2021 Vol. 47, No. 4

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Mine external fire sensing method
SUN Jiping, CUI Jiawei
2021, 47(4): 1-5. doi: 10.13272/j.issn.1671-251x.17760
<Abstract>(116) <HTML> (16) <PDF>(10)
Abstract:
In order to solve the problem that visible light images are greatly interfered by mine lights, car lights, roadway lights, dust and red object in mines, the mine external fire sensing method based on near-infrared and visible light images is proposed. The near-infrared images and visible light images are fused to bring into play the advantages of obvious early flame characteristics in near-infrared images and obvious mid-term flame characteristics in visible light images so as to improve the recognition rate of mine external fire. This paper proposes a mine external fire sensing method based on multiple information fusion of near-infrared image, visible light image, temperature sensor, gas sensor and smoke sensor. The method fuses near-infrared image, visible image and sensor information. The sensor does not need no blind area coverage. Only a certain number of gas sensors, temperature sensors and smoke sensors need to be set up, which has the advantages of being timely, reliable and low-cost.The fire alarms are divided into four categories, including the image, temperature, smoke and gas fire alarms. The image fire alarm information includes near-infrared image and visible light image information. When the fire is detected by near-infrared image or visible light image, the image fire alarm signal is issued.When the temperature exceeds the limit, the temperature alarm signal is issued. When the smoke exceeds the limit, the smoke alarm signal is issued. The gas fire alarm information includes CO, CO2, O2, etc. When CO, CO2 or O2 exceeds the limit, the gas alarm signal is issued. The fire alarms are divided into four levels, including blue, yellow, orange and red, with red being the highest level.When one of the four alarm signals of image, temperature, smoke and gas issued, the blue alarm signal is issued. When two of the four alarm signals of image, temperature, smoke and gas issued, the yellow alarm signal is issued. When three of the four alarm signals of image, temperature, smoke and gas issued,the orange alarm signal is issued. When all four alarm signals of image, temperature, smoke and gas issued, the red alarm signal is issued.
Emulsion pump station system for super high fully mechanized working face
CHEN Wei, WANG Cunfei, BIAN Ya
2021, 47(4): 6-12. doi: 10.13272/j.issn.1671-251x.2020120020
<Abstract>(93) <HTML> (13) <PDF>(18)
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In order to meet the emulsion demand of 8.8 m super high fully mechanized working face, and solve the problems of the existing emulsion pump station system, such as low flow rate of single pump station, insufficient reliability of transmission system, short life of suction and discharge valve and slow system response, the emulsion pump station system for super high fully mechanized working face is designed. The flow rate of a single emulsion pump station reaches 1,200 L/min and the rated working pressure reaches 37.5 MPa.The key technologies of pump station system design such as slider and connecting rod spherical articulated kinematic pair, four-point support crankshaft design, super flow suction and discharge valves, pump station equalization control and real-time rapid system response are discussed.In the existing emulsion pump structure, the slider is connected to the connecting rod in the form of a cylindrical pin, which cannot adjust the center automatically, cannot eliminate the influence of lateral forces, and make the slider easily worn. In order to solve the above problems, a new form of spherical articulation is proposed, in which the connecting rod can swing to a certain extent in the horizontal direction, eliminating the influence of lateral forces in the traditional form.The unique multiple point lubrication channel design makes a stable lubricating oil film to be formed between the ball head and the hinge seat, and makes the service life longer. Four cylindrical roller bearings are used to support the crankshaft, which has strong stability and reduces the deflection of the crankshaft effectively. The stress on the crankshaft is more balanced, which solves the problem of sudden stress changes in the journal fillet. The performance of the suction and discharge liquid valve has been improved in terms of the structure, material and process, and the life of the suction and discharge liquid valve has been increased. The pump station adopts a pump station equalization control strategy to ensure that the running time of each pump is basically the same and the life of the pumps is balanced.The pump station system adopts real-time rapid response technology, which improves the response speed of the system and responds to the equipment's demand for flow and pressure in real time, ensuring the timeliness and accuracy of the action. The practical application results show that the system has reasonable structure, reliable performance and easy maintenance, which meets the requirements of the fluid supply system in the 8.8 m super high fully mechanized working face and improves the high production efficiency and safe production of coal mines.
Rapid detection method of bolt abnormality based on machine visio
WANG Yudong, DAI Wei, MA Xiaoping
2021, 47(4): 13-18. doi: 10.13272/j.issn.1671-251x.2021020038
<Abstract>(155) <HTML> (27) <PDF>(15)
Abstract:
The existing manual detection method of bolt abnormality can only perform random inspection on a single bolt, cannot check the bolt abnormality comprehensively, and has low efficiency. When the bolt is abnormal, the exposed section of the bolt often changes in length or angle, or even falls off. According to the characteristics that the length and angle of the exposed section change when the bolt is abnormal, and taking the roadway inspection robot as a platform, a non-contact bolt abnormality detection method consisting of bolt image matching and extraction and bolt characteristic detection is designed based on machine vision technology. In the bolt image matching and extraction stage, perceptual hash algorithm is used to match the collected image with the original image, histogram equalization is used to achieve image enhancement, and YOLOv3 algorithm is used to locate and extract the bolt area. In the bolt characteristic detection stage, bilateral filtering and Canny edge detection algorithm are used to extract bolt image edge information, and line segment detection algorithm is used to extract straight line segments of bolt images. Combined with the characteristic that bolt contour can be regarded as a group of parallel lines, the method can achieve the length and angle characteristic extraction, and compare with the original image bolt characteristics to realize abnormality detection. The laboratory-made data set is used to conduct experiments on the rapid bolt abnormality detection method, and the results shows that the method can detect bolt abnormality quickly and accurately.
Research on unmanned driving system of mine-used truck
YAN Ling, HUANG Jiade
2021, 47(4): 19-29. doi: 10.13272/j.issn.1671-251x.17729
<Abstract>(305) <PDF>(49)
Abstract:
With the deep exploration of large open-pit coal mines, the phenomenon of steep slopes and many bends has gradually increased. Moreover, the mine-used truck driving is difficult and there are hidden safety hazards. Therefore, a design scheme of unmanned driving system for open-pit coal mine trucks is proposed. The unmanned driving system includes a vehicular autonomous package, a vehicle-to-ground wireless data communication system and a ground management system. The driving system can realize the completely unmanned autonomous operation of ‘loading, transporting and unloading’ of mine-used trucks. In order to meet the demand of unstructured environment sensing in open-pit coal mines, a multi-source heterogeneous sensor fusion sensing algorithm for the unstructured environment of open-pit coal mines is proposed. According to the driving demand of mine-used trucks in different load qualities and different slopes, a longitudinal adaptive control algorithm considering the quality and slope is proposed to meet the requirements of longitudinal speed control and distance control under the working conditions of slope stop, slope start, fixed-point stop and shovel stop with different load qualities of mine-used trucks. According to the driving demand of large curvature steering and reversing in the mining area, the forward and backward lateral control methods based on variable parameter adaption are proposed to meet the requirements of lateral precise control of all complex roads in the mining area. The unmanned driving system has been tested in different environments such as muddy roads and night environments in the Harwusu Open-pit Coal Mine. The results show that the unmanned driving system has the ability to operate in the mining area, can track accurately, avoid obstacles and perform tasks autonomously. The ground control system can control the start and shutdown of unmanned mine-used trucks, and can remotely control and drive the mine-used trucks if necessary. The various functions of the system are stable and reliable. The development trend of unmanned driving systems in mines is pointed out. ① For vehicular system, it is necessary to build systematic and product-oriented thinking at first, select the corresponding hardware in the form of products, and improve the adaptability of the hardware in the mining area. The perception system should focus on improving the target recognition ability in the complex and heavy dust environment so as to improve the detection redundancy. The control system should focus on improving the response speed of the wire-controlled actuator so as to improve the accuracy of the load quality acquisition. The decision-making system should focus on the guiding safety at first, and further consider the guiding efficiency and improve the system operation efficiency. ② For the ground system, it should fully integrate the existing achievements of the previous stage of digital mine and be compatible with the current mining area scheduling management system. It should focus on the development of mixed running and multi-vehicle cooperative management system, which has the efficiency and energy-saving control indexes in multi-vehicle scheduling. It is proposed that the ‘cloud control’ technology should be developed vigorously, and V2X (Vehicle-to-Everything) and other advanced methods should be used to improve the cooperative safety of unmanned driving systems.
Control scheme of electric driving system for large electric wheel mine-used truck
XU Xu, BAO Weiwei, WANG Han, GAO Yu, SHEN Yanhua
2021, 47(4): 30-38. doi: 10.13272/j.issn.1671-251x.17736
<Abstract>(191) <HTML> (28) <PDF>(14)
Abstract:
The power demand of large electric-wheel mine-used trucks fluctuates greatly. It has high requirements for the backup power during acceleration and the energy recovery capacity during braking. The traditional hybrid vehicle adopts the parallel power supply method of a generator set and a single power battery. However, this method is difficult to meet the vehicle’s dual requirements for peak power and energy. In order to solve the above problem, a control scheme of electric driving system for large electric wheel mine-used truck is designed, and an energy cooperative control strategy based on the combination of power following and bus voltage regulation is proposed. In the energy control process, the generator set and battery set are used as the main energy source to follow the target demand power, the super capacitor is used as the auxiliary energy source, and the DC bus voltage is regulated by alternating the work of super capacitor and generator set. Hence, the truck can automatically select the suitable bus voltage regulation mode according to the driving conditions. Considering the limitation of the maximum charging capacity and the battery life, a method is proposed in which the super capacitor is responsible for the circuit energy recovery and slowly transfers energy to the battery according to the remaining power of the super capacitor. The simulation results of the extreme driving conditions of a specific truck show that the control scheme ensures that the truck has sufficient driving power and improves the efficiency of the electric driving system. The scheme reduces the number of repeated charging and discharging of the lithium battery, which is helpful to extend the lithium battery life. Moreover, the scheme ensures the stability of the DC bus voltage when the high power fluctuates, which improves the reliability of the electric driving system.
Study on weak environmental energy harvesting by shearer
LUO Yimin, LIU Zhenjian, LIU Bing, QIU Jinbo, ZHUANG Deyu, ZHANG Yang
2021, 47(4): 39-43. doi: 10.13272/j.issn.1671-251x.2020120026
<Abstract>(64) <HTML> (15) <PDF>(10)
Abstract:
Energy harvesting is the process of converting external environmental energy into electrical energy. This technology has certain development potential in realizing self-powered low-power wireless sensors. At present, there are few researches on the adaptability of energy harvesting systems in terms of the application of energy harvesting technology in shears. Therefore, it is unable to achieve reliable applications. In order to solve the above problems, based on the characteristics of the working environment of shearer, this paper analyzes the feasibility of the weak environmental energy being harvested by shearer and the feasibility of converting the energy into electrical energy. It is pointed out that light energy, temperature difference heat energy and vibration energy are the three typical environmental energies that exist in shearer. Theses three energies have different adaptability due to different energy characteristics. Light energy has poor adaptability and is not suitable as an environmental energy source in energy harvesting technology. Temperature difference energy source is stable and the thermoelectric power generation device is easy to install. This energy has certain adaptability. However, the thermoelectric power generation device needs to be installed in the main heat producing part of shearer, and the installation location has certain restrictions. The total amount of vibration energy is large, and the piezoelectric power generation device has a simple structure. Vibration energy is less affected by the working environment factors and has a strong adaptability without installation location restrictions.
Research on intelligent air volume regulation in mines
WU Xinzhong, ZHANG Zhichao, XU Jialin, WANG Kai
2021, 47(4): 44-50. doi: 10.13272/j.issn.1671-251x.17693
<Abstract>(139) <HTML> (17) <PDF>(14)
Abstract:
At present, most researches on mine air volume regulation are single-branch regulation, which cannot meet the requirement of large air volume of a specific wind branch. Therefore, it is necessary to distribute air on demand through multiple branch joint regulation. Based on the nodal air volume balance law, the loop air pressure balance law and the minimum air volume constraint conditions of each branch, the mine air volume regulation model is established. According to the air volume requirement of the wind branch under different ventilation network conditions, and the ventilation network sensitivity matrix, the optimal adjustable branch set and the adjustable range of air resistance are determined. The grey wolf optimization algorithm is improved by the strategies of initializing the population with good point set, fusing with the differential evolution algorithm and optimizing nonlinear control parameters. Moreover, the improved algorithm is used to optimize the mine air volume regulation model, obtain the maximum adjustable air volume of the wind branch and the corresponding adjustable branch wind resistance. In the context of the actual operation of the mine ventilation network, an intelligent air volume regulation scheme is proposed to select the number of branches according to the branch air volume requirement, and the scheme is verified based on the mine intelligent ventilation experimental platform. The results show that the regulated branch air volume meets the mine safety air volume requirement under the condition of meeting the minimum air volume requirement of other branches.
Distributed accurate time synchronization algorithm for underground coal mine time-sensitive network
SONG Haoming, HUANG Yourui, CHEN Zhenping, XU Shanyong, ZHANG Chao
2021, 47(4): 51-56. doi: 10.13272/j.issn.1671-251x.2020090008
<Abstract>(158) <HTML> (13) <PDF>(11)
Abstract:
In order to meet the requirements of high accuracy and low energy consumption of time synchronization among massive nodes of coal mine underground network, a distributed accurate time synchronization algorithm is proposed based on the time-sensitive network (TSN) of coal mine with non-uniform clustering structure of multiple Sink nodes. The underground coal mine TSN is divided into 3 layers, including the TSN convergence layer containing all Sink nodes, the main network consisting of Sink nodes and all cluster head nodes within their respective communication radius, and the secondary network consisting of cluster head nodes and common nodes in the cluster. The TSN convergence layer uses the gPTP algorithm to achieve nanosecond time synchronization among Sink nodes. The main network uses an optimized algorithm based on Kalman filter to predict and compensate for frequency offset, phase offset and noise errors so as to improve the network time synchronization accuracy. The secondary network uses the broadcast-based single and two way hybrid synchronization algorithm to reduce the number of synchronization message packets. The simulation results show that the proposed algorithm can improve the accuracy and stability of network time synchronization effectively and reduce the energy consumption of network time synchronization.
Energy optimization method of wireless monitoring network in coal mine working face
ZOU Xiangyu, LIU Yan, ZHAO Duan, ZONG Zhengxue, SHI Xinguo, ZHAI Bo, WANG Weilong
2021, 47(4): 57-61. doi: 10.13272/j.issn.1671-251x.2020030047
<Abstract>(166) <HTML> (16) <PDF>(7)
Abstract:
In coal mine working face, there are problems such as uneven energy distribution of wireless monitoring network, the difficulty of manual maintenance and node battery replacement and energy limitation of some monitoring nodes. In order to solve the above problems, an energy optimization method of wireless monitoring network in coal mine working face based on mobile nodes is proposed by using the characteristics of periodic movement of the shearer. This method installs mobile nodes on the shearer to forward data that collected by monitoring nodes in the network to reduce multi-hop data transmission, and reduces redundant data transmission by setting transmission thresholds to reduce node energy consumption. The mobile nodes are used to radiate radio frequency energy to the monitoring nodes, which provides targeted energy supplement to the monitoring nodes so as to achieve energy balance of the network nodes. The experimental results show that compared with LEACH protocol, this method can make the wireless monitoring network energy distribution more balanced, reduce the network energy consumption and monitoring node mortality rate effectively under the same operation round, and extend the effective life of the network by 2.8 times.
DA-GCN-based coal mine personnel action recognition method
HUANG Han, CHENG Xiaozhou, YUN Xiao, ZHOU Yu, SUN Yanjing
2021, 47(4): 62-66. doi: 10.13272/j.issn.1671-251x.17721
<Abstract>(204) <HTML> (28) <PDF>(21)
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At present, the monitoring video in coal mine production area is vague, the type of personnel actions is complex, and the accuracy of conventional action recognition methods is low. In order to solve the above problems, a coal mine personnel action recognition method based on dynamic attention and multi-layer perception graph convolutional network (DA-GCN) is proposed. The Openpose algorithm is used to extract the key points of the human body in the input video to obtain the key point information of the human body in 3 dimensions and 18 coordinates, reducing the interference of fuzzy background information. The spatial characteristics of the key points of the human body is extracted by dynamic multilayer perception graph convolution network (D-GCN), and the temporal characteristics of the key points of the human body is extracted by temporal convolutional network (TCN) so as to improve the generalization ability of the network for different actions. The dynamic attention mechanism is used to enhance the network's attention to action key frames and key skeletons to further mitigate the impact of poor video quality. The softmax classifier is used for action classification. Through scene analysis, underground actions are classified into five types, including standing, walking, sitting, crossing and operating equipment. The method constructs a Cumt-Action data set that applicable to coal mine scenes. The experimental results show that the highest accuracy rate of D-GCN in the Cumt-Action data set is 99.3%, and the highest recall rate is 98.6%. Compared with other algorithms, DA-GCN has higher recognition accuracy in both the Cumt-Action data set and the public data set NTU-RGBD.
Underground target detection algorithm based on improved Gaussian mixture model
ZHANG Xiaoyan, GUO Haitao
2021, 47(4): 67-72. doi: 10.13272/j.issn.1671-251x.2021010063
<Abstract>(139) <HTML> (11) <PDF>(8)
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The monitoring video images of underground coal mine have problems such as poor quality, noisy and being susceptible to sudden changes in illumination. The traditional Gaussian mixture model for target detection has problems such as slow running speed, high algorithm complexity and susceptibility to illumination. In order to solve the above problems, an underground target detection algorithm based on improved Gaussian mixture model is proposed. The improved dark channel defogging algorithm is applied to preprocess the underground image, finding the dark channel map for the thumbnail of the underground fog map, and using bilinear interpolation to obtain the defogging image. Based on the Gaussian mixture model, an improved block modeling strategy is used to reduce the modeling complexity and improve the algorithm running speed. Combined with the three-frame difference method, different learning rates are set for the early and late Gaussian modeling according to the proportion of the image foreground to suppress the influence of illumination on target detection and improve the modeling speed and accuracy. The experimental results show that when the illumination changes suddenly, the algorithm proposed in this paper can still describe the detection object well, and has a significant suppression effect on illumination changes. Compared with the three-frame difference method and the traditional Gaussian mixture model, the proposed algorithm can improve the processing speed effectively.
Experimental study of CO2 replacement for CH4 at different gas injection pressures
ZHENG Xuezhao, HUANG Yuan, WEN Hu, WANG Xilong, WANG Baoyuan
2021, 47(4): 73-78. doi: 10.13272/j.issn.1671-251x.17697
<Abstract>(159) <HTML> (12) <PDF>(15)
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Most of the existing studies on CO2 replacement for CH4 are focused on microscopic gas injection replacement mechanism and macroscopic replacement efficiency influencing factors, and most of the studies are theoretical analysis at the model level or multiple factor analysis at the simulation test level. There are few physical simulation experiments and quantitative analysis. In order to solve the above problems, by using CO2 replacement for CH4 experiment system, this paper studies the seepage diffusion evolution law and time-varying characteristics of CO2 replacement for CH4 in coal during the replacement process at different injection pressures. This paper analyzes the change law of CO2 and CH4 concentrations at the gas outlet, the accumulated CH4 replacement volume and the replacement ratio during the whole process. Physical simulation experiments are used to investigate the influence of gas injection pressure on the replacement efficiency and make the quantitative analysis. The experiments results show that: ① The CO2 and CH4 gas concentration change trends at different injection pressures are basically the same, which can be divided into three stages, including the original equilibrium stage, the dynamic equilibrium stage and the new equilibrium stage. As the gas injection pressure increases, the time of CO2 and CH4 gas breaking the original equilibrium stage is gradually shortened, the time of the dynamic equilibrium stage increases, and the time of the new equilibrium stage is about the same. ② At different injection pressures, the accumulated CH4 replacement volume increases with the increase of gas injection time, and the increase rate is fast at first and then slow, and becoming a fixed value at last. The gas injection pressure increases from 0.6 MPa to 1.4 MPa, the accumulated CH4 replacement volume increases, the replacement ratio decreases from 4.99 to 4.10, and the replacement efficiency increases. When the gas injection pressure is 1.4 MPa, the replacement ratio is the smallest and the replacement efficiency is the best. This conclusion can provide a reference for the theoretical study of CO2-ECBM related technologies and the selection of related process parameters for technical implementation in low permeability coal seams.
Research on two-dimensional inversion method of transient electromagnetic in whole-space based on particle swarm
HUANG Weiwei
2021, 47(4): 79-84. doi: 10.13272/j.issn.1671-251x.2021010032
<Abstract>(128) <HTML> (11) <PDF>(8)
Abstract:
In order to improve the detection accuracy, provide effective targets for drilling and provide reliable geological information for mine water damage prevention and control, a two-dimensional inversion method of transient electromagnetism in whole-space based on particle swarm is proposed for the complexity of actual mining conditions in coal mines. By establishing a Q-type geoelectric model and carrying out a two-dimensional forward simulation based on finite difference in the time domain, the magnetic field intensity values at each grid node at different times are obtained. The extracted magnetic field intensity values obtained from the forward simulation and the magnetic field intensity values from the measured data are inverted by the least squares method. The particle swarm algorithm is used to optimize the resistivity and formation thickness parameters, so that the fitting error of the inversion results meets the accuracy requirements. According to the measurement point number, the magnetic field intensity values after the least square inversion are calculated by the two-dimensional inversion method of transient electromagnetism in whole-space. Moreover, the transient electromagnetic field response law and inversion accuracy obtained after the two-dimensional inversion are analyzed. The practical application results show that the two-dimensional inversion method of transient electromagnetism in whole-space based on particle swarm is feasible. The low-resistance anomaly in the inversion result has layered characteristics and certain connectivity, which can better reflect the lithological structure characteristics and water-bearing characteristics of the layered formation that dominated by sand and mudstone and improve the detection accuracy and resolution.
Stability analysis of roadway surrounding rock under the action of bolt bearing layer
LI Yan, GAO Zhaoning, CHEN Dengguo, GU Wenwei
2021, 47(4): 85-91. doi: 10.13272/j.issn.1671-251x.2020120071
<Abstract>(70) <HTML> (12) <PDF>(7)
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The existing method of controlling the stability of roadway surrounding rock is to apply the bolt support resistance to the roadway surface uniformly. But there are few research on the equivalent support force of the bolt bearing layer formed by the coupling of the bolt and the surrounding rock. By analyzing the surrounding rock mechanical model, the analytical expression of the equivalent supporting force of the bolt bearing layer and the analytical expression of the stress in the elastic zone and the plastic zone of the roadway surrounding rock under the action of bolt bearing layer, the radius of the plastic zone and the surface displacement of roadway surrounding rock are obtained. The analysis results shows the following three points. ① The bolt bearing layer thickness increases when the bolt length increases. The bolt bearing layer thickness decreases with the increase of the bolt row spacing when the bolt length is fixed. The bolt bearing layer equivalent support force increases when the bolt bearing layer thickness increases. ② In the plastic zone, compared with the Fenner solution that without considering the bolt bearing layer, the tangential stress of the surrounding rock increases significantly with this solution that considering the bolt bearing layer, and the peak stress position is closer to the center of the roadway. In the elastic zone, compared with the Fenner solution, the tangential stress of the surrounding rock decreases and the radial stress increases with this solution. ③ With the increase of the equivalent support force of the bolt bearing layer, the radius of the plastic zone decreases. With the increase of the equivalent support force of the bolt bearing layer, the surface displacement of the roadway surrounding rock with the Fenner solution and this solution decreases, and the displacement change with the Fenner solution is larger than that of this solution. The Flac3D software is used to numerically simulate the stress of the roadway surrounding rock under the action of the bolt bearing layer, the radius of the plastic zone and the roadway surface displacement. The numerical simulation results are basically consistent with the analysis results of the calculation example, and the stability of the roadway surrounding rock under the action of the bolt bearing layer is more reliable.
Edge computing-oriented scraper detection method for coal preparation plants
ZHANG Zhiqiang, FENG Wei, ZHAO Xiaohu, YOU Xingyi
2021, 47(4): 92-97. doi: 10.13272/j.issn.1671-251x.2020100001
<Abstract>(75) <HTML> (12) <PDF>(13)
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The calculation amount of the current scraper detection method for coal preparation plants is large. Moreover, the method runs on the low-power, low-cost embedded Jetson Nano and has problems such as low execution efficiency and poor real-time performance. In order to solve the above problems, this paper proposes an edge computing-oriented scraper detection method that can parallelize the Hough transform.Firstly, the scraper image is pre-processed.Then the Hough transform algorithm is used to detect the scraper and calculate the scraper angle. If the scraper angle was less than the set threshold value, the alert would besent. If the scraper angle was within the threshold value, the display would be normal.In the scraper detection, the Hough transform is parallelized and the data is transmitted with zero copy. At the same time,the overall process of the scraper detection is designed into a CPU and GPU cooperative working mode. The scraper image pre-processing runs on the CPU side and the parallelized Hough transform runs on the GPU side.In this mode, the hardware resources in Jetson Nano can be fully utilized to realize real-time detection of the scraper in Jetson Nano.The experimental results show that by using the parallelized Hough transform algorithm, the scraper image in Jetson Nano with resolution of 960×540 can be detected 10 times faster than the original Hough transform. The detection frame rate can reach 17 frame/s and the scraper angle accuracy rate can reach 96.3%, which meets real-time requirements.
Gap measuring instrument of plane joint-surface for mine explosion-proof electrical devices
ZHANG Yong
2021, 47(4): 98-102. doi: 10.13272/j.issn.1671-251x.2021.04.17717
<Abstract>(96) <HTML> (8) <PDF>(9)
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The current structural inspection of mine explosion-proof electrical equipment mainly uses the feeler gauge to measure the gap width, which is inefficient and requires equipment to be shutdown. A non-contact explosion-proof electrical equipment plane joint surface gap measurement method is proposed, and an intrinsically safe plane joint surface gap measurement instrument is designed on this basis. The measuring instrument uses a microscope to collect the gap image of the plane joint surface, and obtains the gap width automatically through image binarization, inversion, denoising, cavity filling and other preprocessing methods and through minimum circumscribed rectangle image processing algorithm. The measuring instrument makes the measuring line coincide with the edge of the gap by manually adjusting the position of the measuring line so as to calculate the gap width. According to the actual situation, the gap measurement mode of the plane joint surface of the explosion-proof electrical equipment can be selected by the key of the measuring instrument. The test results show that the gap measurement error of the measuring instrument in the automatic measurement mode is less than 0.02 mm, the measurement process is less than 3 s, and the measurement error in the manual measurement mode is less than 0.01 mm, which meets the requirements for rapid and accurate measurement of the gap of the plane joint surfaces of explosion-proof electrical equipment. When using the measuring instrument to measure the gap of the plane joint surface of mine explosion-proof electrical equipment, the dangerous plane joint surface gap can be quickly determined by the automatic measurement mode, and then the gap can be further measured precisely by using the manual measurement mode.
Two-dimensional Gabor filter-based  belt tear detection
LIU Xiaoyang, LIU Jing, ZHANG Xiangyang, SHEN Lifei, DENG Zhigang, MA Xinyan, WANG Di
2021, 47(4): 103-107. doi: 10.13272/j.issn.1671-251x.2020110045
<Abstract>(138) <HTML> (12) <PDF>(8)
Abstract:

As the existing belt tear detection method based on machine vision technology being used for images with complex background texture, it is easy to misjudge the defect areas with inconspicuous tear marks relative to the background texture as non-defects, and the detection results are noisy and difficult to identify. In order to solve the above problems, a belt tear detection method based on two-dimensional Gabor filter  is proposed. The method uses Gabor filtering to process the belt images and obtain multiple Gabor filtered processing images. Through the Gabor optimization selection method, a new cost function is constructed based on the coefficient of variation, and the optimal filter channel is selected to highlight the texture characteristics of the tear area. The Sobel operator is used to extract the texture characteristics of the tear area in the horizontal and vertical directions respectively so as to obtain the gradient images of the two directions. The self-propagation normalization operation is applied on the obtained gradient images to enhance the texture information, and the pixel-weighted average method is used to fuse the two images. The obtained fused images are segmented by adaptive threshold binarization method, and morphological technology is used to perform belt tear detection on the images to be detected. The detection results show that the improved Gabor optimization selection method has a lower miss detection rate than the Gabor optimization selection method and the Sobel operator-based longitudinal tear detection method. The method can detect all defects in the belt defect images with complex background texture. The detection results are clear and the contour characteristics of the tear area are preserved relatively well.
Driving system design of inspection robot for mine belt conveyor
LIANG Zhanze
2021, 47(4): 108-112. doi: 10.13272/j.issn.1671-251x.2021010003
<Abstract>(169) <HTML> (11) <PDF>(18)
Abstract:
The current research on mine belt conveyor inspection robots mainly focuses on the fault identification and diagnosis of belt conveyor inspection robots, while there are few researches the movement of inspection robots. There are large amount of equipment in roadways of coal mines, the working space is narrow and the terrain is complicated. Therefore, when the inspection robot moves, it will encounter extreme road conditions such as climbing slope and coal mud obstacles. In the context of the long inspection distance of the mine belt conveyor, the relatively single inspection target and fixed inspection route, the rail type driving system is adopted as the walking mode of the inspection robot. However, when the rail surface is covered by the coal mud, the driving wheels will be stuck. Moreover, when facing the rail with a large slope, the robot may skid. Therefore, a four-wheel support and two-wheel drive rail type driving system is designed. The inspection robot moves forward by the friction between the driving wheels and the rail, while the support wheels carrying the quality of the inspection robot and playing the role of walking assistance. The finite element simulation analysis is carried out on the main parts of the inspection robot driving system, which are the driving shaft and the swing arm. The ultimate stresses of the driving shaft and the swing arm are 83.2 MPa and 65.8 MPa respectively, which are much lower than the yield strength of the material, ensuring the performance reliability of the inspection robot. The climbing and coal mud obstacles crossing performance of the inspection robot driving system is tested. The results show that the inspection robot can still complete acceleration on the 25° slope rail, and runs smoothly during up and down slopes. There is no skidding and jamming when running on the coal mud obstacle rail.
Object-oriented device modeling method and its applicatio
JING Cheng, LIU Lijing, CHEN Xing, ZHOU Pufan
2021, 47(4): 113-115. doi: 10.13272/j.issn.1671-251x.2020120063
<Abstract>(121) <HTML> (20) <PDF>(16)
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The communication protocols of different coal mine monitoring systems correspond to different data structures, which makes it difficult to configure and manage device information when multiple coal mine monitoring systems are integrated. To solve the above problems, an object-oriented device modeling method is proposed. The method converts a variety of non-standardized data structures into standardized data structures through data driving, and establishes corresponding device models based on the relevant attributes of actual devices. The method creates device instances based on device model, uses hierarchical tree structure to display the parent-child relationship of device instances, and displays the detailed information of device instances through dynamic pages, which enables unified configuration and management of devices with different attributes. The object-oriented device modeling method is applied to the graphic configuration so as to bind the device model to the graphic element and bind the device instance to the graphic instance, which can quickly configure the data visualization graphics.
Coal quality whole process management system desig
JIANG Shuijun, HU Min
2021, 47(4): 116-120. doi: 10.13272/j.issn.1671-251x.2021010005
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Abstract:
In the process of coal quality management by CHN Energy Group Shendong Coal Group Co., Ltd., there are problems such as insufficient data sharing, low efficiency of manual coal quality prediction and labor-intensive coal quality inspection and assessment. In order to solve the above problems, based on the coal quality management business process, this paper designs a coal quality whole process management system. The system uses a combination method of workflow technology and status control fields to achieve coal quality information sharing among different departments, which enables coal quality data to flow quickly among different departments and ensures the traceability, uniqueness and accuracy of the data. Through the RBAC(role-based access control) permission control model based on the tree structure function module, the proposed system simplifies the system permission configuration, ensures the validity and security of coal quality data flow and prevents 'illegal users' from invading the system or 'legal users' from accidentally operating the system and causing data loss. The system realizes the input, analysis, sorting and statistics of coal quality related data, and forms corresponding coal quality reports/graphics and coal quality prediction plans, etc. It is helpful to provide the real-time monitoring of coal quality information for management departments at all levels and ensure the timeliness, authenticity and security of coal quality information circulation.

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