interface and in this way could guide the shearer drum to avoid hard rock to reduce the damage on mining equipment.

Intelligent Height Adjustment Method of Shearer Drum Based on Rough Set Significance Reduction and Fuzzy Rough Radial Basis Function Neural Network

The intelligent adjustment method of the shearer drum is the key technology to improve the intelligent level and safety degree of fully mechanized mining face. This paper proposes a shearer drum intelligent height adjustment model based on rough set significance attribute reduction (AR) and fuzzy rough radial basis function neural network (FRRBFNN) optimized by adaptive immune genetic algorithm (AIGA). The model first selects the parameters of shearer process monitoring based on the importance attribute reduction algorithm of rough set, and establishes the attribute reduction set of shearer operation characteristic parameters and the drum height decision rule base. Next, a fuzzy rough radial basis function neural network determined by the decision rule space is proposed. By introducing the fuzzy rough membership function as the connection weight, the network can accurately describe the complex nonlinear relationship between the working characteristic parameters of the attribute shearer and the drum height, and measure the uncertainty of the coal seam distribution. Finally, to further optimize the performance of FRRBFNN, the adaptive immune genetic algorithm is introduced to optimize its parameters, to build a high-precision shearer drum height prediction system. For the evaluation method of the model, we use three indicators: mean absolute error, mean absolute percentage error, and root mean square error. Based on the measured data in Yujialiang area, Shaanxi Province, the experimental results show that—compared with the FRRBFNN and support vector regression (SVR) models, a gated current neural network (GRU), a radial basis function neural network (RBF), the memory strengthen long short-term memory (MSLSTM) model, and the adaptive fuzzy reasoning Petri net (AFRPN)—the MAE of the AR-AIGA-FRBFNN model for predicting the height of the left and right rollers are 18.3 mm and 17.2 mm, respectively; the MAPE is 0.96% and 0.93%, respectively; and the RMSE is 21.2 mm and 22.4 mm, respectively. The AR-AIGA-FRBFNN model is therefore more effective than the other considered methods.

Retracted: Research on intelligent elevation control method of shearer drum based on deep learning

AbstractRetraction: [Pu Zhang, Research on intelligent elevation control method of shearer drum based on deep learning, IET Software 2023 (https://doi.org/10.1049/sfw2.12089)].The above article from IET Software, published online on 17 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

Analysis on the influence law of traction speed on the cutting performance of coal containing hard concretion

Due to the great differences in mechanical properties between hard concretion and coal, the shearer drum cutting coal and rock containing hard concretion will inevitably lead to a series of problems, such as severe load impact, increased cutting specific energy consumption and low coal loading efficiency. Taking the cutting part of a thin coal seam shearer in service in the target mining area as the prototype, the mechanical models of shearer drum and rocker arm are established by using UG, and the discrete element model of coal wall with hard concretions is built by importing it into EDEM. The influence law of traction speed on coal loading rate, drum load and cutting specific energy consumption is analyzed, and the corresponding fitting relationship function is obtained. Taking the traction speed as the design variable, and the drum load, cutting specific energy consumption and coal loading rate as the comprehensive indicators, a multi-objective optimization function is established. The optimal solution is obtained by using NSGA II optimization algorithm, and the accuracy of the simulation is verified by experiments. This method has certain engineering significance for the reasonable selection of shearer traction speed.

Research on indirect measurement and estimation method of shearer drum cutting load

For the difficult problem that the shearer drum load is difficult to be detected and perceived directly, a shearer drum load indirect estimation measurement method and technique is proposed and invented. Based on the structural characteristics of the rocker arm, the basic rod system skeleton of the rocker arm is extracted. Based on the transfer route of the drum load on the rocker arm, the feasibility of using the rocker arm pin shaft load for drum load prediction is analyzed, and the correlation mechanics equation of load from the drum to the rocker arm pin shaft is constructed. To address the statically indeterminate problem in the equation, the Lagrange multiplier is introduced to construct the energy function of the rocker rod system skeleton. Based on the principle of minimum complementary energy and solving the extreme value of energy function, the statically indeterminate equation is transformed into the statically determinate equation, and a rough prediction model of drum load based on the force of the rocker arm hinged ear pin shaft is derived, and the maximum relative error of the model is 25.15 %. To address the low prediction accuracy of the model due to the dynamic characteristics of the drum rocker arm, the drum load is derived from the rocker arm hinged ear pin shaft load and the rough prediction model as input, and the experimentally measured drum load as output. The bp neural network error correction model is constructed, and the accurate estimation and perception of the drum load are realized by the prediction model and the bp neural network correction model. Finally, the accuracy of the prediction algorithm is verified by experiments. The results show that after correction by bp neural network, the average error of the drum three directional force is 0.14 × 104N ∼ 0.55 × 104N, the mean square error is 0.18 × 104N ∼ 0.65 × 104N, and the relative error is 3.99 %∼10.12 %. The average error of the drum three directional moment is 0.31 × 104N·m ∼ 0.40 × 104N·m, the mean square error is 0.16 × 104N·m ∼ 0.50 × 104N·m, and the relative error is 2.04 %∼11.44 %. The accuracy of drum load prediction is higher than 11.44 % in all cases. The research results can provide theoretical and technical support for intelligent shearer design, development, and healthy operation and maintenance.

Optimization of Shearer Drum Based on Multi-Objective Bat Algorithm with Grid (MOBA/G)

The shearer drum undertakes the main function of coal falling and loading, and picks distributed on it have a great impact on the performance of the drum. However, few studies have optimized the pick and drum at the same time. In this paper, parameters of pick and drum are considered as design variables, and the response functions of design variables are established based on the central composite experiment method. The optimal structural and working parameters of the pick and the drum of MG500/1130-WD shearer are obtained by using the multi-objective bat algorithm and multi-objective bat algorithm with grid, respectively. Comparing results of the two algorithms, the multi-objective bat algorithm with grid is more effective in improving the comprehensive performance of the drum. According to the optimized design variables, a coal mining test is carried out to verify the optimization effect of the algorithm. The result provides some theoretical references for the design and production of the drum and has some engineering application value.

Improvement of Measurement Method and Design of Intelligent Sensor for Shearer Drum Height

The shearer drum height measurement plays a crucial role in the fully mechanized mining face. This paper proposes a measurement method of drum height, taking the ranging arm swing-angle and fuselage attitude angle into consideration; therefore, compared with the existing drum height measurement methods, our approach adheres more to the actual operating conditions of the shearer. Based on our approach, we further developed a shearer drum height sensor. Firstly, TLE5012B (MEMS magnetic angle chip) and MPU6050 (MEMS inertial navigation chip) are selected as the sensing elements of swing-angle and attitude angle, respectively. Secondly, a &#x201C;rocker-rotating shaft&#x201D; is designed to convert the swing-angle into the rotation of TLE5012B&#x2019;s external magnetic field. Thirdly, an intelligent drum height sensor based on DSP-TMS320F28335 is developed, including hardware circuits and software that measure and process the angle data, calculate the drum height, store and display the data, and transmit the data by CAN or WIFI. Fourthly, the magnetic field distribution and vibration source of the shearer are simulated and analyzed, and the magnetic shielding shell and anti-vibration device are designed to reduce the influence of external factors on the sensor. Furthermore, a sensor prototype was developed and experimentally tested. The maximum absolute errors of sensor swing-angle, pitch angle, roll angle, and drum height were 0.16&#x00B0;, 0.07&#x00B0;, 0.06&#x00B0;, and 6.7mm, respectively. Finally, we establish a measurement error model of shearer drum height and calculate the maximum measurement error is 2.24cm. The results show that our approach and sensor meet the requirements of shearer drum height measurement.