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- Online First 2023, Volume 49, Issue 8 Cover Catalogue Previous Issue
Online First have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
2023, 49(8): 1-8.
doi: 10.13272/j.issn.1671-251x.18147
Abstract: In order to meet the needs of remote monitoring, video monitoring, data acquisition, and voice communication in coal mines, the 5G communication system used in coal mines should have the following functions. ① The system has different service-bearing functions such as remote control, monitoring, positioning, surveillance, and voice. ② The system has remote control functions such as coal mining machines, roadheaders, electric shovels, excavators, trackless rubber wheeled vehicles, and electric locomotives. ③ The system has an emergency remote takeover function for mining transportation vehicles. ④ The system has a remote real-time transmission function of camera audio and video. ⑤ The system has data collection functions such as monitoring equipment, sensors, and vehicle-assisted driving. ⑥ The system has a voice call function. ⑦ The system has an end-to-end slicing function that meets the differentiated business performance requirements of remote control, monitoring, video, and voice. ⑧ The system supports SA networking and 5G NR communication system. ⑨ The system supports 5G LAN Ethernet communication. ⑩ The system has an emergency inertia operation function. In case of disconnection between the mining area's private network and the communication operator's public network, local businesses can continue to operate online. ⑪ The system has a device level redundancy protection function that ensures uninterrupted data service in the event of a single physical port failure. ⑫ The system has a dual device redundancy protection function of the core network that allows for the switching of backup devices to continue providing services when the main device fails. ⑬ The system has the core network control surface transmits confidentiality and integrity protection functions to ensure the security of the core network control surface. ⑭ The system has terminal authentication, checking, and restricting access to unauthorized terminals in the system, supporting the authentication of terminals by coal mining enterprise security servers. ⑮ The system has functions that prevent terminal attacks on the system and legitimate terminal. ⑯ The system has the integrated management function of the core network, transmission equipment, base station controller, base station, and terminal. ⑰ The system has a centralized monitoring function for network performance and business service performance. ⑱ The system has an abnormal visual alarm and fault location function. ⑲ The system has the evaluation function of mining 5G network resources. The system can evaluate the utilization rate of 5G network resources and provide a report on whether new services can be accessed when the coal mine adds new services or more terminals are connected to the 5G network. ⑳ The system has backup power supply. The main technical indicators of the 5G communication system used in coal mines should meet the following requirements. ① When the uplink rate is 20 Mbit/s and the wireless working frequency band is 700-900 MHz, the wireless coverage radius (unobstructed) of the base station in the underground coal mine should be ≥ 500 meters. When the wireless working frequency band is other working frequency bands, the wireless coverage radius (unobstructed) of the base station in the underground coal mine is ≥ 150 m. When the uplink rate is 30 Mbit/s, the wireless coverage radius (unobstructed) of the base station in the open-pit coal mine is ≥ 400 m. ② The wired transmission distance from the base station to the base station controller is ≥ 10 km. ③ The maximum number of access terminals in the system is ≥ 20000. ④ The wireless transmission power of the base station and terminal of the underground coal mine is ≤ 6 W. The transmission power of the base station in the open-pit coal mine is ≤ 320 W. The wireless transmission power of the terminal in the open-pit coal mine is ≤ 6 W. ⑤ The base station wireless reception sensitivity is ≤ −95 dBm. The terminal wireless reception sensitivity is ≤ −85 dBm. ⑥ The wireless working frequency should be selected from the frequency bands of 700 MHz, 800 MHz, 900 MHz, 1.9/2.1 GHz, 2.6 GHz, 3.3 GHz, 3.5 GHz, 4.9 GHz, 6 GHz, etc. (preferably 700 to 900 MHz for underground coal mine). ⑦ When the format is TDD and the frame structure is 1D3U1S, the average uplink throughput rate of multiple users accessed by the base station is ≥ 600 Mbit/s, and the average downlink throughput rate is ≥ 250 Mbit/s. ⑧ For underground coal mines, when operating upstream services at 1 Mbit/s and 20 Mbit/s, the average system delay should be less than 20 ms, and the probability of end-to-end delay stability being less than 100 ms should not be less than 99.99%. For open-pit coal mines, when operating upstream services at 1 Mbit/s and 30 Mbit/s, the average system delay should be less than 20 ms, and the probability of end-to-end delay stability being less than 100 ms should not be less than 99.9%. ⑨ The packet loss rate of a single user is ≤ 0.01%. ⑩ The handover delay for a single user from cell A of the base station to cell B of the base station is ≤ 100 ms. ⑪ The continuous working time of the mobile station battery should not be less than 11 hours, among which the call time should not be less than 2 hours. ⑫ After a power outage in the power grid, the backup power supply continuously provides power to the base station, base station controller, and transmission equipment for ≥ 4 hours.
2023, 49(8): 9-19.
doi: 10.13272/j.issn.1671-251x.2023050063
Abstract: Currently, the fault warning technology for the cutting part of cantilever roadheader relies on traditional data collection methods. In the operation process of the cutting part of the roadheader, problems such as difficulty in obtaining signals and high noise limit the capability to predict and warn faults in the cutting part of the roadheader. In order to solve the above problems, a fault warning method for the cutting part of cantilever roadheader based on virtual and real fusion data is proposed. The method performs three-dimensional solid modeling of the cutting section of a cantilever roadheader. It uses the automatic dynamic analysis of mechanical systems (ADAMS) to obtain virtual data of the cutting section's mechanical system, constructs its dynamic simulation model to obtain virtual data. The method uses the cosine similarity function to characterize its similarity with real data to verify the credibility of the virtual data. The method uses Bayesian estimation and adaptive complementary weighted fusion methods to perform similarity association and complementary association fusion on virtual and real data, respectively, to obtain virtual and real fusion data. In response to the problem that the learning efficiency of traditional self-organizing mapping (SOM) neural networks is easily affected by the learning rate, a fault warning model based on an improved SOM neural network is established. A monotonic decreasing function about time is introduced to train the SOM neural network, ensuring both the learning rate and the stability of the model. The method inputs the fused data into the fault warning model based on SOM neural network to determine the winning neuron and adjust its weight. The method calculates the distance between the real data and the winning neuron and adjusts its weight to achieve fault warning. The experimental results show that the average operating efficiency of the improved SOM neural network can be improved by 35.84%. The fault warning method for the cutting part of a cantilever roadheader based on virtual and real fusion data can successfully predict the types of single and composite faults, with a prediction accuracy of 83.33%.
2023, 49(8): 20-29.
doi: 10.13272/j.issn.1671-251x.2023050099
Abstract: As an efficient means of geophysical exploration, mine DC electrical method plays an important role in accurately circling various types of anomalous zones. The development of underground detection is limited by many factors due to small space, interference and high technological requirements. Therefore, it is significant to establish a mine DC electrical method technology system that matches the intelligent mine production under the rapid extraction mode. The paper gives an overview of mine DC electrical method from three aspects, namely, basic principle, technology development and classification. It summarizes the latest progress of mine DC electrical method used in roof and floor exploration, roadway advance detection, and anomaly area exploration in the working face, etc. It analyzes the progress of the research and development of mine DC electrical method instruments and equipment. It enumerates several common types of mine DC electrical method instruments. It analyzes the key problems of mine DC electrical method in solving the engineering problems. ① The current mine DC electrical method advance detection technology has low positioning precision in the circled space of water-bearing/conducting anomalies. At the same time, there is the problem of insufficient effective detection distance. ② The construction space of mine DC electrical method is narrow, and the electrical response of multi-directional geological anomalies is superimposed in the limited testing space. It increases the difficulty of data processing and interpretation. ③ The mine DC electrical method is susceptible to interference from metal sources at the site when applied underground, especially by large metal parts such as roadheaders, hydraulic supports, anchor locks (nets) supports, rails, and conveying pipelines. The future development direction of the mine DC electrical method is prospected. ① It is suggested to construct a multi-source geoelectric field data response feature library. ② It is suggested to obtain interpretation of multi-source data fusion. ③ It is suggested to establish the intelligent monitoring system of mine DC electrical method.
2023, 49(8): 30-36.
doi: 10.13272/j.issn.1671-251x.2023060031
Abstract: With the continuous promotion of the construction of unmanned automated fully intelligent mechanized working faces, higher technical requirements have been put forward for the automation control function of the hydraulic support electrohydraulic control system. The electrohydraulic control technology developed in China has problems such as low communication speed, delayed response, and poor reliability in meeting the requirements of intelligent production technology. An end controller for the electrohydraulic control system of hydraulic support based on a 32-bit processor has been developed. A communication architecture of the end controller based on industrial Ethernet and CAN bus has been designed. According to the technical requirements of intelligent perception, intelligent decision-making, and automatic control for unmanned intelligent mechanized working faces, parameter inspection, parameter modification, online upgrade, and control functions of automatic follow-up have been designed in the end controller. In order to meet the requirements of standardization and normalization of data in the hydraulic support electrohydraulic control system in intelligent fully mechanized working faces, the end controller can encode the data generated by the hydraulic support electrohydraulic control system according to the data encoding standard based on tag numbers. Through the experiment on the "three machines" experimental platform of fully mechanized working faces, the results show the following points. The entire process from issuing inspection instructions to receiving data from 27 support controllers on the experimental platform takes 1.8 s for the end controller. It is 1.5 s faster than using RS485 communication to achieve parameter inspection. The size of the upgrade program sent by the end controller is 38 KiB and the transmission time is 1.2 s. After testing, it takes 4-6 s for all support controllers in the fully mechanized working face to receive the upgrade command and successfully upgrade together, achieving the expected goal. The end controller can control the corresponding hydraulic support to make correct actions based on the position of the shearer. It can meet real-time requirements.
2023, 49(8): 37-52, 80.
doi: 10.13272/j.issn.1671-251x.2023010003
Abstract: Scraper conveyor is the core transportation equipment of the fully mechanized working face. Accurately perceiving its form is an important prerequisite to enhance its carrying capacity, alleviate the transmission impact, and improve the straightness of fully mechanized working face. The commonly used indirect measurement methods for the shape of scraper conveyors are difficult to accurately characterize their shape, resulting in significant measurement model errors. To address this issue, an inertial measurement unit is used to directly measure the original pose information of the middle trough of scraper conveyor, achieving accurate acquisition of the shape data of scraper conveyor. A wavelet thresholding denoising method that combines Heursure threshold rules and a new threshold function is used to filter out noise interference in the acceleration signal of the middle trough. Based on this, the motion features of the middle trough are analyzed, and a middle trough motion state recognition model based on random forest algorithm is designed. Based on the motion state recognition results, different strategies are used to update the position of the middle trough. It reduces the accumulated IMU data error over time and improves the precision of IMU position calculation. The improved Harris hawk optimization (HHO) algorithm unscented Kalman filter (UKF) is designed for middle trough attitude calculation. It is verified through experiments that the attitude angle calculated by this method meets the requirements of middle trough attitude measurement. The experimental platform for shape monitoring of scraper conveyors is constructed. It conducts experimental verification on the shape calculation method of scraper conveyors based on motion state recognition and improved HHO optimized UKF. The results show that when the scraper conveyor performs a single sliding with a step distance of 250 mm, the maximum cumulative errors of displacement in the X and Y directions of the scraper conveyor composed of 10 middle troughs are 6.4 mm and 8.4 mm respectively under the horizontal working condition of bottom plate. It remains unchanged in the Z direction. The maximum cumulative errors of pitch angle, roll angle, and heading angle are −0.148°, −0.035°, and 0.457° respectively. Under the working condition of floor undulation, the maximum cumulative errors of displacement in the X, Y, and Z directions are 6.6 mm, 11.5 mm, and 6.9 mm respectively. The maximum cumulative errors of pitch angle, roll angle, and heading angle are −0.540°, −0.157°, and 0.817° respectively. This method can effectively suppress cumulative errors, reduce measurement errors, and achieve accurate perception of the shape of the scraper conveyor.
2023, 49(8): 53-59.
doi: 10.13272/j.issn.1671-251x.2022120027
Abstract: Path planning is one of the important contents of research on coal mine rescue robots. A path planning method for coal mine rescue robots based on improved A* algorithm is proposed to address the unstructured features of post disaster coal mine environments and the problems of non-shortest path length, multiple turns, and poor smoothness of path planned by traditional A* algorithm. The method constructs raster maps by binarizing map information in real environments, determines the relative position between the current point and the target point, and uses the improved A* algorithm for path planning. Then a path from the current point to the target point is obtained. Douglas-Pucker (D-P) algorithm is used to extract key nodes on the path, and cubic spline interpolation function is used to fit the key nodes, thereby completing the smooth processing of the path. The improved A* algorithm expands the traditional A* algorithm's 8 neighborhood search to a purposeful 13 neighborhood search. When conducting path search, the position relationship between the current point and the target point is first determined, thereby reducing path nodes and length, and improving path smoothness. The Matlab simulation results show that compared with the 8 neighborhood A* algorithm, 24 neighborhood A* algorithm, and 48 neighborhood A* algorithm, the improved A* algorithm has certain optimizations in path length, number of turns and smoothness. It is more suitable for path planning of coal mine rescue robots. Compared with the Fuzzy algorithm, the improved A* algorithm achieve shorter path planning time, shorter planned path length, and fewer turns.
2023, 49(8): 60-69.
doi: 10.13272/j.issn.1671-251x.2022120067
Abstract: The loose cooperative group robot system has broad application prospects in the current coal mine auxiliary robot operation. However, the task assignment process of the loose cooperative group robot system did not provide feedback to the division process, resulting in insufficient efficiency and rationality of the task division and assignment process. To address this issue, an efficient task assignment algorithm for coal mine underground group robots based on an improved Rubinstein negotiation strategy is proposed. Based on the multi-party game features of task division and assignment in group robot systems, the Rubinstein negotiation strategy is extended from a bipartite game to a multi-party joint game. A "bid-bargain-counteroffer" rule for multi-party negotiation games is proposed. From the perspective of the difference between the execution capability and task execution status of individual robots, a discount factor calculation method based on the task completion quantity per unit time of robot individuals is proposed. A task completion status feedback parameter model based on the task execution status of each assignment cycle is also proposed to achieve dynamic task division and assignment. By collaborating with three groups of robots to perform overall monitoring tasks in coal mining areas, experimental verification is conducted on the performance of the algorithm. The results show the following points. ① Algorithm 3 uses an improved Rubinstein negotiation strategy. Algorithm 1 directly uses the ratio of the number of unmanned aerial vehicles in each group multiplied by their running speed as the standard for task division and assignment in three groups of unmanned aerial vehicles. Algorithm 2 uses the Rubinstein negotiation strategy of multi-party negotiation without considering the feedback parameters of task completion status. Algorithm 3 has a higher efficiency in task division and assignment than Algorithm 1 and Algorithm 2 by 30.10% and 18.29% respectively. ② The average maximum time difference for the three groups of unmanned aerial vehicles based on Algorithm 3 to execute tasks is 42 seconds. It is 77.66% and 65.29% optimized compared to Algorithm 1 and Algorithm 2, respectively. This is because Algorithm 3 introduces task completion status feedback parameters to timely evaluate the task execution process of the task participants. Algorithm 3 provides feedback on the task assignment and execution process to the task division stages, making the task division and assignment more accurate.
2023, 49(8): 70-80.
doi: 10.13272/j.issn.1671-251x.2023020010
Abstract: Unmanned driving technology has enormous advantages in improving efficiency, saving costs and reducing safety hazards. In the current implementation of localization and navigation solutions in underground environments, there are problems of implementation difficulties, high costs, and time-consuming construction of maps. In order to solve the above problems, a localization and navigation method for underground mine autonomous driving based on local geometric topology map is proposed. A local geometric topology map has been designed. The main structure of the underground environment road network is represented by a topology map. The map defines roadways (sides) and intersections (nodes), and stores a local geometric map built around the node in each node to achieve precise positioning at the node. A localization method based on local geometric topology map is proposed, which uses a LiDAR-based intersection detection algorithm and intersection localization algorithm for global vehicle localization. A trajectory-following algorithm based on adaptive model predictive control (MPC) has been designed to ensure the path-tracking precision of vehicles turning at high curvature intersections. A simulation environment and vehicle simulation model for underground mines are constructed by using a 3D physical simulation platform. The simulation results show that this method can achieve underground mine autonomous driving localization and navigation functions. The positioning errors are within 0.2 m at various types of intersections, meeting the positioning localization precision requirements of autonomous driving. Throughout the entire driving process, the vehicle maintains a relatively stable driving state and a small tracking error. Compared with the current localization and navigation methods that rely on technologies such as 5G and UWB, this method only relies on two types of vehicle sensors: LiDAR and inertial measurement unit. It has great advantages in controlling equipment costs.
