2021 Vol. 47, No. 12

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Cover Catalogue
Achievements of Scientific Research
Real-time video processing system in coal mine based on edge-cloud collaborative framework
LI Jingzhao, QIN Xiaowei, WANG Lei
2021, 47(12): 1-7. doi: 10.13272/j.issn.1671-251x.2021070023
<Abstract>(236) <HTML> (14) <PDF>(36)
Abstract:
At present, the intelligent video monitoring in coal mine mainly adopts cloud computing to process real-time video, and the video transmission occupies large network resources and has high delay, which can not respond to emergency events in the monitoring area in real time. In order to solve this problem, a real-time video processing system in coal mine based on edge-cloud collaborative framework is proposed. In this system, the real-time target recognition task is sent to the edge, and the tasks with large calculation and weak real-time performance such as edge device integration are sent to the cloud for processing. At the video monitoring site, the neural network model deployed on the edge device is used to process the video monitoring image locally. Through the underground heterogeneous fusion network, the processing results and model parameters of the edge devices in different network environments are sent to the cloud server. The cloud server updates and pushes the model of edge devices in each scene, and finally realizes real-time interaction of edge-cloud data and online optimization of edge services. In order to solve the problems that Tiny-YOLOv3 can not extract the deep characteristic of the image, and is prone to gradient disappearance and over-fitting, a down-sampling residual module is designed according to the residual structure, and Tiny-YOLOv3 is improved to improve the deep characteristic extraction and generalization capability of the model. On the basis of edge-cloud data interaction, the target detection model on the edge device is optimized for the targeted scene to improve the accuracy of model detection on the edge device. The test results show that the stability and data generalization capability of the improved Tiny-YOLOv3 model are better than those of YOLO and Tiny-YOLOv3. After specialized training in a single scene, the improved Tiny-YOLOv3 model is more accurate in target recognition. Compared with cloud computing, the edge-cloud collaborative framework can reduce the latency of monitoring video processing significantly.
Research on safety application technology of coal mine 5G communication system
ZHANG Liya
2021, 47(12): 8-12. doi: 10.13272/j.issn.1671-251x.17854
<Abstract>(242) <HTML> (27) <PDF>(33)
Abstract:
According to the safety application requirements of coal mine 5G communication system, the safety application technology of 5G core network side and wireless access side is studied. On the core network side, a private network technology and a network slicing technology are adopted to realize the physical isolation of different coal mine business scenarios. A proportional fair algorithm is adopted to optimize the allocation of resource blocks in a slicing group to realize the slicing resource scheduling and guarantee the safe and reliable transmission of coal mine business data. On the wireless access side, the antenna isolation circuit is designed to realize the intrinsic safety of the output signal of the base station, and the RF threshold power of the 5G base station is limited to 6 W so as to eliminate the potential safety danger caused by radiated energy, and to realize the safe access of a variety of underground mine terminal device. The underground test results show that the wireless coverage radius of the 5G base station is 100 m, the signal strength in the coverage area is not less than 100 dB, the upload rate is not less than 520 Mbit/s, the average communication delay is 18.56 ms, and the user service performance is improved by 52.8% when the number of users is 200. On the basis of ensuring the safety and reliability of the communication system, the 5G base station meets the requirements of multiple concurrency, large capacity, high speed and low delay wireless communication of coal mine business data.
Design of current sharing system for mine explosion-proof lithium power supply
LI Qiwei, CHEN Wei, ZHANG Jian, SHAO Tiantian
2021, 47(12): 13-18. doi: 10.13272/j.issn.1671-251x.2021110006
<Abstract>(112) <HTML> (5) <PDF>(26)
Abstract:
In order to solve the problem of uneven discharge current when multiple mine explosion-proof lithium power supplies are used in parallel, a current sharing system for mine explosion-proof lithium power supply is designed. The system is composed of several explosion-proof lithium power supplies connected in parallel. The explosion-proof lithium power supplies adopt 166 60 A·h lithium iron phosphate batteries connected in series in the explosion-proof cavity. The digital current sharing strategy based on the average current is adopted, the current sharing controller is used as the current adjustment component, and the double closed-loop control is adopted. The inner loop of the system is a current loop, and the outer loop is a voltage loop. A current sharing compensation is added to the voltage loop. The current sharing control is realized through voltage deviation signal and current sharing compensation signal. The test results show that after the current sharing system is adopted, the current sharing unbalance degree is 1%~2% when the total load current is 20 A, and the current sharing unbalance degree is kept within 1% when the total load current is greater than 30 A. Compared with the power supply without current sharing strategy, the parallel current sharing effect of power supplies using digital current sharing strategy is better and the power supply reliability is higher.
Spray sealing technology for gas extraction drilling
KONG Weiyi, ZHAO Heping, LIU Quanlin, ZHOU Xin
2021, 47(12): 19-24. doi: 10.13272/j.issn.1671-251x.2021050022
<Abstract>(102) <HTML> (3) <PDF>(11)
Abstract:
The sealing quality of extraction drilling is the key factor affecting gas extraction and outburst elimination. In order to solve the problems of poor quality of passive hole sealing, low gas concentration in drilling and extraction, and cumbersome process of active hole sealing, a spray sealing technology for gas extraction drilling is proposed. After the drilling construction is finished, a pneumatic deep-hole centrifugal spray cup type high-rotation speed spray nozzle is sent to the preset position of the drilling hole, and a hole sealing material preheating system is started at the same time. When the temperature of the spray type hole sealing material is stabilized at 70-80℃, a pneumatic suction pump is started to suck the sealing material, and the sealing material is mixed and sprayed out through the spray nozzle and solidified on the inner wall of the drilling hole. The four-quadrant slide structure system guides the nozzle to move from the bottom of the hole to the mouth of the hole to complete the spray-type sealing operation. Finally, the PVC plug of 2.0-3.0 m is fixed with the polyurethane foam material at the drilling hole, and then the extraction system is connected. The field application results show that the new spray sealing material has the advantages of liquid quick setting, good sealing performance, strong adhesion, flame retardant, high toughness and high strength, etc. It can react and solidify quickly in the gas extraction hole, and form a flame retardant sealing film with high strength and toughness. The use of spray sealing technology and equipment can realize automatic sealing of coal seam drilling. Compared with polyurethane sealing technology, the volume fraction of gas extraction after applying spraying-type sealing technology is increased by 19%, the cost of single-hole sealing is saved by 53%, and the sealing time of single-hole is saved by 50%.
Analysis Research
Research on trajectory control of dual-power composite directional drilling in underground coal mine
LI Quanxin, CHU Zhiwei, XU Chao, YANG Dongdong
2021, 47(12): 25-31. doi: 10.13272/j.issn.1671-251x.2021060038
<Abstract>(115) <HTML> (14) <PDF>(8)
Abstract:
Drilling trajectory control is one of the key technologies to achieve safe and efficient composite directional drilling. Due to the different force conditions of drilling tools in the hole and the composition of the analysis model, the existing trajectory control theory of composite directional drilling in the field of surface oil and gas drilling cannot be directly applied to the coal mine. Based on the analysis of the technical characteristics of dual-power composite directional drilling in coal mines, structural bend angle of screw motor and rotary centrifugal force are treated equivalently. The dual-power composite directional drilling trajectory control model is established based on the quasi-dynamic principle to analyze the influence law of structural bend angle of screw motor, weight on bite and borehole diameter expansion rate on the trajectory control. The results show that increasing structural bend angle of screw motor is conducive to increasing the build-up rate of the sliding deflection, and is not conducive to the control of rotary angle holding trajectory. Increasing the weight on bit is not conducive to improving the build-up rate of the sliding deflection, and is conducive to the control of rotary angle holding trajectory. Increasing the expansion rate of borehole diameter is not conducive to improving the build-up rate of the sliding deflection, and has little effect on the control of rotary angle holding trajectory. Based on the analysis of the influence law of drilling trajectory control, a dual-power composite directional drilling trajectory control method is proposed, and different parameter setting suggestions are given. The structural bend angle of screw motor is generally 1.25°, and can be set to 1.5° when the drilling tool grade is large. In the context of the safety of the drilling tool, the weight on bit can be increased appropriately, and the weight on bit setting should not be too large when drilling in coal-measure strata with low consistent coefficient. The rotary speed is generally 40-60 r/min, the borehole diameter expansion rate is generally 4%-6%, and the proportion of rotary angle holding section is no less than 80%. The dual-power composite directional drilling trajectory control method is used in the test of super-deep directional long drilling for gas extraction above 3 000 m in the large area of Baode Coal Mine. The results show that the drilling efficiency is high, the drilling trajectory control capability is strong, which meet the requirements of efficient drilling in deep holes.
Research on regional anti-burst and pressure relief technology of roadway group affected by mining in thick and hard roof working face
DOU Guidong, JIA Zenglin, GAO Yonggang, ZHANG Ying
2021, 47(12): 32-38. doi: 10.13272/j.issn.1671-251x.2021060036
<Abstract>(74) <HTML> (5) <PDF>(5)
Abstract:
Under the impact of special geological and mining technology conditions, the roadway group area near the working face of the mine threatened by the rock-burst disasters is often in the high stress environment with a high impact risk. In order to solve the problem of roadway group regional anti-burst and pressure relief under the impact of mining in thick and hard roof working face, taking the 40309 working face of Shaanxi Binchang Xiaozhuang Mining Co., Ltd. as the engineering background, through on-site monitoring, the microseismic, ground sound and stress data at the end of working face mining are obtained. And the analysis show that the peripheral connecting roadway, chamber and central main roadway at the end of the working face are within the impact range of working face mining, and the impact risk continues to increase due to the impact of mining. The theoretical analysis shows that the reason for the impact risk of roadway group under the impact of mining in 40309 working face is the superposition and accumulation of concentrated dynamic and static loads in roadway group area under the condition of thick and hard roof. Aiming at different roadway areas of 40309 working face, the deep hole and ultra-deep hole roof presplitting blasting anti-burst pressure relief scheme is proposed, and the engineering practice and effect test are carried out. The results show that after adopting the anti-burst pressure relief scheme, the frequency and energy of microseisms in the 40309 working face and the nearby roadway group area are reduced by 55% and 60% respectively, the proportion of the c and d levels in the ground sound monitoring disaster level has decreased by 22.8%, the degree of regional stress concentration of the roadway group is significantly reduced, and the impact risk is significantly reduced. The working face and nearby chambers, connecting roadways and central roadways have no deformation and dynamic phenomena, and the anti-burst effect is good.
Application of CT inversion monitoring and early warning technology in microseismic anomaly area
LI Yunsheng, XU Desheng, MA Zhifeng, ZHOU Haijun, GUO Wenhao
2021, 47(12): 39-45. doi: 10.13272/j.issn.1671-251x.2021030074
<Abstract>(115) <HTML> (15) <PDF>(16)
Abstract:
In order to solve the problems that microseismic monitoring can only reflect the danger of the area where the microseisms are located, and CT inversion monitoring cannot reflect the current danger level of the working face in time, taking the 3105 working face of Dongshan Gucheng Coal Mine in Jining, Shandong as the engineering research background, a microseismic-stress multi-dimensional information monitoring and early warning method is proposed. The method combines short-term microseismic monitoring and medium and long term seismic wave CT inversion monitoring technology to identify the impact dangerous area of the working face. And the method combines the large-scale monitoring results based on medium and long term CT inversion, uses microseismic data around the working face to correct them so as to realize the real-time and dynamic monitoring and early warning of the medium and long term stress evolution of the working face and short-term microseismic accumulation. According to the abnormal situation of spatial and temporal distribution of microseismic events in August 2019 in 3105 working face for nearly one month, it is judged that the coal pillar area of the narrowing section in front of the working face is the abnormal stress area, and the CT inversion technology is adopted for dangerous area division and early warning. According to the results of CT inversion, the range of dangerous areas of strong and medium impact is given, and the high wave velocity impact dangerous area of 3105 working face is determined to be 100-200 m ahead of the material roadway and transportation roadway of the 3105 working face. According to the results of CT inversion, in accordance with the principle of zoning management, the corresponding pressure relief measures combining large diameter drilling of coal seam, coal blasting and deep hole blasting pressure relief are adopted for the high wave velocity impact dangerous area. The application results show that the seismic wave CT inversion technology can predict the corresponding relationship between high wave velocity and abnormal pressure area in two roadways accurately, predict the impact dangerous area effectively and can distinguish the danger level. After implementing pressure relief measures in dangerous areas with high wave velocity, the microseismic frequency and energy in the area are reduced effectively. The microseismic frequency and energy are reduced from 515, 12×105 J to 338, 5.98×105 J, are decreased 34.4% and 50.2% respectively. The pressure relief effect is obvious.
Experimental Research
Measurement and calculation method of attitude parameters of roadheader
GUO Lunfeng, GUO Yinan, JIANG Kangqing, GE Shirong
2021, 47(12): 46-54. doi: 10.13272/j.issn.1671-251x.2021070010
<Abstract>(154) <HTML> (8) <PDF>(25)
Abstract:
The current roadheader attitude parameter measurement method uses the output angle of the biaxial inclinometer directly as the pitch angle and roll angle of the roadheader. By analyzing the attitude parameter measurement of the roadheader and the measurement principle of the biaxial inclinometer, it is concluded that whether it is in a horizontal or inclined roadway, the pitch angle and roll angle cannot be measured by using the biaxial inclinometer alone. The biaxial inclinometer must be integrated with the positioning method containing the heading information of the roadheader to calculate the full attitude parameters of the roadheader simultaneously. Aiming at two typical driving conditions of horizontal roadway and inclined roadway, the attitude calculation method of combining sector laser and biaxial inclinometer (method 1) and the attitude calculation method of combining roadheader two-point coordinates and biaxial inclinometer (method 2) are proposed. In method 1, the yaw angle of the roadheader relative to the roadway coordinate system is determined in real time according to the spot position of the sector laser beam, and the pitch angle and the roll angle of the roadheader body relative to the roadway coordinate system are obtained by a biaxial inclinometer, so that the yaw angle, the pitch angle and the roll angle of the roadheader are calculated. In method 2, the three-dimensional coordinates of two points to be measured on the roadheader body in the roadway coordinate system are firstly measured, and then according to the principle of double-vector attitude determination, the attitude parameters of the roadheader are measured and calculated by using the biaxial inclinometer. The co-simulation results of Matlab and Gazebo show that in horizontal roadway and inclined roadway with four different inclination angles, the method of taking the output angle of biaxial inclinometer as the pitch angle and roll angle of roadheader directly has large errors, which can not meet the needs of attitude parameter measurement of roadheader. The errors of method 1 and method 2 are very small. The average maximum angle error in the horizontal roadway is 0.004 9°, and the average maximum angle error in the inclined roadway is 0.025°, which verifies the rationality of the two roadheader attitude calculation methods.
Method of cutting trajectory planning of roadheader based on hybrid IWO-PSO algorithm
TIAN Jie, YIN Xiaoqi, WEN Yicheng
2021, 47(12): 55-61. doi: 10.13272/j.issn.1671-251x.2021050018
<Abstract>(96) <HTML> (9) <PDF>(12)
Abstract:
In order to solve the problems of low accuracy and large loss of heading equipment in cutting trajectory planning method of roadheader, a cutting trajectory planning method of roadheader based on hybrid IWO (invasive weed optimization)-PSO (particle swarm optimization) algorithm is proposed. The cutting section environments are divided into three types, namely single gangue, double gangue and multi-gangue, and the corresponding sections are rasterized and the grid map is established. The irregular gangue is expanded by using binary expansion method. The hybrid IWO-PSO algorithm is used for trajectory planning in the three types of section environments. The hybrid IWO-PSO algorithm is based on the seed diffusion method in IWO algorithm, which diffuses the initial population and allows all individuals to reproduce freely before competitive exclusion, thus effectively ensuring the diversity of optimization space. The position iterative update method in PSO algorithm is also used to iteratively update the reproduced seed positions, and the particle positions are adjusted in time by using group experience and individual experience to improve the optimization depth and speed of the algorithm effectively. The simulation results show that the length of cutting trajectory, the number of secondary excavation grids and the cutting energy consumption of the roadheader based on the hybrid IWO-PSO algorithm are smaller than those of the standard PSO algorithm, and the capability to avoid the obstacle and gangue is better than that of the standard PSO algorithm. The section cutting test is carried out by EBZ135 roadheader, and the results show that the maximum errors of the left side, right side and both sides of the roadway section forming are 30, 20 and 50 mm respectively, and the relative error is within 2%, 1.4% and 1.7% respectively, which can meet the requirements of effective obstacle avoidance and forming under different roadway section environments.
Uplink rate enhancement algorithm for 5G network in intelligent mine
JIANG Jianfeng, CHEN Sihua, YOU Lantao
2021, 47(12): 62-67. doi: 10.13272/j.issn.1671-251x.2021080067
<Abstract>(79) <HTML> (3) <PDF>(14)
Abstract:
The 5G application scenarios such as remote control, high-definition video, unmanned mine car and unmanned aerial vehicle in intelligent mine put forward new requirements for the uplink rate of wireless network. However, the current 5G network uplink rate is insufficient, which leads to the limitation of intelligent mine business. And the existing 5G network uplink rate enhancement algorithm has limited range to improve the uplink rate. In order to solve the above problems, this paper proposes an uplink rate enhancement algorithm for 5G network in intelligent mine. By using supplementary upload technology, the spectrum resource aggregation is realized by overlaying Sub-3 GHz low band on the high band of C-Band, and the uplink rate of the network is improved by frequency domain resource allocation and time domain resource scheduling. In the middle-near point area, when the base station performs uplink data scheduling, the user equipment uses the 3.5 GHz frequency band to send uplink data in the uplink time slot of the C-Band frequency band, and uses the 1.8/2.1 GHz frequency band to send uplink data in the downlink time slot of the C-Band frequency band. In the far point area, the 3.5 GHz frequency band uplink is limited, and the user equipment only uses the 1.8/2.1 GHz frequency band to send uplink data. The test results show that the algorithm improves the mine near-point area, middle-point area and far-point area uplink rate by 17%, 41% and 213% respectively, and the average network uplink rate is significantly improved.
Research on heterogeneous clustering networking protocol in 3D open-pit mine scenario
ZHANG Hongguang, LIU Tingting, LYU Xiusha, ZHANG Ying, NIE Jianhong, LI Qing
2021, 47(12): 68-74. doi: 10.13272/j.issn.1671-251x.2021070067
<Abstract>(104) <HTML> (3) <PDF>(8)
Abstract:
Open-pit mine networking is one of the basic key technologies of intelligent mines. However, the complex communication environment in open-pit mines and the large mobility difference of various heterogeneous nodes lead to unstable communication links. In order to solve this problem, a heterogeneous clustering networking protocol (HCNP) is proposed. HCNP supports the access of static solar LoRa relay equipment at any time, and can be flexibly arranged with the change of mining depth. HCNP uses the shortest path tree to form a static backbone network from static devices and static relay devices to base stations. HCNP divides the priority according to whether the node moves, whether the energy is limited, the number of hops and the distance to the base station. The cluster head selection and clustering process are completed based on the different priorities of the node, and a heterogeneous networking mode of static backbone network and dynamic clustering is formed so as to realize the reliable forwarding of data. The simulation results show that compared with Ad hoc on-demand distance vector routing (AODV), optimized link state routing protocol (OLSR), greedy peripheral stateless routing protocol (GPSR), and node location-based 3D geographical routing protocol (AB3D), HCNP has higher successful transmission rate, lower end-to-end delay and lower energy consumption. When the simulation time and the number of nodes change, the successful transmission rate is always higher than 83%, the end-to-end delay is lower than 20 ms, and the energy consumption does not exceed 0.66 J. This shows that the static backbone network and the clustering strategy considering node priority are suitable for 3D open-pit mines with complex environment, and meet the requirements of dynamic adaptability of mine equipment and personnel number.
Coal block detection method integrating lightweight network and dual attention mechanism
YE Ou, DOU Xiaoyi, FU Yan, DENG Jun
2021, 47(12): 75-80. doi: 10.13272/j.issn.1671-251x.2021030075
<Abstract>(143) <HTML> (16) <PDF>(23)
Abstract:
In order to solve the problems of low detection precision and slow detection speed of existing coal block detection methods on belt conveyor in underground coal mine, an improved YOLOv4 model integrating lightweight network and dual attention mechanism is proposed, and it is applied to coal block detection of belt conveyor. The improved YOLOv4 model uses K-means clustering algorithm to re-cluster the prior frames, so that the prior frames are more suitable for the size of the detected target. The model improves the backbone network structure by introducing the MobileNet lightweight network model to reduce the amount of model parameters and calculations, and improve the detection speed. A convolution block attention module with dual attention mechanism is embedded to improve the sensitivity of the model to target characteristics, suppress interference information and improve the precision of target detection. The experimental results show that the improved YOLOv4 model can detect coal blocks of different sizes accurately. Compared with the YOLOv4 model, the improved YOLOv4 model weight file is reduced by 36.46%, the accuracy rate is increased by 2.16%, the recall rate is increased by 20.4%, the average accuracy is increased by 14.37%, the missed detection rate is decreased by 16%, the detection speed is increased by 19 frames/s, the processing time for a single image is reduced by 1.31 s, which improves the detection precision and speed of coal block detection.
Multi-motor synchronous control technology of mine belt conveyor
CHENG Guodong, WU Wei
2021, 47(12): 81-86. doi: 10.13272/j.issn.1671-251x.17831
<Abstract>(108) <HTML> (10) <PDF>(15)
Abstract:
When the mine long-distance belt conveyor adopts multi-point driving mode, the multi-motor synchronous control is adopted between the driving points at a long distance. Moreover, the multi-motor synchronous control strategy based on the traditional relative coupling control can not meet the synchronous requirements in the starting process when the rotational inertia of each motor is different, and the synchronous precision is not high when the steady state is disturbed. In order to solve the above problems, an improved relative coupling control method is proposed. A simple structured and easily implemented torque compensator is added on the basis of the traditional relative coupling control, the deviation between the actual rotating speed of each motor and the average rotating speed of all the motors is sent to a proportional controller for adjustment, and then the output result of the proportional controller is taken as a required torque compensation signal. In order to ensure the safe operation of the multi-motor drive system, the output torque of each motor after compensation is subjected to the same amplitude limiting. The simulation and experimental results show that the improved relative coupling control with torque compensator can realize the speed synchronization of multi-motors in the starting phase under different moments of inertia without affecting the dynamic response speed of the system. The proposed method ensures the system to have good anti-disturbance performance in steady state operation and high synchronization precision after disturbance.
Research on time-frequency characteristics of microseismic signal and precursory characteristics of rockburst in Gengcun Coal Mine
ZHANG Guohua, CHEN Dong, LIN Song
2021, 47(12): 87-92. doi: 10.13272/j.issn.1671-251x.2021080038
<Abstract>(90) <HTML> (6) <PDF>(14)
Abstract:
Based on the microseismic monitoring data, the time-frequency characteristics of the rockburst events induced by mining in 13200 working face of Gengcun Coal Mine of Henan Energy and Chemical Industry Group Co., Ltd. and microseismic events before the rockburst events are analyzed by using fast fourier transform, wavelet packet transform and Hilbert-Huang transform. The results show that the main frequency of rockburst is within 10 Hz, and the main frequency of the microseismic event waveform before rockburst is within 100 Hz. The highest energy distribution frequency band is within 5 when rockburst occurs. The highest energy distribution frequency band of the previous three microseismic events waveforms is about 10. The instantaneous energy of the six microseismic event waveforms before rockburst is not high, indicating that there is a silent period of energy before rockburst occurs. Based on the time-frequency characteristics of rockburst events and microseismic events before rockburst, the precursor characteristics of rockburst are obtained. The main frequency of the microseismic event waveform is within 100 Hz, the highest energy distribution frequency band is within 10, and the instantaneous energy is less than 1.5.
Near-infrared reflectance spectrum data preprocessing method for coal gangue identification
DING Zhen, CHANG Boshen
2021, 47(12): 93-97. doi: 10.13272/j.issn.1671-251x.17853
<Abstract>(231) <HTML> (41) <PDF>(24)
Abstract:
When using near-infrared reflectance spectrum to identify coal gangue, the change of detection distance between spectrum acquisition device and working face and dust interference will affect near-infrared reflectance spectrum. In order to select the best pre-processing method for near infrared reflectance spectrum for coal gangue, samples of anthracite and gangue with similar appearance are collected. A spectrum acquisition device consisting of near infrared spectrometer, collimator and halogen lamp is set up in the laboratory to acquire near infrared reflectance spectrum of coal gangue at different detection distances (1.2,1.5,1.8 m) and dust concentrations (200, 500, 800 mg/m3). Through the analysis of near-infrared reflectance spectrum characteristics of coal gangue, it is found that the detection distance and dust concentration change have no obvious impact on the waveform of near-infrared reflectance spectrum curve and the position of absorption valley of coal gangue. The absorption wavelength point of spectral characteristics will not be changed. However, the reflectance of near-infrared reflectance spectrum of coal gangue will be significantly affected. The spectral reflectance will decrease with the increase of detection distance and dust concentration, which will cause near-infrared reflectance spectrum drift of coal gangue. In order to enhance the absorption characteristics of near-infrared reflectance spectrum of coal gangue, the spectrum data are preprocessed by differential, standard normal variable transformation and polynomial smoothing methods. The preprocessed near-infrared reflectance spectrum data of coal gangue are input to the particle swarm optimization BP neural network model for coal gangue identification. The experimental results show that the differential preprocessing method has the best optimization effect on the near-infrared reflectance spectrum data of coal gangue collected under the change of detection distance and dust concentration, and can eliminate the impact of detection distance and dust concentration on the spectral reflectance effectively.
Inspection behavior detection of underground power distribution room based on conditional variational auto-encoder
DANG Weichao, SHI Yunlong, BAI Shangwang, GAO Gaimei, LIU Chunxia
2021, 47(12): 98-105. doi: 10.13272/j.issn.1671-251x.2021030087
<Abstract>(124) <HTML> (9) <PDF>(13)
Abstract:
The research focus of the existing inspection behavior detection methods in underground power distribution room is on the classification of video action. However, in practical application, for end-to-end video detection tasks, it is necessary not only to identify the category of inspection actions, but also to predict the start time and end time of inspection actions. Moreover, the existing research method based on supervised learning needs to label each frame of the video when training the network, so there are problems of complicated data set production and long training time. And the research method based on weakly supervised learning also relies on a video classification model, so it is difficult to distinguish the action frame and the background frame without video frame-level labeling. In order to solve the above problems, this paper proposes an inspection behavior detection model of weakly supervised underground power distribution room based on conditional variational auto-encoder. The model consists of two parts, namely discriminative attention model and generative attention model. The inspection behavior detection form of the underground power distribution room is divided into two tasks, namely classification and positioning of inspection action. Firstly, the RGB characteristics and light flow characteristics of the monitoring video of the underground power distribution room are extracted by using the characteristic extraction model. Secondly, the obtained RGB characteristics and the light flow characteristics are input into an attention module for training to obtain the attention of the characteristic frame. The soft classification is obtained by judging an attention model, and the action frame and background frame are distinguished according to the attention score. Finally, the output of the discriminative attention model is post-processed, and the output video contains the time interval, action label and confidence of the inspection action, that is, the classification and positioning of the inspection action are completed. In order to improve the precision of the positioning task, the generative attention model based on conditional variational auto-encoder is added, and the potential characteristics of the video are learned by using the generative confrontation between conditional variational auto-encoder and decoder. The inspection behavior is divided into standing detection, squatting detection, walking back and forth, standing record and sitting record by using the monitoring video of the underground power distribution room, and the inspection behavior data set is made for experiment. The result shows that the inspection behavior detection model based on the conditional variational auto-encoder can complete the inspection behavior classification and positioning tasks simultaneously. And the mAP@0.5 reaches 17.0% on the THUMOS14 data set, and the mAP@0.5 reaches 24.0% on the self-made inspection behavior data set, which meets the requirements for inspection behavior detection in underground power distribution rooms.
Research on fault diagnosis method of asynchronous motor based on Park-WPT and WOA-LSSVM
HUI Ali, LU Weiqiang, RONG Xiang, WEI Lipeng, CHEN Wenya
2021, 47(12): 106-113. doi: 10.13272/j.issn.1671-251x.2021070035
<Abstract>(162) <HTML> (25) <PDF>(18)
Abstract:
In order to solve the problems of poor precision and high cost of the existing motor multiple fault diagnosis technology, the rotor broken, air gap eccentricity and their mixed faults of asynchronous motor are studied based on three-phase stator current signals, and a fault diagnosis method of asynchronous motor based on Park-WPT (Park-wavelet packet transform) and WOA-LSVM (whale optimized algorithm-least squares support vector machine) is proposed. The collected three-phase current signals are preprocessed through Park vector transformation, the signal characteristics are extracted according to the distortion rate of the elliptical trajectory and the signal characteristics are taken as the first type characteristic quantity. The wavelet packet transformation is performed on the Park vector modulus square spectrum so as to obtain the energy value of its decomposition coefficient as the second type characteristic quantity. The mechanism of WOA's shrinkage surrounding prey and spiral updating prey position is used to optimize the regularization parameters and kernel width in LSSVM, and a fault diagnosis model based on WOA-LSSVM is established based on the extracted two types of characteristic signals. The experimental results show that the single characteristic extraction algorithm based on Park vector transform or wavelet packet transform has poor recognition effect on mixed faults, and the recognition rates of fault characteristics are 73.75% and 88.33% respectively. The recognition rate is improved to 97.08% by combining the two types of characteristics. WOA-LSSVM has a faster optimization speed and a higher fault diagnosis accuracy rate. Its overall performance is better than PSO (particle swarm optimization) algorithm, GWO (grey wolf optimization) algorithm and GA (genetic algorithm) optimized LSSVM.
Experience Exchange
Design and application of intelligent filling system for fully mechanized working face in extremely thin coal seam
ZHANG Zhaohai
2021, 47(12): 114-120. doi: 10.13272/j.issn.1671-251x.2021030091
<Abstract>(100) <HTML> (5) <PDF>(14)
Abstract:
At present, the filling technologies such as raw gangue and pneumatic pumping are usually used to fill the goaf of extremely thin coal seam, the design function of filling system is relatively single, and the linkage between multiple systems is lacking, so the intelligent separation of gangue and the continuous filling with the working face can not be realized. In order to solve the above problems, taking the 1901N fully mechanized working face of Great Wall Coal Mine of Ordos Xinkuang Group in Inner Mongolia Autonomous Region as the research background, the intelligent filling system of fully mechanized working face in extremely thin coal seam is designed. The system comprises a coal gangue intelligent separation and crushing and long-distance continuous transportation system, a continuous pumping filling system and a filling template support matched with the continuous pumping filling system. Firstly, the mined coal gangue is transported to a coal gangue intelligent separation and crushing system by a belt conveyor for separation, crushing and screening. Secondly, the coal gangue is transported to a mixer by a tubular belt conveyor for mixing to form concrete for filling. Finally, the coal gangue is transported to a filling port by a high-pressure pipeline for filling. Through the test, the best proportion of filling materials and the corresponding compressive strength standard value of each age are obtained, which are suitable for the fully mechanized working face of extremely thin coal seam in Great Wall Coal Mine. And the filling scheme is determined, which is mainly filled along the gob-side entry retaining and supplemented by the filling of the goaf behind the support. The field measurement results show that the system can simultaneously implement precise filling along the gob-side entry retaining and the goaf behind the support, improve the filling efficiency and the advancing speed of the filling surface, reduce the impact of dynamic load on the surrounding rock of the roadway, and control the deformation of the roadway effectively. The convergence of the two sides of the filling roadway and the maximum displacement of the roof and floor are 133.5 mm and 178.2 mm respectively, which are within the reasonable control range and meet the field application requirements.
Design of coal preparation data center platform based on Hadoop ecosystem
ZHAO Xin, WANG Ranfeng, FU Xiang
2021, 47(12): 121-127. doi: 10.13272/j.issn.1671-251x.2021040004
<Abstract>(103) <HTML> (15) <PDF>(13)
Abstract:
The existing coal preparation plant information management system uses nonstandard interface, which leads to repeated data collection, and each system is independent of each other, and the capability to process multi-source heterogeneous data is weak. In order to solve above problems, based on big data technology of Hadoop ecosystem, a coal preparation data center platform design scheme based on Hadoop ecosystem is proposed. The system integration is realized by defining data standards through master data management system and enterprise service bus. Normalization, correlation coefficient matrix and noise abnormal point detection programs are designed to realize data processing. DS (Dempster-Shafer) evidence theory, Hadoop and Hive data warehouse are combined to design multi-source heterogeneous data fusion subsystem to realize data fusion. Highcharts data visualization components are used to achieve interactive visualization of data. The practical application results show that the data center platform realizes the standardization of master data definition standard and system integration interface, improves the processing capability of coal preparation data, realizes the fusion and sharing of multi-source heterogeneous coal preparation data, and realizes the real-time interactive visualization of data.
Foreign object detection in coal mine belt transportation based on Fast_YOLOv3 algorithm
REN Guoqiang, HAN Hongyong, LI Chengjiang, YIN Yanfang
2021, 47(12): 128-133. doi: 10.13272/j.issn.1671-251x.2021030021
<Abstract>(245) <HTML> (38) <PDF>(18)
Abstract:
The existing foreign object detection methods in coal mine belt transportation are low in detection precision and slow in detection speed, and YOLOv3 algorithm has faster detection speed and higher detection precision. However, when it is used in foreign object detection in coal mine belt transportation, there are problems such as poor detection effect on small targets, easy to appear missing detection and imbalance of positive and negative samples. In order to solve the above problems, Fast_YOLOv3 algorithm is designed. By improving the priori box and bounding box, the algorithm is adapted to the detection scenario of small target foreign object in coal mine belt transportation. By adding the deconvolution network, the algorithm is able to improve the detection capability of small target foreign object. By introducing the Focal Loss to improve the cross entropy of the negative sample confidence in the loss function, the algorithm is able to solve the problem of imbalance in the number of positive and negative samples so as to improve the detection precision. The StiPic data enhancement method is designed to preprocess the coal belt transportation image to improve the training efficiency of the Fast_YOLOv3 model and the detection precision of small target foreign objects. The experimental and field test results show that the Fast_YOLOv3 algorithm can detect foreign objects in the belt transportation with an average precision of 90.12%, an average detection time of 35 ms, and a detection rate of 93.50% for small target foreign objects, which meets the requirements of foreign objects detection precision and real-time detection in the belt transportation field.
2021, 47(12): 134-136.
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