工矿自动化

Digital twin: meeting the technical challenges of intelligent fully mechanized working face

GE Shirong, WANG Shibo, GUAN Zenglun, WANG Xuesong, AN Wenlong, LYU Yuanbo, CHEN Shuhang

2022, 48(7): 1-12. doi: 10.13272/j.issn.1671-251x.17959

<Abstract>(534) <HTML> (109) <PDF>(117)

Abstract:
The goal and task of intelligent fully mechanized working face are to independently complete the reliable coal cutting of the fully mechanized working face, maintain the geometric relationship of the working face and reliable roof support. According to the goal and task, the key technologies of intelligent control of fully mechanized working face are proposed. The technologies include shearer positioning technology, working face visualization technology, hydraulic support electro-hydraulic control technology (device), working face communication technology, collaborative control technology of fully mechanized mining equipment, autonomous height adjustment technology of shearer, autonomous straightening technology of working face and surrounding rock support control technology of working face. Among these technologies, the first three technologies belong to the perception and execution layer of intelligent fully mechanized working face. The working face communication technology is the transmission layer of intelligent fully mechanized working face. And the last four technologies belong to the decision-making layer of intelligent fully mechanized working face. The challenges faced by the intelligent fully mechanized working face are pointed out, which are that the autonomous decision-making capability of the decision-making layer cannot adapt to the complex and changeable working conditions, and the perception and execution layer cannot support the information demand of the decision-making layer and the reliable execution of the decision-making instructions. In order to solve the above challenges, the digital twin system architecture of fully mechanized working face is proposed by use of the simulation-based digital twin modeling method. The virtual entity of the digital twin system of the fully mechanized working face comprises a mechanism model and a behavior model. The unmeasurable data of a physical system of the fully mechanized working face equipment can be obtained by the mechanism model. The behavior model can provide holographic information reflecting the running state of the physical equipment for an intelligent control system of the fully mechanized working face. Thus the problem of the lack of data information in the decision-making layer is solved. The off-line run mode of the combination of the mechanism model of fully mechanized mining equipment and its control system forms the hardware in the loop simulation system of fully mechanized working face, which provides a test platform for intelligent control algorithms based on process rules. The off-line run mode of the combination of the mechanism model, behavior model and its control system of the fully mechanized mining equipment forms the calculation experimental system of the fully mechanized working face, which provides a test platform for the development of the real independent decision-making complex algorithm of the intelligent control system of the fully mechanized working face.

Research on pose measurement system of cantilever roadheader based on laser target tracking

XUE Guanghui, LI Yuan, ZHANG Yunfei

2022, 48(7): 13-21. doi: 10.13272/j.issn.1671-251x.17967

<Abstract>(158) <HTML> (21) <PDF>(31)

Abstract:
The accurate and rapid measurement of the roadheader pose is the premise and foundation of intelligent heading in coal mine roadway. The existing cantilever roadheader pose measurement has the problem of non-absolute pose measurement, low measurement precision, complex arrangement, or only a few pose parameters being measured. The measurement can not meet the intelligent heading requirement. In order to solve the above problems, based on the pose measurement method of the cantilever roadheader based on laser target tracking, a pose measurement system of cantilever roadheader based on laser target tracking is designed. The system consists of a laser tracking device and a laser target. The laser tracking device is arranged behind the roadway, emits laser to the laser target arranged on the cantilever roadheader fuselage, and tracks the movement of the laser target. By solving the conversion matrix between coordinate systems such as laser tracking device, laser target, roadheader and roadway, six absolute pose parameters such as heading direction position, offset, height, deviation angle, pitch angle and roll angle can be measured. The full parameter real-time measurement of absolute pose of cantilever roadheader in roadway coordinate system is realized. The error influence factors of the system are analyzed, and the error distribution law is obtained by simulation. With the increase of heading distance, the pose measurement error of roadheader changes within a certain range. The measurement errors of offset and height increase linearly. Within the measurement range of 5-80 m, the measurement errors of the deviation angle, pitch angle and roll angle of the roadheader are less than 1.4, 1, 0.03° respectively. The measurement error of the heading direction position is less than 5 mm, and the measurement errors of offset and height are less than 20 mm. Using the crawler robot chassis, an experimental system for pose measurement is built. The pose measurement experiment is carried out in the simulated roadway. The results show that the measurement errors of the heading direction position, offset and height are less than 5 mm. The measurement error of the deviation angle is less than 1°. The measurement error of the pitch angle is less than 0.6°. And the measurement error of the roll angle can be ignored. The results are consistent with the simulation results, which proves the reliability of the system.

Research on coal-rock interface distribution perception based on near-infrared spectra

YANG En, WANG Shibo, XUAN Tong

2022, 48(7): 22-31, 42. doi: 10.13272/j.issn.1671-251x.17950

<Abstract>(185) <HTML> (31) <PDF>(24)

Abstract:
Near-infrared reflectance spectra can distinguish coal and rock based on the difference of reflectance spectra characteristics caused by different intrinsic material attributes of coal and rock. This method has high identification accuracy and good real-time performance. But it has not been used for identification of coal-rock interface position distribution. According to the demand for self-determination of the coal-rock interface in the subsequent cutting cycle of shearer memory cutting, the precise distribution sensing technology of coal-rock interface based on near-infrared reflectance spectra technology is studied. A coal-rock interface platform is built by using gas coal and carbonaceous shale cutting block samples. A spectrum detector integrated with optical fiber collimator and tungsten halogen light source is designed and installed on the shearer's body. The near-infrared (1 000-2 500 nm) backward reflectance spectra curves of coal and rock near the coal-rock interface are measured at three walking velocities of the shearer (0, 3, 7 m/s) and four scanning angular velocities of the spectrum detector (3, 4, 5, 6 °/s). For all the reflectance spectra collected by the spectrum detector in each scanning track on the coal wall, the unsupervised identification of coal-rock reflection spectra is carried out based on cosine distance fuzzy C-means clustering (CFCM) in the differential characteristic wave bands of 2 150-2 250 nm. According to the detection results of each position on each scanning trajectory, the theoretical detection position of the coal-rock interface point is determined based on the height difference weighting method and scanning trajectory equation. The research result shows that under each movement state of the shearer and the spectrum detector, the near-infrared reflectance spectra in the backward direction of gas coal and carbonaceous shale collected by the integrated optical fiber collimator tungsten halogen light source spectrum detector have obvious differential absorption valley bands around 1400, 1900, 2200 nm. The reflectance spectra curves of coal and rock all show a downward trend with the increase of the detection incident angle. With the increase of the scanning angular velocities of the spectrum detectors under the same walking velocity of the shearer, and with the increase of the walking velocity of the shearer under the same scanning angular velocity of the spectrum detector, the reflectance spectra curves of coal and rock tend to be flat as a whole. Based on CFCM, height difference weighting method and coal wall scanning trajectory equation, rapid and precise detection of coal-rock interface points under the movement of the shearer and spectrum detector can be realized. Among them, the root mean square error of the detection results of coal-rock interface points under three scanning angular velocities of spectrum detectors 3, 4, 5 °/s is not more than 1.5 cm. The research provides a reference for the application of near-infrared reflectance spectra technology to the precise and efficient perception of coal-rock interface distribution.

Development of coal and rock identification device based on near-infrared spectroscopy

LYU Yuanbo, WANG Shibo, GE Shirong, ZHOU Yue, WANG Saiya, BAI Yongtai

2022, 48(7): 32-42. doi: 10.13272/j.issn.1671-251x.17953

<Abstract>(212) <HTML> (49) <PDF>(46)

Abstract:
The current near-infrared spectroscopy identification of coal and rock is to collect spectral data in a static state for offline identification. The technology cannot meet the need for real-time identification of high-speed moving coal and rock on conveyor during caving operation. In order to solve this problem, a coal and rock identification device is developed based on near-infrared spectroscopy technology. The device consists of a data acquisition and processing device, and a light source and probe integrated device. The light source and probe integrated device is used to collect the reflected light of coal and rock. The improved coal and rock identification algorithms (cosine angle algorithm and correlation coefficient method) in the data acquisition and processing device is used to analyze the spectrum data. The spectrum information can be analyzed immediately after obtaining a coal and rock spectrum curve. Then the current coal and rock type can be determined. In order to obtain the best characteristic band and standard spectral library size of the improved coal and rock identification algorithms, the effects of different characteristic bands and standard spectral library sizes on the identification accuracy are obtained through experiments. The characteristic widths of 1 300 -1 500 nm, 1 800-2 000 nm and 2 100-2 300 nm are suitable for most coal and rock samples. The size of the standard spectral library is positively correlated with the accuracy. It is necessary to increase the number of curves in the standard spectral library during identification. In order to improve the spectral quality collected by the coal and rock identification device, the relative motion of coal and rock and the light source and probe integrated device is simulated in the laboratory. The influence law of different spectral acquisition parameters on spectral quality is explored. The integration time mainly refers to the light intensity of the light source. When the acquisition conditions are good, the integration time should be set to be slightly higher than the lower limit by 5-10 ms. For the fully mechanized top coal caving face, the real-time requirement of coal and rock identification is high, and the coal and rock on the scraper conveyor change rapidly during the coal caving process. The integration number is set to one for the best. The smoothing times mainly refer to the speed of environmental fluctuation, which can be set to eliminate the change of ambient light. In order to improve the identification accuracy of coal and rock identification device in the coal flow movement state of working face, the identification accuracy of improved cosine algorithm and correlation coefficient method in the relative movement of coal and rock and light source and probe integrated device is explored. The improved correlation coefficient method is more suitable for the identification algorithm used in working face, and the accuracy rate is 91.3%. The results of the coal and rock identification test in coal mine show that after collecting the spectral curves of coal and rock in a coal drawing cycle, the device immediately analyzes the spectral information and determines the current coal and rock category by the improved identification algorithm. The device realizes the real-time identification of coal and rock in the coal drawing process.

Research on the cantilever roadheader positioning based on near-infrared binocular stereo vision

WANG Xue, ZHOU Hongxu, ZHANG Lei, WANG Huaying

2022, 48(7): 43-51, 57. doi: 10.13272/j.issn.1671-251x.17896

<Abstract>(187) <HTML> (26) <PDF>(34)

Abstract:
The existing roadheader has problems, such as unable real-time positioning, inaccurate positioning, and positioning failure caused by camera view occlusion in visual positioning. In order to solve the above problems, a positioning scheme of the cantilever roadheader based on near-infrared binocular stereo vision is proposed. A near-infrared LED target is arranged on the fuselage and arm of cantilever roadheader. Taking LED as the near-infrared target, the characteristic information of the roadheader is constructed. The three-dimensional spatial positioning of the roadheader fuselage and the cutting part is realized through image processing and pose calculation. The binocular stereo vision camera is arranged at the top of a roadway. The distance between the roadheader and the binocular stereo vision camera gradually increases as the roadheader continues to advance. It leads to the failure of binocular image acquisition, which leads to the failure of the visual solution of the pose of the cutting part. In order to solve this problem, a magnetic field assisted positioning method of the cutting part based on one-dimensional convolution neural network (1D-CNN) is introduced. Three-axis digital magnetometers are arranged on two sides of the fuselage of the roadheader. The permanent magnet is arranged on the machine arm. The strength component of a magnetic field and pose data obtained by binocular stereo vision camera are used as training data to construct the 1D-CNN model, and the pose of a cutting part of the roadheader is output under the condition that vision measurement fails. The cantilever roadheader positioning based on near-infraared binocular stereo vision scheme is tested from the aspects of depth information and its fuselage of the roadheader and the cutting position are verified. The results showed that the measurement error of the fuselage is within ±11 mm, and the relative error is within 0.4%. The measurement error of the cutting part is within ±50 mm, and the relative error is within 1%.The relative pose error between the roadheader fuselage and the cutting part is within ±2.5°, the root-mean-square error of the pitch angle is 0.930 1°, and the root-mean-square error of the yaw angle is 0.922 0°. The errors are within the allowable range of roadway operation. The results show that the cantilever roadheader positioning scheme based on near-infrared binocular stereo vision is effective and reliable. The effectiveness of the magnetic field assisted positioning method based on 1D-CNN is verified. In order to simulate the complex magnetic field environment in coal mine underground, the interference magnetic source is randomly added near the roadheader. The results show that the predicted values of the pitch angle, yaw angle and rolling angle of the cutting part of the roadheader by this method are basically consistent with the measured real values. The determination coefficients of the predicted pitch angle, yaw angle and rolling angle are 0.992 4, 0.995 9 and 0.917 4 respectively. It shows that the magnetic field assisted positioning method of the cutting part of the roadheader based on 1D-CNN can better meet the positioning requirements of the roadheader in the case of visual positioning failure.

Shearer positioning method based on non-holonomic constraints

SONG Danyang, YANG Jinheng, TAO Xinya, LU Chungui, TIAN Muqin, SONG Jiancheng

2022, 48(7): 52-57. doi: 10.13272/j.issn.1671-251x.2022020006

<Abstract>(227) <HTML> (24) <PDF>(21)

Abstract:
At present, the shearer positioning method is based on the combination of the inertial navigation system and odometer. The method directly uses the output of the odometer to correct the shearer forward speed calculated by the inertial navigation system. However, the capability of suppressing the error divergence of the inertial navigation system is very limited. The shearer in the process of movement meets the characteristics of the non-holonomic constraints. When the shearer does not jump and sideslip, the lateral velocity and vertical velocity at the connection between the traction gear and the crawler are zero. Based on this characteristic, a new shearer positioning method based on non-holonomic constraints is proposed on the basis of the combination of the inertial navigation system and odometer. The output of the inertial measurement unit arranged in the middle of the shearer's body is mechanically arranged, so as to obtain the attitude, speed and position information of the shearer. The output of the odometer installed on the traction gear of the shearer is used to calculate the instantaneous velocity of the shearer. The Kalman filtering state equation is established by using a mechanical arrangement result of the inertial navigation system and an error propagation model. The non-integrity constraint is introduced at the joint of a traction gear and a crawler of the shearer. The Kalman filtering observation equation is established by using the difference between the velocity projected at the joint by the inertial navigation system and the velocity output by the mileometer as an observation vector. The output of the inertial navigation system is modified by using the results of the Kalman filtering algorithm as error feedback. Then the optimal estimation of the attitude, speed and position of the shearer is obtained. The experimental results show that compared with the traditional combined positioning method of inertial navigation system and odometer, the positioning error does not diverge with time after the non-holonomic constraint is added. The positioning method has good tracking performance on the actual trajectory. The positioning errors of the shearer in the forward, lateral and vertical directions are reduced by 66%, 62% and 67% respectively.

Study on dynamic modification method of 3D model of coal seam in fully mechanized working face

LIANG Shua, WANG Shibo, GE Shirong, BAI Yongtai, XIE Yang

2022, 48(7): 58-65, 72. doi: 10.13272/j.issn.1671-251x.17956

<Abstract>(186) <HTML> (36) <PDF>(29)

Abstract:
The high-precision coal seam geographic information of fully mechanized working face is the key to realizing intelligent unmanned mining. However, the vertical precision of 3D model of coal seam constructed at this stage is low. The model cannot meet the actual needs of intelligent mining. In order to solve this problem, a dynamic modification method of 3D model of coal seam in fully mechanized working face is proposed. The static data of the initial coal seam 3D model and the dynamic data generated by the shearer cutting in the mining process are fused. The method is based on the prediction algorithms of long-short term memory (LSTM) network and its improved algorithm. The improved algorithms are based on the convolutional long-short term memory network (Conv LSTM) and encoder-decoder long-short term memory network (Encoder-Decoder LSTM). The coal seam floor curved surface and the coal seam thickness of the unmined area in the next stage are dynamically predicted according to the coal seam data of the previous mining stage. The parameters of the above three prediction algorithms are optimized by using the grid search method of double-layer loop nesting. The obtained high-precision vertical distribution data of the coal seam floor curved surface and the coal seam thickness of the unexploited area are taken as the coal seam 3D model correction value. The correction value is used to dynamically correct the coal seam 3D model of the unexploited area in the next stage. With the continuous mining of the working face, the newly obtained correction data is used to continuously and dynamically correct and update the initial coal seam 3D model, so as to improve the precision of the initial coal seam 3D model. Therefore, the dynamic modified coal seam 3D model can reflect the actual coal seam distribution of fully mechanized working face more accurately. Taking the coal seam 3D model of 18201 working face of a coal mine in Lvliang, Shanxi Province as an example, the proposed dynamic correction method is used to correct the coal seam 3D model. Within the range of 16-23.2 m in the advancing direction of the working face, the average error of the coal seam floor after the dynamic correction is 0.068 5 m. The average error of the coal seam roof is 0.076 m. Compared with the average floor error of 0.20 m and vertical average error of 0.40 m of the coal seam thickness before correction, the precision of the coal seam 3D model after dynamic correction is greatly improved. The results confirm the effectiveness of the correction method.

Research on large flow intelligent liquid supply system in fully mechanized working face

SI Ming, WU Bofan, WANG Ziqian

2022, 48(7): 66-72. doi: 10.13272/j.issn.1671-251x.2022030033

<Abstract>(212) <HTML> (29) <PDF>(37)

Abstract:
The liquid supply system in fully mechanized working face has the problems of insufficient liquid supply capacity, large pressure fluctuation and poor system operation stability. In order to solve the above problems, an immune particle swarm optimization fuzzy neural network PID (IPSO-FNN-PID) algorithm is proposed. The IPSO-FNN-PID controller is designed to stabilize the pressure of the liquid supply system. In the IPSO-FNN-PID algorithm, a particle swarm optimization (PSO) algorithm and an immune algorithm (IA) are introduced into a fuzzy neural network (FNN) PID controller. The immune particle swarm optimization (IPSO) algorithm is used to solve the problem that the FNN algorithm is easy to fall into local optimization. The IA is added to the PSO algorithm to improve the convergence of the PSO algorithm. Therefore, the output of the optimal PID parameters is realized. In order to verify the effectiveness of the IPSO-FNN-PID controller, traditional PID controller, Fuzzy-PID controller and FNN-PID controller are selected to compare. The simulation results show that the IPSO-FNN-PID controller has the best control effect on the emulsion pump. The rise time, peak time and regulation time of the other three controllers are longer than the IPSO-FNN-PID controller. The maximum overshoot is greater than the IPSO-FNN-PID controller. After adding the disturbance signal, the IPSO-FNN-PID controller has good adaptability and robustness, and it takes only 1.2 s to restore to a stable state. When traditional PID and Fuzzy-PID controllers are used to control the emulsion pump, the oscillation is obvious and the overshoot is large, which are 41.2% and 22.3% respectively. When the FNN-PID controller is used to control the emulsion pump, the oscillation is significantly weakened, the overshoot is reduced to 17.6%, and the adjustment time is reduced to 2.68 s. When the IPSO-FNN-PID controller is used to control the emulsion pump, there is almost no oscillation. The overshoot is only 5.22%, the adjustment time is shortened to 2.61 s. And the stability is stronger when encountering interference signals. When the disturbance signal is received, the load disturbance has little effect on the IPSO-FNN-PID controller, the convergence is rapid, and the robustness is greatly improved. The results show that the IPSO-FNN-PID controller has good anti-disturbance and disturbance compensation capability, and can meet the pressure stabilization control requirements of the liquid supply system.

Top coal migration time measurement system based on accelerometer

LI Zenglin, JIN Shukai, LIU Anqiang, ZHANG Quan, YUN Mingtao, KANG Junxuan, YANG Kehu

2022, 48(7): 73-80. doi: 10.13272/j.issn.1671-251x.2022060089

<Abstract>(124) <HTML> (19) <PDF>(22)

Abstract:
The multi-round sequential memory coal drawing technology can improve the recovery rate of top coal and gangue content in the fully mechanized working face. But it needs to accurately measure and control the time of each round of coal drawing in field application. In the practical application of the automatic coal drawing technology based on the top coal migration tracker, the top coal movement tracker is only used as a mark point and is arranged in the top coal. The top coal movement tracker can not obtain more top coal movement information. In view of the above problems, based on the top coal movement tracker, a top coal migration time measurement system based on accelerometer is designed. The system includes three parts: tag, collector and central computer. The label is placed inside the top coal, and moves along with the top coal in the coal drawing process. Through the built-in accelerometer, the specific force data is collected in real-time. The time measurement algorithm is called to realize the monitoring of top coal migration. Then the different coal drawing stages are determined. The top coal migration time information of different stages is calculated. When the tag is released from the coal chute, it collides with the scraper conveyor belt, and sends the top coal migration time information outward to the collector through the RF signal. The information is further transmitted to the central computer through the field bus to guide the fully mechanized working face to realize multi-round of sequential coal drawing on site. The hardware and software design of the time measurement label of top coal migration is introduced in detail. The functions of real-time acquisition of specific force value, wireless signal transmission and data storage are realized. A calibration platform with 3D turntable as the core and Gauss-Newton method as the calibration algorithm is built. The calibration of the accelerometer is completed. The calibrated accelerometer can accurately collect the specific force data of the top coal migration time measurement label. According to the migration characteristics of top coal in the process of coal drawing, the time measurement algorithm based on threshold and the time measurement algorithm based on long-term and short-term memory (LSTM) are proposed. The time measurement algorithm based on threshold realizes the time identification of motion stage by introducing static threshold and maximum threshold. The time measurement algorithm based on LSTM identifies the dynamic changes of the specific force vector sum in the time domain, finds the mutation point, and realizes the time identification of the motion stage. The performance test of the two time measurement algorithms is completed through the tag free falling experiment. The time measurement variance is 0.000 6 and 0.000 2 respectively. The time measurement error is 13.07% and 5.22% respectively. The results meet the on-site top coal migration time measurement requirements. And the time measurement algorithm based on LSTM has obvious application advantages in top coal migration time measurement.

Full pose measurement and virtual simulation of solid filling hydraulic support

WANG Yu, SHI Yannan, WANG Yiying, QI Penglei, WANG Hanqiu

2022, 48(7): 81-89. doi: 10.13272/j.issn.1671-251x.2022030078

<Abstract>(155) <HTML> (30) <PDF>(17)

Abstract:
The dynamic change of the solid filling hydraulic support's spatial pose state is difficult to directly identify under complex geological conditions. The existing pose measurement system has some missing pose parameters. In order to solve the above problems, a full pose measurement system of the solid filling hydraulic support is designed. The 3D model of the solid filling hydraulic support is established by using 3D Max modeling software. Based on different characteristic nodes of the solid filling hydraulic support, nine parameters reflecting the full spatial pose are obtained by using the multi-sensor fusion measurement method. The nine parameters include the inclination angle of the support base (included angle with the horizontal plane), the attitude angle of the top beam (included angle with the horizontal plane), the support height, the pushing distance, the status of the guard plate, the inclination angle of the pushing and compacting mechanism (included angle with the rear top beam), the pushing distance of the pushing and compacting mechanism, the distance between the guard plates of the support group, and the included angle between scraper conveyor central groove and support pushing gear. The inclination angle sensors are arranged at the front top beam, the rear top beam, the base, and the jack of pushing and compacting mechanism. They are used for measuring the inclination angle of the base of the support, the attitude angles of the front top beam and the rear top beam. The displacement sensors are arranged on the pushing gear and pushing and compacting mechanism of the support. The sensors are used for measuring the pushing distance. The vision sensors are used for collecting image data. The monocular vision measurement model is established. The converting of a global coordinate system into a local coordinate system is obtained. Therefore, the distance between the guard plates of the solid filling hydraulic support set, the angle between the support pushing gear and the center groove of the scrap conveyor, the state of the guard plates and the support height can be analyzed and calculated. The existing virtual simulation system of solid filling hydraulic support lacks in-depth research in data analysis, motion relationship constraints and other aspects. In order to solve these problems, a virtual simulation system of solid filling hydraulic support based on Unity3D is designed. The system realizes the motion simulation of the support by using Unity3D. The system reflects the change of the pose state of the running support in real time. The virtual simulation system of solid filling hydraulic support based on Unity3D is used together with the full pose measurement system of solid filling hydraulic support, which can truly reflect the running state of solid filling hydraulic support, and ensure the stability and the reliability of data of solid filling hydraulic support simulation. The systems can provide technical support for the smooth running of solid filling hydraulic support.

Staged multi-index comprehensive evaluation method for fire risk of coal working face

CHEN Xiaolin

2022, 48(7): 90-95, 104. doi: 10.13272/j.issn.1671-251x.2021120083

<Abstract>(141) <HTML> (12) <PDF>(20)

Abstract:
The mine fire risk evaluation method has problems of single evaluation dimension, incomplete evaluation index and unreliable evaluation result. In order to solve the above problems, based on the analytic hierarchy process, a staged multi-index comprehensive evaluation method for fire risk of coal working face is put forward. In order to analyze the coal working face internal fire, the method selects spontaneous combustion tendency, spontaneous combustion period, million-ton ignition rate, coal seam thickness, coal seam dip angle, geological structure, coal seam gas grade, coal mine process, goaf treatment method, upper and lower traveling wind pressure difference of the coal working face, the effectiveness of fire prevention and extinguish measures, self-heating period stage and Graham index as evaluation indexes. The method calculates the evaluation index score by adopting an interpolation method and gives weight to each evaluation index. Then the fire risk scores of the three stages including incubation period, self-heating period and combustion period are obtained. When the risk score of the incubation period of the internal fire in the coal working face is more than 50 points, the score is taken as the final score of the internal fire risk of the coal working face. Otherwise, it will enter the risk evaluation of the self-heating period. When the risk score of the self-heating period of the internal fire in the coal working face is greater than 50 points, this score will be taken as the final score of the internal fire risk of the coal working face. Otherwise, it will enter the risk evaluation of the combustion period. When entering the risk evaluation of combustion period, the internal fire risk score of the coal working face is directly set as zero. Aiming at the external fire risk of the coal working face, this study relies on the fire online monitoring, risk graded management and control and hidden danger investigation mechanism. The study takes the following factors as the evaluation indexes to score the external fire risk of the coal working face. The factors include temperature, oxygen volume fraction, carbon monoxide volume fraction, overdue hidden danger without receiving orders, overdue hidden danger without rectification, unqualified hidden danger review, overdue risk control measures without feedback, overdue risk control measures without review, unqualified risk control measures review. The lowest risk score of internal and external fire in the coal working face is taken as the fire risk score of the coal working face. The higher the score, the lower the fire risk of coal working face.

Analysis and optimization method of monitoring capability of coal mine microseismic monitoring network

CHEN Fabing, WU Hongjun, CUI Baoge, WANG Yuanjie, LI Yan

2022, 48(7): 96-104. doi: 10.13272/j.issn.1671-251x.2022020048

<Abstract>(141) <HTML> (16) <PDF>(22)

Abstract:
The monitoring capability of microseismic monitoring network depends on many factors, such as network layout, velocity model, seismic phase reading error, regional anomaly of travel time, positioning algorithm, equipment running state and environmental noise. Among these factors, the network layout can be artificially optimized at present stage. In order to effectively evaluate the monitoring capacity of microseismic monitoring network and optimize the network layout, the analysis and optimization method of monitoring capacity of coal mine microseismic monitoring network is proposed. This study analyzes four factors which have the greatest and most direct influence on the monitoring capability of the microseismic monitoring network. The four factors are the number of effective waveforms, the maximum gap angle, the near-station epicenter distance and the height difference between stations. It is pointed out that the number of effective waveforms, the near-station epicenter distance and the height difference between stations play a decisive role in the error of hypocenter depth solution. The number of effective waveforms and the maximum gap angle play a decisive role in the precision of epicenter positioning. According to the situation of the existing network and the working face, the distribution cloud pictures of the four factors are obtained. The monitoring capability of the microseismic network is evaluated item by item through the distribution cloud pictures of the four factors. The new network arrangement scheme is obtained through optimization of the evaluation result. The positioning error and sensitivity of the new scheme are analyzed. The epicenter positioning error, hypocenter positioning error and regional sensitivity of the whole mine are obtained. The second evaluation of the new scheme is carried out. If the secondary evaluation results meet the requirements, the new scheme can be regarded as the best network layout scheme. If the secondary evaluation results do not meet the requirements, the four factors sub item evaluation will be carried out again and the scheme will be optimized until the requirements are met. The field test results show that after the proposed method is used to optimize the microseismic monitoring network of 5307 working face in Tangkou Coal Mine, the average value of blasting hypocenter positioning error is reduced from 59.2 m to 37.2 m. The maximum value of positioning error is reduced to less than 100 m, and the blasting events with error less than 50 m account for 69.0% of the total. The results show that the proposed method can effectively improve the microseismic positioning precision and optimize the monitoring capability of the network.

Composite grouting reinforcement technology for deep roadway surrounding rock

FU Yukai, WANG Tao, SUN Zhiyong, YUE Yanpeng

2022, 48(7): 105-112. doi: 10.13272/j.issn.1671-251x.2022040063

<Abstract>(153) <HTML> (21) <PDF>(14)

Abstract:
The single grouting method and grouting material can not achieve an ideal grouting effect under the complex geological conditions of deep roadway surrounding rock. In order to solve this problem, a composite grouting reinforcement technology for deep roadway surrounding rock is proposed. Taking the 3210 isolated island working face of a mine in Shanxi Province as an example, this paper expounds on the principle and application of the composite grouting reinforcement technology. Firstly, combined with the geomechanical test results of the field test area and the physical and mechanical parameters of coal and rock mass, the range of each cracked zone of 3210 return air roadway is calculated. Secondly, based on the crack characteristics of surrounding rock zones, three-step grouting technology is proposed. The technology includes shallow low-pressure infiltration grouting, deep high-pressure cracking grouting and supplementary grouting. The depth of each borehole in the three-step grouting technology is determined according to the scope of each zone. Then, the corresponding grouting materials are selected according to the crack development degree and crack opening scale in each zone. The inorganic cement grouting materials should be used in high permeability zones. The ultra-fine cement grouting materials should be used in medium permeability zones. The polymer chemical grouting materials should be used for supplementary grouting in low permeability zones. Finally, according to the field grouting test, the grouting pressure parameters of different crack zones are determined. The grouting reinforcement effect of 3210 return air roadway is comprehensively judged by using three indexes. The three indexes include the anchoring force of grouting reinforcement rock mass, the uniaxial compressive strength of grouting reinforcement rock mass, and the integrity of surrounding rock mass. After adopting the composite grouting reinforcement technology, the anchoring force of the roadway side coal body is increased by 144%, reaching 230 kN. The uniaxial compressive strengths of the roof and roadway surrounding rock increase by 10.9% and 18.5% respectively, reaching 50.68 MPa and 23.37 MPa respectively. The wave velocity of the roadway side coal body increases by 15.2%, reaching 750 m/s. From the deformation rate and deformation amount of surrounding rock in grouted area and ungrouted area, the composite grouting reinforcement technology has achieved a good effect.

Coal mine roadway deformation measurement system based on line scanning principle

YANG Hongtao, YU Yin, XU Jichan, SHEN Mei, LU Guanghui

2022, 48(7): 113-117, 148. doi: 10.13272/j.issn.1671-251x.2022060012

<Abstract>(198) <HTML> (16) <PDF>(29)

Abstract:
When 3D laser scanning technology is used in measuring coal mine roadway deformation, there are problems of limited effective scanning distance, low density of acquired point cloud, serious lack of details, low measurement accuracy and low efficiency. In order to solve these problems, a coal mine roadway deformation measurement system based on line scanning principle is proposed. The system shoots a light strip image of a light plane projected by a line scanning laser on the roadway's surface through a measurement robot's measurement camera. The line structured light strip center extraction technology is used for light strip images to obtain the light strip center coordinates. The light strip center coordinates are substituted into the light plane equation fitted by the light plane calibration technology. The light strip image point cloud data of the roadway surface under the measurement camera coordinate system are solved. The rotary motor drives the line scanning laser and the measurement camera to rotate synchronously to obtain all the point cloud data of the roadway. The multiple groups of tracking cameras are used to capture the target image on the robot, so as to realize the continuous tracking and measurement of the robot's pose. Combined with the robot pose measurement results, all the point cloud data of the roadway are spliced to reconstruct the point cloud of the coal mine roadway. The point cloud slice is used to process the point cloud of the coal mine roadway to realize the rapid measurement of coal mine roadway deformation. The experimental results show that the measurement error of the system is less than 7 mm. The system has the characteristics of simple operation, high flexibility, fast measurement speed, wide measurement range and high measurement precision.

Steel wire rope defect magnetic flux leakage detection method based on improved complementary ensemble empirical mode decomposition

ZHONG Xiaoyong, CHEN Ke'an, ZHANG Xiaohong

2022, 48(7): 118-124. doi: 10.13272/j.issn.1671-251x.2022020037

<Abstract>(129) <HTML> (29) <PDF>(13)

Abstract:
The signal of small defects in steel wire rope is often submerged in wave noise. Therefore, it is difficult to detect small defects in wire rope and easy to miss detection. In order to solve this problem, a steel wire rope defect magnetic flux leakage detection method based on improved complementary ensemble empirical mode decomposition (ICEEMD) is proposed. To avoid the influence of the lubricant or dust on the surface of the wire rope on the detection signal, the electromagnetic detection method is adopted. CEEMD-WTF-WF multi-stage noise reduction method is obtained by combining ICEEMD, wavelet threshold filtering (WTF) and Wiener filtering (WF). The intrinsic mode function (IMF) component is obtained by decomposing the magnetic flux leakage signal of steel wire rope through ICEEMD. The energy ratio, permutation entropy and cross-correlation coefficient of IMF components are calculated. The IMF trend component and IMF stock noise component are extracted. WTF is conducted on the stock noise component to filter the useful IMF component reconstruction signal. WF is applied to the reconstructed signal to remove random noise. The eigenvalues of the de-noised defects are extracted, input and trained by BP neural network. The magnetic flux leakage signals of the steel wire rope defects are identified. The experimental results show that ICEEMD-WTF-WF multi-stage noise reduction method has good noise reduction effect on the magnetic flux leakage signal of steel wire rope. The SNR and kurtosis indexes are better than those of WTF, moving average filter and WF. The BP neural network model based on ICEEMD-WTF-WF takes a short time to detect. The average accuracy rate of small defects reaches 98.13%, which can better meet the requirements of wire rope defect detection.

Design of mine multi-band microstrip antenna

ZHANG Zhiwen, XU Yanhong, ZHOU Mengli, WANG Anyi

2022, 48(7): 125-129. doi: 10.13272/j.issn.1671-251x.2022040078

<Abstract>(223) <HTML> (57) <PDF>(19)

Abstract:
With the application of 5G technology in the coal mine, the signal interference between multiple systems becomes more and more intensive. This seriously affects the quality of data, voice and image communication. The coexistence of multiple systems in coal mine becomes increasingly prominent. To solve this problem, a multi-band microstrip antenna for mine is designed, which can work in WiMAX/WiFi/4G/5G NR band at the same time. Based on a planar monopole antenna, the antenna can work in multiple frequency bands in the mode of loading two L-shaped branches and loading an inverted L-shaped branch on the floor. The simulation results show that the antenna's middle, right and left branches produce 2.4, 3.5 GHz and 4.8 GHz resonance points respectively. The inverted L-shaped branch loaded on the floor provides 1.9 GHz resonance point. The antenna can work in three frequency bands, which are 1.88-2.73, 3.26-3.79 GHz and 4.7-5.9 GHz respectively. The antenna can effectively cover all the operating frequency bands of WiMAX/WiFi/4G/5G NR in coal mines. According to the antenna's peak gain and normalized pattern, the antenna has good gain performance and overall radiation performance in the required operating frequency band.

Prediction method of coal calorific value based on quantile regression

ZHAO Xianzhi, CHEN Junlin

2022, 48(7): 130-134. doi: 10.13272/j.issn.1671-251x.2022060023

<Abstract>(175) <HTML> (37) <PDF>(11)

Abstract:
At present, the traditional linear regression model is mainly used to predict the calorific value of coal. But it is difficult to express the complex relationship between independent variables and dependent variables. The model needs data to obey specific distribution assumptions. And the model is sensitive to abnormal values. In view of the above problems, a prediction method of coal calorific value based on quantile regression is proposed. The method selects the coal industry analysis indicators that are easy to measure, such as total moisture, ash and volatile matter. The method uses two quantile regression methods, linear quantile regression and quantile regression forest, to predict the calorific value of coal. The results are compared with that of the traditional linear regression method. The results show that the predicted value of calorific value of coal given by linear regression is only a conditional mean value. But the range of predicted value of calorific value of coal can be given by quantile regression. The prediction effect of quantile regression is better than linear regression and linear quantile regression. The importance of total moisture for the prediction of calorific value of coal is much greater than that of ash and volatile matter. Total moisture has great influence on the prediction of calorific value of low calorific value coal. But total moisture has little influence on the prediction of calorific value of high calorific value coal. Volatile matter and ash have little influence on the prediction of calorific value of low calorific value coal. But volatile matter and ash have a great influence on the prediction of calorific value of high calorific value coal.

Research on exothermic and kinetic characteristics of low-temperature oxidation of preoxidized coal

YAN Guofeng, HUANG Xingli, YAN Zhenguo

2022, 48(7): 135-141. doi: 10.13272/j.issn.1671-251x.2022030032

<Abstract>(255) <HTML> (37) <PDF>(14)

Abstract:
The existing research on the spontaneous combustion characteristics of oxidized coal is mostly based on the coal samples prepared under the conditions of lower oxidation temperature and air. It lacks the analysis of the kinetic characteristics during the oxidation process of oxidized coal. In order to solve the above problems, the C80 microcalorimeter is used to study the exothermic and kinetic characteristics of low-temperature oxidation reaction of preoxidized coal prepared under different oxidation temperatures (100, 200, 300 ℃) and oxygen volume fraction (21%, 15%, 5%). The effects of oxidation temperature and oxygen concentration on the activation energy of low-temperature oxidation reaction of preoxidized coal are discussed. The analysis results of low-temperature oxidation exothermic characteristics of preoxidized coal are shown as follows. ① The low-temperature oxidation process of preoxidized coal lags behind that of raw coal. The degree of lag increases with the increase of oxidation temperature and oxygen concentration. ② The heat release of low-temperature oxidation reaction of preoxidized coal is lower than that of raw coal. The heat release gradually decreases with the increase of oxidation temperature and oxygen concentration. When the oxidation temperature is 100 ℃, t₁ (the temperature at which the heat flow value starts ＞0), t₂ (the temperature corresponding to the maximum growth rate of heat flow value) and the reaction heat of low-temperature oxidation of preoxidized coals with different oxygen concentrations are basically equal. ③ With the increase of oxidation temperature, the effect of oxygen concentration on t₁, t₂ and the reaction heat of low-temperature oxidation is gradually obvious. The results show that the effect of oxygen concentration on the low-temperature oxidation reaction of preoxidized coal is only reflected at higher oxidation temperatures. However, too high oxidation temperature will lead to a serious lag of the low-temperature oxidation reaction process of pre-oxidized coal and the reaction heat release is less than 0. The analysis results of kinetic parameters (activation energy and pre-exponential factor) of low-temperature oxidation of pre-oxidized coal are shown as follows. ① The activation energy of the low-temperature oxidation reaction of pre-oxidized coal in the accelerated oxidation stage is higher than that of raw coal. The activation energy of the rapid oxidation stage is lower than that of raw coal. The results show that the threshold of the oxidation reaction of pre-oxidized coal entering the accelerated oxidation stage is increased, but it is easier to enter the rapid oxidation stage. ② The pre-exponential factor data show that the low-temperature oxidation reaction of pre-oxidized coal is more rapid than that of raw coal. ③ The changes of oxidation temperature and oxygen concentration have no obvious regularity with the activation energy of the low-temperature oxidation process of preoxidized coal. In the accelerated oxidation stage, the activation energy increases with the increase of oxidation temperature. The activation energy first decreases and then increases with the increase of oxygen concentration. In the rapid oxidation stage, when the oxidation temperature is 100 ℃, the activation energy first decreases and then increases with the increase of oxygen concentration, while 200 ℃ is the opposite.

Multi-feature fusion based encrypted malicious traffic detection method for coal mine network

HUO Yuehua, ZHAO Faqi, WU Wenhao

2022, 48(7): 142-148. doi: 10.13272/j.issn.1671-251x.17944

<Abstract>(199) <HTML> (29) <PDF>(16)

Abstract:
The coal mine network is faced with the threat of malicious traffic encrypted by the transport layer security protocol (TLS) generated by malicious software and the high false alarm rate of encrypted traffic during detection. In order to solve the above problems, a multi-feature fusion malicious traffic detection method for coal mine network TLS encryption is proposed. The characteristics of multiple and heterogeneous malicious traffic features of TLS encryption are analyzed. The connection features, metadata and TLS encrypted protocol handshake features of coal mine network TLS encrypted malicious traffic in the transmission process are extracted. A coal mine network TLS encrypted traffic characteristic set is constructed by using a flow fingerprint method. The features in the feature set are standardized, one-hot encoded and normalized, so as to obtain an efficient sample set. Five sub-models of decision tree (DT), K-nearest neighbor (KNN), Gaussian Naive Bayes (GNB), L2 logistic regression (LR) and stochastic gradient descent (SGD) classifiers were used to test the above feature sets. In order to improve the robustness of the detection model, combined with the principle of the voting method, five classifier sub-models are combined to construct a muti-model voting classifier (MVC) detection model. Five classifier sub-models are used as voters. Each classifier sub-model trains the sample set separately, and votes according to the principle of minority obeying majority to get the final prediction value of each sample. The experimental results show that the proposed feature set reduces the dimension of the sample set and improves the detection efficiency of TLS encrypted traffic. DT classifier and KNN classifier perform best on the data set, reaching more than 99% accuracy. But they have the risk of overfitting. Although the LR classifier and SGD classifier sub-models have also achieved recognition accuracy of more than 90%, the false positive rate of these two sub-models is too high. The GNB classifier sub-model performs the worst, with an accuracy of 82%. But it has the advantage of low false-positive rate. The accuracy and recall rate of that MVC detection model on a data set is more than 99%, the false alarm rate is 0.13%. The detection rate of encrypted malicious traffic is improved, and the false alarm rate of encrypted traffic detection is 0. And the comprehensive performance of the MVC detection model is better than that of other classifier sub-models.

Research on network security service chain technology of data center in coal mine enterprise

SUN Lei, SUN Shuxin, WANG Bowen, REN Hehe, PENG Hui

2022, 48(7): 149-154. doi: 10.13272/j.issn.1671-251x.17926

<Abstract>(157) <HTML> (26) <PDF>(19)

Abstract:
At present, most of the network security equipment between the production network and data center of coal mine enterprises are deployed in serial mode. This mode has the problems of single point of failure, link bottleneck, and operation and maintenance coupling. In order to solve the above problems, the network security service chain technology of data center in coal mine enterprise based on software defined network (SDN) is studied. The parallel deployment mode of the security equipment of the data center in coal mine enterprise is designed as follows. A service function chain (SFC) switch is connected in series on the physical topology. All security equipment is connected to the SFC switch. The SDN controller is used to control security equipment and flow through the SFC switch. The SFC switch regularly sends detection messages to the security equipment to detect the health status of the security equipment. According to the configuration, the SDN security service chain in the case of security equipment failure, upgrade or increase is realized. This chain ensures that the security equipment is not aware of online and offline. The test results show that the technology supports the visual and flexible scheduling of security service resources. The technology can enable/disable security services on service chains or configure service chains with different priorities according to needs. The technology can automatically update security service paths in the case of security equipment failure. The technology has low packet loss rate and realizes unaware switching.

2022 Vol. 48, No. 7

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