Robot Detection And Assessment And Autonomous Risk Avoidance In Gas Environment Of Coal Mine

Coal mine robots have been part of the safety infrastructure of coal mines.However,the status of gas environment in coal mine is unknown.It is difficult to judge the safety of gas environment in coal mine,because the correlation and influence relationship between collected gas environmental parameters are not reflected.Most of the driving units of coal mine robots adopt the form of explosion isolation.In order to prevent the explosion of gas and coal dust caused by the mine robot in the case of failure or tumbling collision,Coal mine robots cannot enter the dangerous gas area,especially the environment of zone 0.Therefore,the premise for the coal mine robot to enter the mine to perform detection and rescue tasks is to study the detection,safety assessment and self avoiding risk in gas environment of coal mine,and this has important theoretical and practical significance.In this paper,the detection of underground gas environment,safety assessment and robot autonomous risk avoidance are studied.The main contents are as follows:(1)The gas environment in coal mine is analyzed.Including gas characteristics,gas state,source and movement form.Geometric models of straight roadway,curved roadway,crossing roadway and inclined roadway are established based on the actual coal mine.The numerical analysis method is used to simulate the distribution of multi-component gases such as gas and CO under different conditions of emission,tunnel type and wind speed.The reliability of numerical simulation of gas environment is verified by comparing the gas data measured at various positions in the coal mine roadway with the simulation results.It provides the basis and direction for the design of the gas environment detection system,the location and number of gas sensors arranged on the coal mine robot,the path planning and motion decision-making of the coal mine robot and so on.(2)The detection and data processing of underground gas environment are studied.The detection system of gas environment is designed from the aspects of hardware and software,and the main functions are tested.Time series fusion algorithm is used to improve the accuracy of the original data of the sensor,and fuzzy reasoning data fusion algorithm is used to obtain the accurate gas information of the current position of the robot by data fusion of multiple gas sensors.The simulation and experimental results show that fuzzy reasoning data fusion method of multi-gas sensor can correctly judge the gas state of the robot at the current position,which provides a basis for the autonomous risk avoidance of coal mine robot.(3)A safety assessment method for gas environment of coal mine based on FCE-ANP was proposed.ANP is integrated into FCE for the safety assessment of gas environment in coal mine,and an index system of coal mine gas environment safety assessment is established.The index system of coal mine gas environmental safety assessment is established,the reasonable quantitative index and the correlation between the index factors are given.The safety assessment model of gas environment in coal mine is constructed.The safety assessment of gas environment is verified by practical data measured in coal mine,the results show that the proposed method and the safety assessment model are reasonable and effective,which has important guiding significance for the direction and path planning of coal mine robot.(4)An active avoidance algorithm for robot based on velocity decomposition method is proposed.SOA-PID speed controller of robot is designed to make the robot have good motion response when avoiding danger.The autonomous avoidance algorithm is integrated into the path planning algorithm to adjust the local path of the robot.The simulation results show that the robot path obtained by combining the algorithm of risk avoidance with Dijkstra algorithm can avoid risk,and the total length of the path obtained by Dijkstra algorithm is 11.66 m shorter than that obtained by Dijkstra algorithm,which saves a lot of time for coal mine robot.When there is a sudden change in environmental information,the robot can quickly adjust the path by adjusting the local path of the robot.(5)Experiments and applications are carried out.Autonomous hazard avoidance experiments of robot are carried out in laboratory gas environment and relatively closed simulated tunnel gas environment respectively.The distribution and concentration of the dangerous gas in the process of avoiding danger can be obtained by the curve of the output voltage of the gas sensor changing with time.The range of signal output of gas sensor is very small,which proves the validity of the speed control method of SOA-PID.Then the gas environment detection,safety assessment and robot autonomous risk avoidance are applied to the coal mine robot,and the autonomous risk avoidance test of coal mine robots is carried out in the gas and coal dust explosion test site.The experimental results show that the coal mine robot can detect the gas environment at the current position in real time and give the results of data fusion and safety assessment.Coal mine detection robot can avoid obstacles and dangerous gas area,and the self-avoiding algorithm proposed can realize local path adjustment and self-avoiding when the dangerous gas area changes.The research results of this paper will improve the intelligence of coal mine robot,improve the efficiency and safety of the robot,and effectively avoid disasters and accidents.