工矿自动化

Coal mine roadway roof monitoring system based on distributed optical fiber technology

HOU Gongyu, HU Tao, XU Guicheng, MA Zhanbiao, LIANG Haiping, WANG Shunguang, ZHENG Gang

2020, 46(1): 1-6. doi: 10.13272/j.issn.1671-251x.2019090002

<Abstract>(67) <HTML> (5) <PDF>(20)

Abstract:
At present, roadway roof deformation monitoring method adopts on-line real-time monitoring based on underground industrial ring network, electronic and fiber Bragg grating displacement sensors which are connected by wireless means, has many blind spots, large errors, and relies on continuous power supply. For the above problems, coal mine roadway roof monitoring system based on distributed optical fiber technology was designed. The system uses Brillouin optical time domain reflectometer (BOTDR) as the core monitoring tool for data collection and analysis. It uses 5 mm stranded steal optical fiber as sensing fiber, and uses anchor rod and anchor cable as fixed points to lay optical cable. The strain of the optical fiber is used to monitor deformation of the roof, and the real-time online distributed monitoring of the roof of the coal mine roadway is realized. Field application results show that the fiber strain change can accurately reflect roof deformation in real time,the roof monitoring results based on fiber strain are consistent with the monitoring results of the roof delamination instrument and the cross method. Using fiber optic strain to characterize roof deformation eliminates human factors and power outages, and ensures objectivity of the monitoring results. The power-free distributed optical fiber strain monitoring method with long-distance, good corrosion-resistant and anti-interference performance provides a new way of roadway monitoring for coal mine.

Experimental research on "drilling-cutting-fracturing" pre-fracturing to prevent rock burst technology for deep hole of roof of coal seam

MA Wentao, PAN Junfeng, LIU Shaohong, WANG Shuwen

2020, 46(1): 7-12. doi: 10.13272/j.issn.1671-251x.2019050074

<Abstract>(88) <HTML> (7) <PDF>(17)

Abstract:
Abstract:In view of problems of complicated process of slot prefabrication and poor quality of seam formation in existing roof directional hydraulic fracturing technology, a technology of drilling, high-pressure water jet cutting and high-pressure hydraulic fracturing (drilling-cutting-fracturing) integrated pre-fracture roof to prevent rock burst was put forward, and experimental research of the technology in Hulusu Coal Mine was carried out. The experimental results show that the "drilling-cutting-fracturing" integrated technology and equipment can cut grooves manually without retreating drill pipe, and use single hole retreating multiple fracturing to improve construction efficiency. The symmetrical double hole high pressure jet device can effectively form a 4-5 mm wide artificial fracture groove to increase fracture cutting effect, reduce fracture initiation pressure,and expand fracture radius. The maximum single fracturing radius of roof strata with uniaxial compressive strength of 50-60 MPa can reach 15 m. The "drilling-cutting-facturing" technology weakens the roof and reduces the stress level of surrounding rock. The number of high-energy microseismic events near the goaf roadway has been greatly reduced, and the frequency and energy of microseismic events have not changed dramatically, so as to ensure the smooth mining of the working face.

Research and development of mixing humidification experimental device of atomization and water bath

QIN Ruxiang, XU Tongzhen, LIU Yarui, GAO Wei, CHEN Wentao, ZHOU Liang

2020, 46(1): 13-17. doi: 10.13272/j.issn.1671-251x.2019050066

<Abstract>(24) <HTML> (5) <PDF>(7)

Abstract:
The existing humidification device for air humidity and low temperature oxidation of coal basically adopts a single humidification method,which has low humidification accuracy,small humidification range and incomplete automatic humidification. In view of the above problems,based on the heat and humidity exchange principle,a mixing humidification method combining with water bath and high pressure atomization was proposed,and a mixing humidification experimental device of atomization and water bath was developed. The device realizes humidification by water bath and atomization step by step. The air enters the box through inlet pipe and contacts with water at the bottom of the device to realize water bath humidification. After the humidification of water bath,the air comes out from the water and continues to contact with the water mist in the box after high-pressure atomization,thus realizing high-pressure atomization and humidification. The air outlet of the device is equipped with a humidity controller,which can set different relative humidity according to the needs,and can detect the air in the device in real-time,so as to achieve accurate control of air humidification. The mixing humidification method of water bath and high pressure atomization not only shortens the humidification time of the air,but also enlarges the humidity regulation range of the device,so as to realize the humidification needs of different ranges.

Abnormal data recognition method of coal mine monitoring system based on imbalanced data set

JI Wenli, XI Liutao, WANG Bi

2020, 46(1): 18-25. doi: 10.13272/j.issn.1671-251x.17502

<Abstract>(36) <HTML> (5) <PDF>(10)

Abstract:
Abnormal data recognition plays an important role in mine safety monitoring system, but abnormal data generally only accounts for about 1% of the total data of the safety monitoring system, data imbalance is an intrinsic characteristics of real-time data. At present, most of machine learning algorithms have relatively poor classification accuracy and sensitivity while dealing with classification on imbalanced data sets. In order to accurately identify abnormal data, the data collected by the distributed fiber shaft deformation monitoring system of coal mine is taken as research object, RDU-SMOTE-RF abnormal data recognition method of coal mine monitoring system based on imbalanced data set was proposed. The method uses RDU algorithm for under-sampling of majority data to remove duplicate samples,uses SMOTE algorithm for oversampling of minority abnormal data to improve the imbalance of the data set by synthesizing new abnormal data, and uses the optimized data set to train random forest (RF) classification algorithm to get abnormal data recognition model. The comparison experimental results on 6 real data sets show that the method has an average recognition accuracy rate of 99.3% for abnormal data, which has good generalization and strong robustness.

Research on information visualization of smart mine

TAN Zhanglu, WU Qi, XIAO Yixuan, WANG Zhen, LI Shuo

2020, 46(1): 26-31. doi: 10.13272/j.issn.1671-251x.2019050074

<Abstract>(55) <HTML> (4) <PDF>(13)

Abstract:
Existing information visualization researches of smart mine focus on 3D virtual scene building and real scene monitoring, but ignore selective visual display considering focus points of managers. For the above problems, based on general structure of smart mine of four transversal layers and three longitudinal systems, visualization information framework of smart mine is built by use of visualization mode selection model of ISVE(Information-Subject-Visualization-Effectiveness). Information systems of smart mine are divided into engineering digitization system, integrated automation system and management informationization system. Information in each system is classified on basis of service-object-oriented thought, and attributes of each type of information are researched. A selection thought of information visualization mode is proposed which takes cognition agent as a core. Appropriate information visualization mode should be selected according to information focus points of executives in each management layer of coal mine enterprise, so as to improve cognition efficiency of executives and promote development of informationization and intelligence of coal mine enterprise.

Discussion on mine broadcasting system and its application in coal mine emergency communicatio

ZHENG Xuezhao, GUO Hang, GUO Jun, WANG Baoyuan

2020, 46(1): 32-37. doi: 10.13272/j.issn.1671-251x.17501

<Abstract>(95) <HTML> (4) <PDF>(10)

Abstract:
Development history of mine broadcasting system and the research status of mine broadcasting system based on IP technology, mine broadcasting system based on CAN bus, and mine broadcasting system based on wireless Mesh network were introduced. The characteristics of three kinds of broadcasting systems are analyzed. Mine broadcasting system based on IP technology realizes reliable and fast emergency notification from ground dispatching room to underground working surface, but the optical cable is mainly laid in the roadway, network coverage is low, besides, the use of IP broadcasting requires a lot of IP space, and because the mine environment is complex,the equipments are difficult to set up and receive signals, and have poor resistant capability to disaster. Mine broadcasting system based on CAN bus has the advantages of long transmission distance, fast communication rate, flexible communication method, stable transmission, etc., but because each node unequally shares the bus bandwidth, there will be situations where multiple nodes compete for the bus at the same time which affects stability and real-time performance of communication. Wireless Mesh network has the advantages of high reliability, wide coverage, and flexible networking. However, due to the multi-hop mechanism of the wireless Mesh, as the scale of wireless Mesh network expands, more and more hops are connected, and the total accumulated delay is great. It is pointed out that with the transformation and upgrading of coal industry and the continuous improvement of safe production technology in coal mines, mine broadcasting system will develop in the direction of improving disaster resistance, diversified functions, system intelligence, and multi-system integration; application prospects of mine broadcasting system in coal mine emergency communications is summarized from three aspects of safety monitoring, dispatching command, information transmission, it is pointed out that the combination of mine broadcasting system and personnel positioning system is a typical model of future coal mine dispatching command, adaptive function of wired and wireless routing will greatly improve resistant capability to disaster and reliability of the emergency communication system.

Research status of coal-gangue identification method and its prospect

CAO Xiangang, LI Ying, WANG Peng, WU Xudong

2020, 46(1): 38-43. doi: 13272/j.issn.1671-251x.2019060005

<Abstract>(155) <HTML> (4) <PDF>(27)

Abstract:
According to coal-gangue identification features, research status of coal-gangue identification method was summarized, and representative research achievements of some coal-gangue identification methods were enumerated, such as density identification method and hardness identification method, which were characterized by density and hardness, as well as ray identification method and image identification method, which were characterized by gray scale and texture. Characteristics of various identification methods were compared. Research directions and ways of coal-gangue identification method were prospected, namely researching coal-gangue identification methods which met green development requirements of coal mine, fast and efficient coal-gangue image identification method and new efficient coal-gangue identification method fusing and innovating existing methods on basis of full analysis and understanding feature differences between coal and gangue.

Multi-index monitoring of rock burst and risk zone division of island mining coal face

JIANG Xiyin, TAO Weiguo

2020, 46(1): 44-49. doi: 10.13272/j.issn.1671-251x.2019050062

<Abstract>(38) <HTML> (6) <PDF>(11)

Abstract:
Under superposition influence of stress concentration of coal pillar and dynamic pressure of working face in mining process of island mining coal face, rock burst disaster is easy to occur.At present, the single index is used to give early warning to the impact risk, which has large error in early warning and cannot fully reflect impact risk in the mining process. For the above problems, in order to study hazard degree of rock burst in the mining process of island mining coal face, taking 93down 05 island mining coal face of Jining No.2 Coal Mine as engineering background, a multi-index monitoring method of rock burst of island mining coal face was put forward. The impact risk of the working face was analyzed by means of cuttings，microseismic and borehole stress, and risk zones were divided according to the impact risk of different areas of the working face. The analysis results show that the maximum and total vibration energy of microseismic day, cuttings and borehole stress value are significantly increased in the vicinity of connection roadway and unprotected area, and it is concluded that the vicinity of connection roadway and unprotected area are the dangerous areas of rock burst during the mining process of the island mining coal face. According to the result of the classification of dangerous regions and considering the difference of stress concentration degree in different regions, a large-diameter pressure relief and anti-impact measure with parameter differences was proposed and implemented, which reduces the stress concentration degree, avoids the energy accumulation and prevents occurrence of rock burst disater.

Research on unsupervised sensing methods of typical coal and rock based on reflectance spectroscopy

YANG En, WANG Shibo, WANG Saiya, ZHOU Yue

2020, 46(1): 50-58.. doi: 10.13272/j.issn.1671-251x.2019050078

<Abstract>(44) <HTML> (5) <PDF>(9)

Abstract:
In view of problem of poor recognition effect of existing supervised recognition methods of coal and rock based on reflectance spectroscopy when positions of coal and rock change, in order to study self-adaptive recognition of typical coal and rock based on reflectance spectroscopy, an unsupervised sensing methods of typical coal and rock based on reflectance spectroscopy and fuzzy C-means clustering (FCM) algorithms with improved clustering distances was proposed. Four typical types of coal and rock samples of Xinglongzhuang Coal Mine including gas coal, mudstone, siltstone and argillaceous limestone were studied and spectral reflectance curves of each sample were measured in near infrared band at multiple back reflection angles. The characteristic band with the most different spectral curves of the four types was analyzed and 2 150-2 400 nm were selected as the characteristic bands with the differences of the four types. In the characteristic band, the unsupervised recognition of reflectance spectra of coal and rock was studied for each coal-rock spectra combination of gas coal-mudstone, gas coal-siltstone and gas coal-argillaceous limestone. The results showed that with increasing of back reflection angle, back spectral reflectance of surfaces of all the four types increased first and then decreased. Meanwhile, the depth of absorption valleys of mudstone, siltstone and argillaceous limestone slightly decreased, and the decrease of the depth of absorption valleys of gas coal was relatively obvious. The improved FCM (RFCM, CFCM) methods were used to cluster spectral data quickly, and classifications of the spectral data were determined by membership probability matrix of the final clustering to recognize classifications of coal and rock at different positions. Comparing with FCM, the recognition rates of each coal-rock combination were both more than 90% using the two improved FCM methods. Among them, CFCM took the least number of iteration to cluster and recognize each coal-rock combination, and its total time consumptions were all less than 0.1 s. CFCM is the preferred method and provides a reference for the application of reflectance spectroscopy technology to the highly efficient and adaptive recognition of coal and rock at different positions of coal-rock interface.

Fusion positioning method of underground mine personnel

LI Zongwei, WANG Chong, WANG Gang, XU Zhiming, CUI Pengzhi, JIANG Mengfeng

2020, 46(1): 59-64. doi: 10.13272/j.issn.1671-251x.2019120026

<Abstract>(89) <HTML> (4) <PDF>(18)

Abstract:
For problems that time of flight (TOF) ranging positioning method has many blind spots and limited positioning accuracy, which is easily interfered by non-line-of-sight, and strapdown inertial navigation positioning method has a long time accumulated error, a fusion positioning method of underground mine personnel based on TOF ranging positioning and strapdown inertial navigation positioning is proposed. The method locates by region. When positioning terminal is located within short-range wireless communication coverage area of positioning base station, TOF ranging positioning method is used to send positioning result to nearby positioning base station through short-range wireless communication mode. When positioning terminal is located outside short-range wireless communication coverage area of positioning base station, strapdown inertial navigation positioning method is used, and positioning data is corrected by Kalman filter algorithm and sent to nearby positioning base station through long-range wireless communication mode. When positioning terminal is located outside long-range wireless communication coverage area of positioning base station, positioning terminal locally stores positioning data. When positioning terminal moves within wireless communication coverage area of positioning base station, the stored positioning data is sent to positioning base station. The positioning base station transmits the positioning data to ground monitoring center to obtain personnel trajectory and position coordinates. The experimental results show the effectiveness of the method.

Path planning of mine search and rescue robot based on two-particle swarm optimization algorithm

FENG Shuo, XIE Tingchuan, KANG Jing, LI Jianliang

2020, 46(1): 65-71. doi: 10.13272/j.issn.1671-251x.2019050092

<Abstract>(58) <HTML> (4) <PDF>(13)

Abstract:
In view of problems of slow iterative speed and low solution accuracy of standard particle swarm optimization algorithm used in the path planning of mine search and rescue robot in complex terrain, a path planning method for mine search and rescue robot based on two-particle swarm optimization algorithm was proposed. Firstly, the obstacles are expanded into regular polygons to build an environment model, and then the improved two-particle swarm optimization algorithm is used as the path optimization algorithm. When the sensor detects obstacles within a certain distance in front of the search and rescue robot, it starts to run the improved two-particle swarm optimization algorithm: particle swarm optimization algorithm with improved learning factor (CPSO) grows in steps, which is suitable for finding paths in relatively open areas, while particle swarm optimization algorithm with dynamic velocity weight (PPSO) has small particle steps, which makes it good at finding paths in complex and variable areas of obstacle shapes. Then the algorithm evaluates the paths obtained by the two particle swarm optimization algorithms whether meet the obstacle avoidance requirements or not. If both meet the obstacle avoidance requirements, the shortest path is selected as the final path. Finally, the optimal driving path of the mine search and rescue robot in the whole road condition model is obtained. The simulation results show that the convergence speed of particle swarm optimization algorithm is improved by improving the learning factor and adding the dynamic velocity weight, and the optimal solution fluctuation range is reduced; the improved two-particle swarm optimization algorithm can be effectively combined with the path planning model, and the optimal path can be found in the complex road section, which improves the success rate of path planning and shortens the path length.

Intelligent control strategy for top coal caving based on Q-learning model

LI Qingyuan, YANG Yi, LI Huamin, FEI Shumin

2020, 46(1): 72-79. doi: 10.13272/j.issn.1671-251x.2019110001

<Abstract>(60) <HTML> (5) <PDF>(11)

Abstract:
Traditional top coal caving control on fully mechanized caving face has problems of low top coal recovery ratio and high gangue proportion,and existing intelligent decision-making methods have obstacles such as difficulty in modeling and obtaining learning samples. In view of above problems,the idea of reinforcement learning was introduced into the decision-making process of coal outlet of hydraulic support,and an intelligent control strategy for top coal caving based on Q-learning model was proposed.With the main goal of maximizing the benefits of coal caving combined with real-time state characteristics of top coal release and dynamic occurrence status of top coal,a dynamic decision-making algorithm based on Q-learning is used to generate real-time action strategy of multiple coal outlets online, and optimize cooperative coal caving process of multiple coal outlets,reasonably balance relationship between top coal recovery ratio and gangue proportion. The results of simulation and comparative analysis show that the average recovery ratio of top coal of the proposed control strategy is 91.24%,which is about 15.8% higher than that of the traditional coal caving method; the average global reward value is 685,which is about 11.2% higher than that of the traditional coal caving method. The proposed control strategy can significantly reduce the impact of coal and gangue mixed phenomena on the coal caving process,improve efficiency of top coal discharge,and reduce waste of coal resources.

Pedestrian detection algorithm of coal mine underground

YANG Qingxiang, LYU Chen, FENG Chenchen, WANG Zhenyu

2020, 46(1): 80-84. doi: 10.13272/j.issn.1671-251x.17540

<Abstract>(30) <HTML> (4) <PDF>(9)

Abstract:
Due to uneven underground illumination and high similarity between pedestrian characteristics and background, pedestrian detection technology based on computer vision is facing great challenges in underground application. Faster region convolutional neural networks(RCNN) was proposed for pedestrians detection of coal mine underground. Faster RCNN pedestrian detection algorithm uses region proposal network(RPN) to generate candidate regions. RPN shares convolutional layer with Fast RCNN, so as to improve network training and detection speed. A dynamic self-adaptive pooling method is adopted to perform self-adaptive pooling operation for different pooling domains in the process of image feature extraction, so as to improve detection accuracy. The experimental results show that the algorithm has better detection effect for pedestrian image in different environments.

XU Xiaoben, HU Zuxiang, XING Lifen, HAO Xue

2020, 46(1): 85-89. doi: 10.13272/j.issn.1671-251x.2019080047

<Abstract>(35) <HTML> (4) <PDF>(7)

Abstract:
Taking 1232(1) fully-mechanized mining face of Xieqiao Mine of Huainan Mining Group as engineering background, overburden displacement characteristics during coal seam mining were studied by means of similar simulation experiment. The results show that with continuous advance of fully mechanized mining face, caving angle remains unchanged, caving zone and fault zone height increase gradually, and overburden are increasingly affected by mining. Peak value of overburden vertical displacement is located in the middle of goaf and decreases gradually at both ends. The overburden vertical displacement curve is symmetrical. With the increase of advancing distance of fully mechanized mining face, peak value of overburden vertical displacement increases continuously. With the increase of distance between overburden and coal seam, overburden vertical displacement decreases.

Optimization test of ultra-high pressure hydraulic slotting process parameters in Xuehu Coal Mine

CHEN Hongtao, LI Taixun

2020, 46(1): 90-94. doi: 10.13272/j.issn.1671-251x.2019060067

<Abstract>(72) <HTML> (19) <PDF>(7)

Abstract:
Due to high gas content and poor gas permeability in No.2 coal seam of Xuehu Coal Mine, coal seam gas is treated by borehole along the bed, which has problems such as poor gas drainage effect and long time to reach standard. For the above problems, an ultra-high pressure hydraulic slotting technology was applied to borehole gas drainage of the coal seam. Single-factor test was carried out to determine optimum process parameters of ultra-high pressure hydraulic slotting applicable to the No.2 coal seam of Xuehu Coal Mine: slotting pressure is 60-70 MPa, slotting time is 25 min, slotting speed is 80 r/min and slotting spacing is 2 m. After field application of ultra-high pressure hydraulic slotting technology with the optimized process parameters, average daily gas drainage volume fraction of slotting borehole is about 1.75 times that of ordinary borehole, average daily gas drainage pure volume is 3.25 times, time of gas drainage to reach standard is shortened by about 42% and residual gas content is small.

Design of extensible data acquisition system for semi-physical fully mechanized mining operating platform

LIU Ningning

2020, 46(1): 95-99. doi: 10.13272/j.issn.1671-251x.2019100002

<Abstract>(30) <HTML> (4) <PDF>(6)

Abstract:
Various types of semi-physical operating platforms are gradually applied to mine equipment training, but there are problems such as long development cycle and resources waste in developing specific data acquisition system for specific simulated equipment. Based on analysis of data acquisition requirements of semi-physical fully mechanized mining operating platform, an extensible data acquisition system was designed. The core of the system is data acquisition board composed of main board and extension circuit board. The main board and extension board can acquire 8-channel analog signals and 16-channel switching signals respectively. Modes of one main & multi-extension and one main & multi-slave & multi-extension can be realized through different combinations of the main board and extension board, which are respectively suitable for data acquisition mainly based on switching signal and analog signal. The system can meet data acquisition requirements of various types of semi-physical operating platforms and has a certain degree of universality.

Composite layered equalization circuit for LiFePO4 battery pack of mine-used monorail

WANG Liang, ZHANG Ya, LUO Shuang, WU Liangshu

2020, 46(1): 100-104. doi: 10.13272/j.issn.1671-251x.2019110076

<Abstract>(38) <HTML> (8) <PDF>(7)

Abstract:
In continuous charging and discharging cycle of LiFePO4 battery pack of mine-used monorail, inconsistency among each single batteries will lead to overall performance degradation and shorten service life of the battery pack. Traditional battery pack equalization mode has long equalization time and complex control strategy. In order to solve the above problems, a composite layered equalization circuit was proposed based on Buck-Boost equalization circuit and flying-capacitor equalization circuit. Buck-Boost equalization circuits in bottom layer and middle layer are constructed according to binary tree structure, and flying-capacitor equalization circuit in top layer realizes energy transfer of any two batteries between three adjacent batteries, so that the batteries can not only transfer energy within layer to achieve equalization between adjacent batteries, but also transfer energy between layers to achieve equalization between non-adjacent batteries. The simulation results show that the composite layered equalization circuit greatly reduces equalization time and significantly improves battery voltage consistency.

Design of intelligent coal and gangue sorting system based on EAIDK

WANG Guanjun, SU Tingting, LIU Wenbo, QIAN Zhiping, LI Jiaze

2020, 46(1): 105-108. doi: 10.13272/j.issn.1671-251x.2019050019

<Abstract>(86) <HTML> (16) <PDF>(24)

Abstract:
Existing coal and gangue sorting method based on image identification has poor real-time performance and low sorting accuracy, the density-based sorting method is suitable for underground preparation but has high cost. In view of above problems, an intelligent coal and gangue sorting system based on EAIDK was designed. Embedded artificial intelligence development platform EAIDK is used to build hardware platform for gangue recognition and sorting control, deep learning algorithm is used to build a convolutional neural network under embedded deep learning framework Tengine, and end-to-end trainable image detection model is established and trained by image data obtained by smart cameras.Relationship between the camera coordinate system and the robot arm coordinate system is obtained through hand-eye calibration, and the gangue is tracked and sorted by robot arm. The experimental results show that the system's gangue recognition accuracy remains stable above 95%, the tracking time of robot arm is less than 30 ms, and the execution error is about 1 mm, which can meet the requirements of coal gangue sorting process.

2020 Vol. 46, No. 1

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