Study On The Alignment Method Of Scraper Conveyor Based On Fiber Bragg Grating Sensing In Intelligent Working Face

In this thesis,the alignment method of the scraper conveyor on intelligent working face is taken as the research object.Based on the analysis of the attitude model of the scraper conveyor,the real-time attitude perception of the scraper conveyor is realized through the running track of the scraper conveyor sensed by the FBG curvature sensor.Aiming at the alignment problem of scraper conveyer on working face,a alignment method of scraper conveyer based on FBG curvature sensor is proposed.The main research contents of this thesis include:(1)Analyze the structure composition and working principle of the scraper conveyor,establish the attitude model of the scraper conveyor,and analyze the attitude model.This thesis introduces the perception principle of FBG curvature sensor,combines with the attitude perception model of scraper conveyor,and uses FBG curvature sensor to sense the attitude and position information of scraper conveyor in real time,so as to improve the accuracy and efficiency of the perception of scraper conveyor attitude.(2)The alignment scheme of scraper conveyor is proposed.The alignment method based on scraper conveyor is selected,which includes two aspects: firstly,the current track of scraper conveyor is sensed by FBG curvature sensor,and then the track of scraper conveyor is adjusted according to the alignment algorithm.A alignment prediction model of scraper conveyor based on LSTM neural network algorithm is proposed,which combines the real-time perception and prediction of scraper conveyor attitude effectively,and improves the alignment accuracy of scraper conveyor.During the alignment process of scraper conveyor,in order to verify the alignment effect of scraper conveyor,it is necessary to adjust the track after the current alignment in time.The method of evaluating straightness error is analyzed,and the criterion of evaluating the alignment error of scraper conveyor is introduced.MSE is selected as the evaluation index of the alignment effect of scraper conveyor.(3)Verify the alignment method of scraper conveyor proposed in this thesis based on FBG curvature sensor perception,and choose MATLAB environment for numerical simulation.Under the condition of considering the influence of error,the average error of the straightness of the scraper conveyor after straightening is 27.96 mm when the scraper conveyor is pushed for 50 consecutive times according to the alignment algorithm.LSTM neural network algorithm is used to predict the alignment algorithm track of the scraper conveyor.The predicted alignment track of the scraper conveyor can provide reference for the alignment of the next cutter scraper conveyor and ensure that the straightness of the scraper conveyor meets the requirements of the working face.(4)The alignment experiment platform of the scraper conveyor was built,and the push experiment was carried out on the scraper conveyor model.According to the alignment experiment results,the rationality of the alignment method of the scraper conveyor proposed in this thesis was verified.The error of scraper conveyer in straightening process is analyzed.According to the alignment method of scraper conveyor proposed in this thesis,a alignment system of scraper conveyor is designed,and the feasibility analysis is carried out on the No.12307 working face.There are 48 figures,9 tables and 88 references in this thesis.