2022 Vol. 48, No. 4

Achievements of Scientific Research
Research on ultraviolet image perception method of mine electric spark and thermal power disaster
SUN Jiping, LI Xiaowei, XU Xu, ZHANG Sensen
2022, 48(4): 1-4, 95. doi: 10.13272/j.issn.1671-251x.17917
<Abstract>(258) <HTML> (96) <PDF>(45)
Abstract:
The electric leakage of underground cables and electrical equipment in coal mine, electromotive force discharge induced by high-power radio transmission on metal support and electromechanical equipment metal will generate electric spark, which will then lead to mine fire, gas and coal dust explosion. The early perception of mine electric spark and taking preventive measures can avoid or reduce mine fire, gas and coal dust explosion. The early perception of mine fire, gas and coal dust explosion and timely emergency rescue can reduce casualties and property losses. The ultraviolet image perception method of mine electric spark and thermal power disaster is proposed. The ultraviolet camera, pickup and air pressure sensor are set in coal working face, heading face and roadway to collect mine ultraviolet image, sound and air pressure in real time. The ultraviolet images are preprocessed. The interference of fluorescent lamps, incandescent lamps and LED lamps is eliminated. If there was an electric spark ultraviolet image, the electric spark alarm would be given. If there was a fire ultraviolet image, the fire alarm would be given. If the ultraviolet image was not an electric spark image nor a fire ultraviolet image, and if the pickup detected an explosion sound or the air pressure sensor detected a sudden increase in air pressure, the gas and coal dust explosion alarm would be given. The ultraviolet image is greatly interfered by incandescent lamps and fluorescent lamps, and is less interfered by LED lamps. With LED lamp replacing incandescent lamp and fluorescent lamp in coal mine, various lighting and signal equipment in coal mine have little interference to ultraviolet image in coal mine. Therefore, the ultraviolet image perception method of mine electric spark and thermal power disaster has the advantages of small external interference, high reliability and simultaneously perception of electric spark, external fire, gas and coal dust explosion disasters.
Intelligent coal mine data warehouse modeling method
WANG Lin, FANG Qian, ZHANG Xiaoxia, SU Shanghai, SHI Zhan, WANG Yakun
2022, 48(4): 5-13. doi: 10.13272/j.issn.1671-251x.2021120007
<Abstract>(610) <HTML> (198) <PDF>(107)
Abstract:
The coal mine massive data has problems such as 'data island', weak correlation, poor data quality due to lack of data management system. It is difficult to make full use of the data and provide analysis and decision-making support for coal mine intelligence. The data warehouse can meet the requirements of multi-source heterogeneous data integration in coal mine, and provide data basis for intelligent application in coal mine. By analyzing the coal mine data types, characteristics and intelligent application requirements of actual data, the intelligent coal mine data warehouse modeling method is studied. Firstly, the layered architecture of intelligent coal mine data warehouse is constructed, and the characteristics of data model of original data layer, detailed data layer, basic index layer, service data layer and public dimension layer are analyzed. Secondly, taking the data of fully mechanized working face as an example, the modeling process of data warehouse is expounded from the aspects of business data analysis, application demand analysis and layered architecture design. Thirdly, the construction method of data model in coal mine data warehouse is introduced. The original data is transformed into data warehouse dimensional model through dimension alignment, dimension association and dimensional index aggregation. The method solves the application problem of coal mine data association in different dimensions. Finally, in order to solve the problem of portability of coal mine data warehouse, the design idea of coal mine parametric data warehouse based on general data warehouse in coal mine industry + parametric ETL (extraction-transformation-load) method is proposed. The platform of coal mine data warehouse in the laboratory environment is set up to process the data of fully mechanized working face of Shanxi Tiandi Wangpo Coal Industry Co., Ltd. The auxiliary mechanism model analysis and visual management cockpit are realized based on the processing data, which verifies the practicability of intelligent coal mine data warehouse. The performance indexes of the original data model and the intelligent coal mine data warehouse are compared. The results show that the data organization, model reuse and iteration difficulty of the intelligent coal mine data warehouse are better than those of the original data model, and the data query response time is shortened by more than 50%.
Intelligent identification method for mine car load in coal mine auxiliary shaft
JIN Shukai, WEI Guannan, WANG Chunming, WANG Tonghai, WU Zhonglun, YANG Kehu
2022, 48(4): 14-19, 30. doi: 10.13272/j.issn.1671-251x.2021110055
<Abstract>(286) <HTML> (137) <PDF>(37)
Abstract:
The automatic classification of mine car load based on convolution neural network in coal mine auxiliary shaft is realized in practical application. The misdetection and false alarm are caused by simple trigger conditions. Non-mine car objects passing through the detection area can cause the misoperation of driver controlled switch. In order to solve this problem, an intelligent identification method for mine car load in coal mine auxiliary shaft based on target detection model is proposed. An industrial camera is installed at the wellhead of a coal mine auxiliary shaft to collect the images of mine car load and the images are manually labeled so as to construct a mine car identification data set. And the identification accuracy and the real-time performance of three target detection models, namely Faster R-CNN, YOLOv4 and SSD are evaluated. According to the evaluation results, it is concluded that the YOLOv4 model is more suitable for the identification task of mine car load. In order to reduce the model size and improve the identification speed, the YOLOv4 model is improved. The lightweight network MobileNet is used to replace the original backbone characteristic extraction network CSPDarknet53. So the MobileNetv3-YOLOv4 model is constructed. The test results show that the mean average precision(mAP) of the MobileNetv3-YOLOv4 model is 95.03%, and the identification speed is 44 frames/s, which is 0.77% and 27 frames/s higher than that of the YOLOv4 model respectively. In order to facilitate field application and deployment and improve the performance of the mine car load identification model on the embedded platform, a model acceleration method based on inter-layer fusion and model quantization is proposed. The MobileNetv3-YOLOv4 model before and after the acceleration is transplanted to Jetson TX2 for field test of mine car load identification. The results show that the identification speed is increased from 18.3 frames/s before the acceleration of the MobileNetv3-YOLOv4 model to 35.42 frames/s, and the mAP is 94.68%, which meets the real-time and precise detection requirements in the field. And the detection task is only started when the mine car passes the detection area, which avoids the misoperation of driver controlled switch caused by other objects.
Analysis Research
Track planning of coal gangue sorting robot for dynamic target stable grasping
MA Hongwei, SUN Naxin, ZHANG Ye, WANG Peng, CAO Xiangang, XIA Jing
2022, 48(4): 20-30. doi: 10.13272/j.issn.1671-251x.2021110050
<Abstract>(320) <HTML> (64) <PDF>(68)
Abstract:
When the robot is used to sort coal gangue, in order to solve the problems such as inaccurate positioning of gangue, failure of grasping by end of the manipulator and load impact caused by slippage and left-right swing of belt conveyor, a track planning method of coal gangue sorting robot for dynamic target stable grasping based on machine vision is proposed. Firstly, the target gangue is identified and the pose of the target gangue is obtained by using the HU moment invariants image matching algorithm. Secondly, the kinematic equations of the robot and the camera-robot are established respectively, and the forward and inverse solutions are carried out to realize the accurate positioning of the target gangue based on vision. Finally, the position-velocity-acceleration three-loop PID control algorithm is used to dynamically track the target gangue. The input of the position loop controller is the obtained precise position of the target gangue, the output of the position loop controller is used as the input of the velocity loop controller, the output of the velocity loop controller is used as the input of the acceleration loop controller, and the output of the acceleration loop controller is superimposed on the servo motor. Therefore, the end of the manipulator and the target gangue can achieve the effect of synchronous movement of position and velocity, so as to achieve stable and fast grasping. Matlab is used to compare the three-loop PID control algorithm, the three-dimensional proportional navigation algorithm and the three-dimensional biased proportional navigation algorithm. The results show that in the following, synchronous and intercepting cases of the tracking and grasping of dynamic targets, the response time and tracking and grasping time of the three-loop PID control algorithm are better than those of the proportional navigation algorithm and the biased proportional navigation algorithm. And the three-loop PID control algorithm is continuous and smooth in the speed and acceleration of each axis in the whole process without sudden change, which can realize synchronous tracking of dynamic targets and precise grasping. The three-loop PID control algorithm, proportional navigation algorithm and biased proportional navigation algorithm are applied to the coal gangue sorting system platform to carry out adaptability experiments. The results show that the three algorithms do not exceed the limit of each joint during robot operation. The average time of the three-loop PID control algorithm to complete the grasping is shorter than those of the proportional navigation algorithm and the biased proportional navigation algorithm. The average speed error of the three-loop PID control algorithm at the grasping point is about 1 mm/s, and the tracking speed error is small, which can meet the requirements of synchronous tracking and precise grasping of high-speed targets.
Key technologies of data warehouse for coal mine safety monitoring
LIU Haiqiang, CHEN Xiaojing, ZHANG Xinghua, CHEN Xiangfei
2022, 48(4): 31-37, 113. doi: 10.13272/j.issn.1671-251x.2022010053
<Abstract>(237) <HTML> (66) <PDF>(38)
Abstract:
Due to the adoption of operational data storage method, the coal mine safety monitoring system can't use massive data effectively and the data analysis capability is poor. In order to solve the above problems, this paper proposes the key technologies of data warehouse for coal mine safety monitoring. According to the business requirements of coal mine safety monitoring, the functional structure of coal mine safety monitoring data warehouse is proposed. Moreover, the five business subjects are designed, including overrun analysis, calibration analysis, abnormal data analysis, measuring point network interruption analysis and personnel management analysis. The logical model of coal mine safety monitoring data warehouse is established by using the fact constellation model. The fact table and dimension table are designed by subject. The physical model of data warehouse is established by using SQL Server. According to the characteristics of coal mine safety monitoring data warehouse, data extraction, conversion and loading strategies are proposed. The different data extraction rules are used to extract data by subject. The data from different sources are processed through format conversion, cleaning and sorting. In the process of data loading, pre-loading, loading and post-processing operations are carried out.
Automatic tracking method of reference waveform of mine ultrasonic gas flowmeter
BAI Sizhong
2022, 48(4): 38-43, 59. doi: 10.13272/j.issn.1671-251x.2021080082
<Abstract>(193) <HTML> (24) <PDF>(22)
Abstract:
The accuracy of mine ultrasonic gas flowmeter needs to be improved. The cross-correlation detection signal has 'signal hopping' phenomenon and affects the measurement precision of ultrasonic transit time. In order to solve the above problems, this paper proposes an automatic tracking method of reference waveform of mine ultrasonic gas flowmeter. While calculating the ultrasonic transit time, the cross-correlation operation is carried out between the ultrasonic reference waveform and the real-time received signal waveform. The reliability of the cross-correlation detection is calculated. The reliability effective threshold value and the reference waveform update threshold value are set. The reliability of the cross-correlation coefficient is evaluated so as to determine whether the reference waveform is updated. When the reliability is less than the effective threshold, it is determined that the received signal is invalid, and the ultrasonic signal is re-sent. When the reliability is greater than the update threshold, it is determined that the received signal waveform is highly consistent with the reference waveform. There is no need to update the reference waveform. When the reliability is between the effective threshold and the update threshold, it is determined that the received signal is valid. And the original reference waveform is replaced with the current received signal waveform to realize automatic tracking of the reference waveform. This paper analyzes the two kinds of waveform changes of ultrasonic received signal which may cause ultrasonic transit time error of one waveform period. The waveform changes are continuous envelope deformation and instantaneous envelope distortion. The change of gas flow rate, temperature and pressure will lead to the continuous change of received signal envelope. Spike pulses, random signals and periodic interference may cause instantaneous envelope distortion of the ultrasonic received signal. The instantaneous envelope distortion can be divided into three cases, severe distortion of the main peak, slight distortion of the main peak and non-main peak distortion. The experimental results show that under the influence of different flow velocity, temperature, pressure and noise, the relative error of ultrasonic gas flowmeter is less than ±1.0%. The results meet the measurement requirement of precision level 1.0. The automatic tracking method of reference waveform provides a guarantee for the accuracy and reliability of flow measurement.
Research on instability characteristics and control technology of the mining roadway below the remaining coal pillars in the goaf
CAO Jinzhong, GAO Le, YAN Pengfei, LI Meng, CHEN Lei, YANG Huakang
2022, 48(4): 44-52. doi: 10.13272/j.issn.1671-251x.2021110032
<Abstract>(207) <HTML> (83) <PDF>(25)
Abstract:
When the extra thick coal seam is mined in the goaf, the remaining coal pillar of upper coal seam and adjacent working face will have an important impact on the stability of mining roadway. At present, the research on deformation and failure mechanism and control of mining roadway does not consider the complex environment of gob-side roadway in extra thick coal seam under the condition of short distance coal pillar mining. In order to solve the problem, taking the 30503 repaired roadway in Tashan Coal Mine as the engineering background, the deformation and failure mechanism of the roadway is analyzed by using the methods of field monitoring, theoretical analysis and numerical simulation. And the corresponding surrounding rock support technology is proposed. A roof separator is arranged on the roof of 30503 repaired roadway to monitor and record the rock displacement at each position of the roof in real time. The monitoring results show that the surrounding rock in the roof of 30503 repaired roadway has been broken due to the impact of adjacent working face and the short distance to the overlying remaining coal pillar. After the roadway excavation, the roof deformation speed is fast, the seperation volume increases continuously and the impact range is wide. According to the monitoring results, the impact of the remaining coal pillar on the deformation and failure of the roadway and the impact of the fracture position of the basic roof on the deformation and failure of the roadway are analyzed. The results show the following points. ① The unreasonable arrangement of the roadway is an important reason for the damage of the repaired roadway. At the same time, in order to avoid the impact of the remaining coal pillar, the roadway is arranged at a distance of more than 35 m from the center of the coal pillar (25 m from the edge of the coal pillar). ② The excavation position of repaired roadway is seriously affected by the remaining coal pillar, and the roadway is in the high stress concentration area before excavation. When the adjacent 30501 working face is mined, the basic roof breaking position is located above the roof of the repaired roadway, which is the direct cause of the broken roof of the roadway. According to the above analysis results, the numerical simulation analysis is carried out on the evolution law of deviatoric stress distribution of coal pillars with different widths, and the targeted technical scheme of surrounding rock stability control is proposed. ① On the premise of ensuring sufficient safety of the coal pillar and avoiding waste of resources, the width of the coal pillar in the 30503 repaired roadway section is set to 8 m. ② When excavating the gob-side roadway in the short distance extra thick coal seam, hydraulic fracturing measures are adopted to reduce the impact of the overlying coal pillars on the coal seam. ③ The support scheme of bolt-mesh-anchor+guniting+single pillar is selected to support the newly excavated roadway. In order to verify the application effect of the surrounding rock stability control technology, the cross observation method is used to continuously monitor the roadway deformation during the excavation of the new repaired roadway in 30503 working face. The results show that the deformation of the two sides is 90 mm, the deformation of the roof and floor is 331 mm, and the deformation of the surrounding rock is effectively controlled.
Quantitative study on grouting plugging effect of loaded fractured coal sample based on CT scanning
LI Yan, LI Bing, YAO Shuai, YAO Banghua
2022, 48(4): 53-59. doi: 10.13272/j.issn.1671-251x.17862
<Abstract>(133) <HTML> (29) <PDF>(25)
Abstract:
The existing research on the fracture structure and grouting effect of grouting coal and rock mass cannot be quantitatively characterized. In order to solve the problem, the self-built grouting test system for loaded coal and rock mass is used to carry out the grouting test of different loaded fractured coal samples(uniaxial and splitting). The CT scanning of the fractured coal sample before and after grouting are carried out by using industrial CT scanning equipment. The image analysis software VG Studio MAX is used to accurately extract the fractures of the digital coal sample obtained from CT scanning data reconstruction model. The digital quantitative analysis of the three-dimensional fracture morphology and structure of the loaded fractured coal samples before and after grouting is carried out. ① The results show that the main fracture of the fractured coal sample under uniaxial loading penetrates from both sides of the top of the coal sample to the bottom of the coal sample and converges. The fracture width is basically unchanged. The coal sample is mainly fractured under the action of shear stress. The overall degree of fragmentation is large. The main fracture network is accompanied by more small fractures. The number of fracture above 50 mm is changed from 1 before grouting to 0 after grouting. The total fracture volume is reduced from 12 000 mm3 to 5 700 mm3 by 52.5%. It shows that the fracture structure of fractured coal sample under uniaxial loading is not conducive to slurry diffusion flow. The main fracture of splitting failure coal sample extends downward from the top to the middle and lower part of the coal sample along the vertical direction. The fracture width is large. And then the fracture tilts 45° to one side and continues to extend. The fracture width gradually narrows. The number of fractures above 50 mm is changed from 2 before grouting to 0 after grouting. The total fracture volume is reduced from 3 430 mm3 to 312 mm3 by 90.9%. It shows that the fracture structure of splitting failure coal sample is conducive to the flow and filling of slurry. ② The permeability of fractured coal sample under uniaxial loading is decreased from 57×10−14 m2 before grouting to 1.2×10−14 m2 after grouting by 97.9%. The permeability of splitting failure coal sample is decreased from 75×10−14 m2 before grouting to 1.3×10−14 m2 after grouting by 98.3%. It shows that grouting has a significant effect of plugging leakage and reducing seepage on coal sample with different failure forms. ③ The change of fracture volume and permeability of two kinds of coal samples before and after grouting are compared. It shows that although the grouting slurry of fractured coal sample under uniaxial loading only fills part of the fracture, the permeability difference is very small compared with the original coal sample. This result indicates that by blocking the connectivity of the air leakage channel, the fractures can be effectively blocked and a good grouting hole sealing effect is achieved. The research results can provide useful references for quantitative analysis of grouting in fractured coal and evaluation of grouting plugging effect in coal seam.
Impact of water accumulation in abandoned mines on adjacent production mines
HAO Hongjun, ZHAI Xiaorong, HU Ru, PANG Yao, HUANG Kai, WU Jiwen
2022, 48(4): 60-65. doi: 10.13272/j.issn.1671-251x.2021110008
<Abstract>(128) <HTML> (20) <PDF>(15)
Abstract:
The goaf water accumulation of abandoned mine will damage the strength of boundary coal pillar, cause coal pillar failure, and pose a threat to the safety of adjacent production mine. The research on the safety limit of goaf water level after mining damage of coal pillar at mine boundary is not comprehensive. In order to solve the problem, taking East Shaft of Shuoshi Mining Industry of Huaibei Mining Group(Shuoshi East Shaft) and Huaibei Shuanglong Mining Co., Ltd.(Shuanglong Company) as the research objects, this paper analyzes the impact of goaf water in abandoned mine of Shuoshi East Shaft on Shuanglong Company, and puts forward corresponding water disaster prevention measures. The mining damage of coal pillar at mine boundary is studied by theoretical calculation and numerical simulation, and the safety limit of goaf water level is calculated according to the damage results. Based on the Bernoulli equation and the Darcy-Weisbach pipeline flow theory, the drainage capacity of the existing drainage boreholes is calculated and the safety is evaluated. The research results show that under the impact of mining, the damaged width of coal pillar at the mine boundary is about 19 m, the effective width is only 21 m, and the maximum water level difference that can be borne is 33 m. When the water level in the abandoned mine of Shuoshi East Shaft rises to −398 m, the coal pillar may be unstable. The drainage capacity of the existing drainage boreholes in the mine is about 89 m3/h, which is less than the actual abandoned mine water inflow of 160 m3/h. After reaching the limit water level, the goaf water level may continue to rise, and there is a threat of water disaster. The water disaster prevention and control measures such as enlarging the borehole diameter and adding drainage boreholes are proposed. The research results can provide reference for the water disaster prevention and control of abandoned mine under similar conditions.
Experimental Research
Personnel detection in dangerous area of coal preparation plant based on CenterNet-GhostNet
ZHANG Yixiang, LIN Song, LI Xue
2022, 48(4): 66-71. doi: 10.13272/j.issn.1671-251x.2021080058
<Abstract>(227) <HTML> (87) <PDF>(53)
Abstract:
Due to the dust and fog interference, it is difficult to distinguish accurately the whole body target of personnel in dangerous areas of coal preparation plant from the production environment background. Moreover, the head features of personnel are relatively easy to be identified, and the possibility of head being blocked in the monitoring perspective is low. Therefore, the head detection of personnel in dangerous areas is used instead of the whole body target detection of personnel. At present, the lightweight target detection model based on deep learning has a lot of information loss in feature extraction, and its detection capability of human head target is limited. In order to solve this problem, a lightweight personnel detection model CenterNet-GhostNet is proposed. The model takes CenterNet network as the basic framework, and combines the lightweight network GhostNet and the feature pyramid network(FPN) as the feature extraction network. GhostNet extracts the features of the input image and improves the network feature expression capability. And the FPN fuses the information contained in the feature maps with different resolutions extracted by GhostNet, so that more detailed information is reserved while extracting the high-level semantic features. Three independent convolution operation branches are used to decode and calculate the single output feature map with higher resolution, so as to make full use of the detailed information contained in the feature map. The experimental results show that the detection precision of CenterNet-GhostNet model is 93.7% and 91.7% respectively for the two types of head targets with and without helmet, which are better than the general lightweight models SSD-MobileNet, YOLOv4 Tiny and CenterNet-Res18. The single frame detection time of CenterNet-GhostNet model deployed on NVIDIA Jetson Nano is 67 ms, which meets the requirements of high-precision and real-time detection of personnel in dangerous areas of coal preparation plant.
A dual-motor drive system for scraper conveyor
JING Wanli, JIA Lixin, LI Mengyi, MA Yuxin, SUN Wenyao
2022, 48(4): 72-77. doi: 10.13272/j.issn.1671-251x.2021120097
<Abstract>(217) <HTML> (31) <PDF>(38)
Abstract:
Current scraper conveyors with permanent magnet synchronous motors often improve their efficiency by updating the mechanical structure of their drive systems, few efforts are made to optimize the control of permanent magnet synchronous motors. This paper fills the gap by involving maximum torque per ampere (MTPA) and flux-weakening controls to improve the dual-motor drive system of scraper conveyors. Given the direct-axis current, the proposed system reduces the motor loss by adopting MTPA control to obtain the maximum torque per ampere. By using flux-weakening control to increase the speed regulation range of scraper conveyors, the coal output of a scraper conveyor can be relatively stable under various production loads. To balance the power of two motors, the proposed system applies the master-slave control that takes the rear motor as the master and the front motor as the slave, and gives the master's torque setpoint to the slave's MTPA and flux-weakening control systems. The effectiveness of the proposed system is evaluated by using AMEsim and Matlab/Simulink to simulate the scraper conveyor and its dual-motor drive system, respectively. The results show that the stator current under MTPA can be stable at 130.1 A when the motor load suddenly raised, while the stator current under traditional vector control is stable at 149.2 A. MTPA control outperforms the vector control, as the smaller stator current implies the better system when the same output torque maintained. Flux-weakening control extends the speed regulation range from 0-750 r/min to 0-850 r/min. Master-slave control maintains the same output torques of the master and the slave, leading to the balanced dual-motor power.
Intelligent fault diagnosis of rolling bearings based on deep network
LI Jincai, FU Wenlong, WANG Renming, CHEN Xing, MENG Jiaxin
2022, 48(4): 78-88. doi: 10.13272/j.issn.1671-251x.2022010008
<Abstract>(437) <HTML> (120) <PDF>(42)
Abstract:
In order to solve the problem that the data distribution of the source domain and the target domain of rolling bearing is different in the variable working condition environment and the samples of the target domain do not contain labels, a fault diagnosis model of the rolling bearing based on the deep adaptive transfer learning network (DATLN) is proposed. Firstly, a domain-shared characteristic extraction network is built, and multiscale convolutional neural network (MSCNN) is used to suppress noise interference, so as to effectively extract local fault information contained in vibration signals. Secondly, combined with a bi-directional long short-term memory network (BiLSTM), the temporal characteristics in the local fault information are further learned. Finally, transfer learning is introduced to build a domain adaptive module with domain adversarial (DA) training combined with adaptive joint distribution (AJD) metrics. By maximizing the domain classification loss and minimizing the AJD distance, the source and target domain characteristic samples are aligned. The anti-noise experiment and transfer experiment are carried out on the open source CWRU data set and the measured data set of the mechanical fault platform respectively. The anti-noise experiments show the following points. ① The identification accuracy of MSCNN-BiLSTM network is above 99% in the noise-free environment, which shows that MSCNN-BiLSTM network has a good characteristic extraction capability. ② The identification accuracy of MSCNN-BiLSTM, LeNet-5, MSCNN and BiLSTM decreases with the increase of noise intensity. ③ Under the noise environment of 3, 5 and 10 dB, the average identification accuracy of MSCNN-BiLSTM network is higher than that of LeNet-5, MSCNN and BiLSTM networks, indicating that MSCNN-BiLSTM network has better anti-noise interference performance. ④ The MSCNN-BiLSTM network converges first with less fluctuation in both the noise-free environment and the 3 dB noise environment. The transfer experiments show the following points. ① The average identification accuracy of DA+AJD method is 97.36% on unlabeled target domain dataset, which is higher than that of Baseline, transfer component analysis(TCA) and domain adversarial neural network (DANN). ② On the test set confusion matrix, only one sample of the DA+AJD method is incorrectly identified, indicating that the DA+AJD method based on domain adaptation has better fault transfer diagnosis performance. ③ The t-SNE algorithm is used to visualize the processed source and target domain characteristic samples. The DA+AJD method only has a small number of rolling element fault and outer ring fault characteristic samples in the target domain that are incorrectly aligned to the inner ring fault characteristic samples area in the source domain. This result indicates that the DA+AJD method can effectively reduce the edge distribution and conditional distribution differences between the source domain and the target domain, and thus achieves better characteristic sample alignment.
Two-dimensional dynamic matching algorithm for mobile edge computing in intelligent mine
ZHAO Duan, SHEN Chengyang, SHI Xinguo, LIU Ke
2022, 48(4): 89-95. doi: 10.13272/j.issn.1671-251x.17782
<Abstract>(145) <HTML> (24) <PDF>(19)
Abstract:
In the application of mobile edge computing(MEC) in intelligent mine, the mobile users unload tasks to non-optimal edge servers due to unreasonable resource allocation, which leads to extra transmission time and execution delay, thus resulting in the decrease of the total task completion rate. In order to solve the above problem, a two-dimensional dynamic matching algorithm based on preference is proposed to optimize the resource allocation decision in MEC system. The data of the position of a mobile user in MEC system and the calculation amount required by a task in one time slot is sent to the edge server. The preference table of the edge server for the mobile user is formed according to the set preference value. At the same time, the preference table for all the edge servers is formed by the mobile user according to different physical distances. The two preference tables are combined to form a two-dimensional dynamic preference table, which is abstracted into a two-dimensional matrix. The two-dimensional matrix is processed by a two-dimensional dynamic matching algorithm based on preference, and the matching optimization results of mobile users and edge servers are obtained. The simulation results show that compared with the conventional MEC scene unloading algorithm, the preference-based two-dimensional dynamic matching algorithm can effectively alleviate the problem of the decrease of the total task completion rate in a large number of sudden task scenes, and can achieve the total task completion rate of more than 60% in extreme cases.
Study on failure characteristics of coal sample under different unloading stress paths
YU Fei, ZHANG Tong, LIU Wenjie, TAN Hui, YANG Xin, YU Xiang
2022, 48(4): 96-104. doi: 10.13272/j.issn.1671-251x.2021090081
<Abstract>(175) <HTML> (68) <PDF>(26)
Abstract:
The existing research on the failure characteristics of coal samples has some problems, such as single mechanical parameter test and large limitation of stress loading direction. The numerical simulation effect has deviation in the inversion of real geological conditions, and the determination of coal and rock dynamic disaster and bursting liability is based on the macro-research of field experiments. There are few studies on the failure mechanism of coal samples under different unloading stress paths in true triaxial. In order to solve the above problems, taking the engineering geology of Hujiahe Coal Mine in Binchang, Shaanxi Province as the research background, the true triaxial test of coal samples under three different unloading stress paths is designed by using the triaxial dynamic and static load test system of high-frequency vibration acquisition and borehole imaging. And the failure characteristics, peak strength characteristics, acoustic emission response characteristics and fractal law of coal samples are studied. ① The results show that the failure modes of coal samples under three different unloading stress paths are tensile-shear composite failure, and the initiation failure of macro-cracks mostly occurs in the coal samples with relatively low strength. The axial stress of each coal sample increases continuously, and each horizontal stress provides tensile stress in the process of gradually decreasing, resulting in significantly different surface failure forms of coal samples under different unloading stress paths. ② There are obvious differences in the stress of the three different unloading stress paths at the peak failure stage, and the standard deviation reaches 4.35 MPa, accounting for 29.25% of the average peak strength. When the stress load exceeds the average peak strength of the three stress paths by 14.87 MPa, the coal samples are damaged. ③ Under the action of high static load, the pores of the coal samples are compacted after initial loading. The internal structure is relatively uniform, and no fracture expands. The damage variable value is 0 in the initial stage. In the stable development stage of damage, the internal pores of the coal samples reach the limit state and break to form micro-fracture, and the damage variable value is 0.04-0.17. During the loading process, the micro-fracture develop rapidly, expand and converge into the fracture network, and the coal sample is macroscopically damaged. The bearing capacity of the coal sample decreases rapidly, the damage variable value increases sharply first and then stabilizes, and the maximum damage variable value reaches 1.0 in the stage of accelerated damage development. The acoustic emission(AE) energy value increases suddenly when the coal sample is damaged by stress instability and tensile-shear failure. When the AE energy intersects with the damage variable curve, the coal sample begins to break, and the AE energy has a good coupling with the coal sample failure. ④ Under different unloading stress paths, the larger the fractal dimension of coal sample, the higher the degree of fragmentation.
A temperature prediction model for coal spontaneous combustion based on PSO-SRU deep artificial neural networks
JIA Pengtao, LIN Kaiyi, GUO Fengjing
2022, 48(4): 105-113. doi: 10.13272/j.issn.1671-251x.2021090047
<Abstract>(160) <HTML> (41) <PDF>(26)
Abstract:
Traditional temperature prediction models for coal spontaneous combustion typically have low generality and robustness. This paper improves them by proposing a coal spontaneous combustion temperature prediction model based on particle swarm optimization and simple recurrent unit(PSO-SRU). It firstly pre-processes the gas concentration data collected from temperature programmed oxidation tests, selects the concentration data of O2, CO, CO2, CH4, C2H4 that highly relate to the coal temperature as the prediction indicators, and further separates the indicators into training and testing data sets. Then, a SRU based prediction model over the training data set is trained to learn the nonlinear relationship between the coal spontaneous combustion temperature and the indicators. Mean absolute error(MAE) forms the fitness function and PSO algorithms are involved to optimize the SRU prediction model's parameters. Finally, the PSO-SRU model with optimized parameters are applied over the testing data set to predict the coal spontaneous combustion temperature. Experiments show the PSO-SRU model can improve the prediction accuracy, as the model's MAE and root mean square error(RMSE), comparing with those generated by support vector regression(SVR), random forest(RF), and back propagation(BP), decreases by 12.58, 7.65, 5.91 ℃, and 22.65, 17.45, 8.94 ℃ respectively. The PSO-SRU model also demonstrates a good generality and robustness, as the difference of determination coefficient (R2) of the model over the training and testing data sets is only 0.03.
Real-time calculation method of mine ventilation network based on ultrasonic full-section wind measurement
SONG Tao, WANG Jianwen, WU Fengliang, ZHANG Guoqun, CHEN Fei, FENG Xiong, LI Longqing
2022, 48(4): 114-120, 141. doi: 10.13272/j.issn.1671-251x.2021090073
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Abstract:
The wind flow in underground coal mine is changing all the time. The coal mine ventilation network solution is a static calculation method, which can not solve the dynamic wind flow in real time, and requires wind speed sensor to obtain the dynamic wind flow data. However, the current wind speed sensor has poor stability and incomplete coverage. In order to solve the above problems, a real-time calculation method of mine ventilation network based on ultrasonic full-section wind measurement is proposed. The time difference between downwind and upwind of ultrasonic propagation between two points is used to measure the wind speed of the whole section of the roadway. The wind speed measurement result is independent of the sound speed and is not affected by the parameters such as the sound speed, temperature and humidity and air pressure. The problem that the air duct of the traditional wind speed sensor is easily blocked by mine dust is avoided. The resolution of the wind measuring device reaches 0.03 m /s. By continuously collecting the real-time working conditions of air volume and air pressure of main fans and the real-time air volume of some shafts and roadways, the ventilation network is calculated. And the fixed air volume method is used to integrate the monitored air volume into the ventilation network, and the real-time air volume of the whole ventilation network can be obtained through calculation. The Lagrangian multiplier method is used to correct and calculate the air volume and wind resistance in real time, so as to solve the problems of unbalanced air volume of nodes caused by redundant air volume monitoring branches and unbalanced air pressure of loop caused by fluctuation of the wind resistance. It is verified by an example that the calculation results of the real-time calculation method are highly consistent with the monitoring values. At the same time, the results strictly follow the constraints of the loop air pressure balance and the node flow balance. The real-time calculation of the ventilation network with 1 319 branches and 945 nodes in Ningtiaota Coal Mine is carried out. The time for one calculation is only 0.9 s, the number of iteration convergence is about 105, and the calculation results are continuously updated with time. The results verify the feasibility of the real-time calculation method.
Rock burst prevention technology in multi-roadway intersection area of hard roof strong impact working face
MA Hongyuan, PAN Junfeng, XI Guojun, JIAO Biao, LIU Shaohong, WU Jianhong
2022, 48(4): 121-127. doi: 10.13272/j.issn.1671-251x.2021120039
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Abstract:
In order to ensure the safety of multi-roadway crossing area in the mining process of strong impact working face under hard roof, the end mining of 401111 working face of Shaanxi Binchang Hujiahe Mining Co., Ltd. is taken as the engineering background. The method of theoretical analysis and field monitoring is used to classify the rock burst hazard area of the working face during the end mining period. Moreover, the dynamic and static load influencing factors that lead to the increase of rock burst hazard are analyzed. The dynamic and static load monitoring situation during normal mining and the end mining are compared. The results show that the 401111 working face mining coal seam has strong rock burst tendency. Under the condition of hard roof, the static load is provided by the working face goaf, adjacent goaf and multi-roadway intersection area. The dynamic load is provided by the instantaneous release of elastic energy in the overlying hard roof overhanging and collapsed and multi-roadway intersection areas in the goaf. The joint action of dynamic and static loads leads to an increase in the rock burst hazard of the 401111 working face at the end of mining. And the rock burst hazard in the intersection area of the return air roadway is higher than that of the transport roadway side. The idea of separate source prevention and control of rock burst is adopted. For the overlying hard roof, the roof pre-split blasting technology is used to shorten the roof collapse step. And the dynamic load disturbance caused by the large-area overhang and collapse of the roof is reduced. For the roadway side and floor, large-diameter drilling is used to relieve pressure so as to reduce the accumulation of static load and the degree of load on the surrounding rock. At the same time, the roof of the roadway is supported by bolt+steel belt mesh and anchor cable. The side of the roadway is supported by anchor cable+steel ladder mesh so as to improve the rock burst resistance of surrounding rock. After using the rock burst prevention technology based on pressure relief and joint support, the micro-seismic events are greatly reduced. The result indicates that the coal and rock mass fracture degree is low and the integrity is good, and the safe mining of the working face is ensured.
Experience Exchange
Prediction of water inrush source of coal seam floor based on Fisher discriminant model
DUAN Lihong, DAI Lei, ZHANG Jinling
2022, 48(4): 128-134. doi: 10.13272/j.issn.1671-251x.2021110019
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Abstract:
In order to solve the problems of low accuracy mine water inrush source discriminant method for mine floor water inrush source discrimination, taking the second level coal seam of suburban coal mine as an example, the Fisher mine floor water inrush source discriminant model is established. The aquifers with the threat of water inrush in the second level coal seam of suburban coal mine are the coal-measure sandstone aquifer and the karst fractured aquifer of the Taiyuan Formation in the floor. Considering the importance of hydrochemical ions and the validity of the data, three kinds of water quality analysis data of sandstone water, limestone water and mixed water with water inrush threat in the coal seam floor are used as samples. The content and mineralization of six kinds of ions, Ca2+, Mg2+, Na++K+, HCO3, Cl and SO42−, are selected as the discriminant analysis variables for the identification of mine inrush water sources. Two typical Fisher discriminant functions (the first and the second discriminant functions) are obtained by SPSS software. The central values of the typical discriminant functions in the three water quality groups are calculated. By comparing the distance between the function values of the water samples to be discriminated and the central values of the three water quality groups, it is able to determine which group the samples belong to. The back substitution estimation method is used to test the Fisher mine floor water inrush source discriminant model. The results show that the discriminant accuracy rate of the model is 93.3%, and the discriminant results are highly reliable. The model is used to classify 10 known water samples in the second level of suburban coal mine. The results show that the discriminant effect of 10 water samples is consistent with the actual situation, and the discriminant accuracy rate is 100%.
Three-dimensional coal seam modeling of fully mechanized working face based on transparent geology
XUE Guohua
2022, 48(4): 135-141. doi: 10.13272/j.issn.1671-251x.2021090079
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Abstract:
The three-dimensional coal seam modeling method based on transparent geology is an effective way to indirectly solve the problem of coal rock identification. Most of the existing three-dimensional coal seam modeling methods focus on the expression of spatial three-dimensional entities. There is a lack of research on the dynamic change of coal seam roof and floor in the mining process. And the prediction precision of coal seam roof and floor elevation under complex geological conditions is not high, which is difficult to meet the actual needs of coal mining. In order to solve the above problems, this paper proposes a three-dimensional coal seam modeling method of fully mechanized working face based on transparent geology. Based on the geological data of air inlet and return roadway, borehole measurement data, open-off cut data of working face and the coal seam geological data obtained by using three-dimensional seismic re-interpretation technology, in-seam seismic exploration technology and wireless electromagnetic wave perspective technology, the discrete smooth interpolation (DSI) algorithm is applied to predict the elevation of coal seam roof and floor. And the static three-dimensional coal seam model of fully mechanized working face is constructed. In order to improve the precision of the static three-dimensional coal seam model of the working face, the geological information newly revealed by open-off cut and DSI algorithm are used to dynamically update the model to obtain a more accurate dynamic three-dimensional coal seam model of the working face. Based on the updated three-dimensional coal seam model, the cutting curve of the shearer is dynamically planned to guide the shearer to automatically adjust height so as to achieve adaptive coal cutting. The method is applied to 810  fully mechanized working face of Huangling No.1 Coal Mine, the results show that the DSI algorithm is better than Kriging interpolation algorithm and spline function interpolation algorithm in the prediction of coal seam roof and floor elevation. The mean absolute error of interpolation is 0.015 5 m. The three-dimensional coal seam model is updated once every 5 m of cutting, and the elevation prediction error of coal seam roof and floor is ≤ 6.3 cm, which meets the requirements for precise planning of the cutting track of the shearer.
A system design for coal mine fire-fighting robots
CHEN Cheng, CHEN Xiutian, ZHU Mingliang
2022, 48(4): 142-146. doi: 10.13272/j.issn.1671-251x.2021090019
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Abstract:
Although fire-fighting robots are important devices for underground coal mines to prevent and deal with fire incidents, current research has hardly studied the approaches of robot locating, path planning, and accurate fire detection and extinguishment for complex underground coal mine topography. To fill the gap, this paper proposes a system design for underground coal mine fire-fighting robots. By combining the technologies of ultra wide band (UWB) and laser radars, the design applies the iterative closest point (ICP) and the adaptive Monte Carlo localization (AMCL) algorithms to initialize robots' position and locate robots in a real time manner, respectively. By using inertial measurement units and odometers, the design can raise the real localization accuracy up to 5-10 centimeters. By adding a distance parameter to limit the searching area, an enhanced A* algorithm is proposed to plan paths for robots. Experiments show that the algorithm can find the suitable paths in lower time cost. The design supports a robot to detect targets using a template mapping system based on a pre-generated feature image set. It limits the false positive rate to 10% (true positive rate of 90%) and completely meets the design requirement. The design allows a robot to be equipped with a cascade controller that uses feedbacks of velocity and position to control the elevation and yaw angels of the pan-tilt-zoom (PTZ). Fire extinguishing bombs can be further thrown to targets, via the PTZ, to support accurate fire extinguishment.