AUTHOR=Zhao Lijuan , Han Liguo , Zhang Haining , Ge Man , Yang Shijie , Jin Xin 

TITLE=Influence of particle characteristics on dynamic characteristics of tail beam under coal rock caving impact

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.976210

DOI=10.3389/fenrg.2022.976210

ISSN=2296-598X

ABSTRACT=In order to improve the accuracy of simulation parameters used in the discrete element simulation test of fully mechanized top coal caving process, further explore the intelligent fully mechanized coal caving technology, and study the influence of particle characteristics on the dynamic response of tail beam under the impact of caving coal rock in the process of coal caving. Based on the interface technology, the EDEM-RecurDyn-AMESim multi-domain collaborative simulation top coal caving support is built—model of hydraulic mechanical integration system for scraper conveyor, which is used to simulate the coal caving process of the top coal caving support, obtain the vibration signal of the tail beam of the top coal caving support, and convert it into a two-dimensional time spectrum image by STFT(Short-Time Fourier Transform)algorithm. Several groups of simulation tests were carried out for different particle radius (20mm,40mm,60mm), standard deviation of particle normal distribution (0,0.05,0.1)and particle slenderness ratio(1.0,1.5,2.0,N/A). The time-domain information and frequency-domain information were used to analyze and compare. Through the tail beam vibration signals measured in the underground field, the optimal setting parameters for multi-domain collaborative virtual prototype simulation were obtained, compared with the actual downhole site, the relative error of the maximum vibration value of the tail beam is only 3.8%, the minimum relative error is 5.5%, and the relative error of the root mean square value is 14%. The correctness of the method and simulation results is verified; The problems of difficult sampling in underground field, high risk coefficient and high test cost are solved, and the development of intelligent process of coal mine is promoted.