Wear Characteristics And Prediction Of Scraper Conveyor Chute Under Multi-factor Coupling

The chute is the key component of the scraper conveyor.Its performance is directly related to the working reliability and service life of the scraper conveyor.In recent years,the tribological problems of the chute were mostly analyzed from the single factor point of view.However,the operation condition of the middle plate of scraper conveyor is complex,and there are many factors affecting the wear loss,so it is necessary to study the influence of multi-factor coupling.In the process of transportation,the chute bears the friction and impact from coal,gangue,scraper chain and scraper.The process of wear is restricted by many factors such as coal bulk,material and working condition.Serious wear failure and fracture are easy to cause malignant accidents.Therefore,it is of great significance to study the wear characteristics of the middle plate under the multi-factor coupling effect and predict the wear loss of the chute for selecting materials according to local conditions,ensuring the safe production of the coal mine and improving the economic and social benefits.Aiming at the wear problem of the chute,the wear law and wear mechanism of the middle groove under multi-factor coupling were studied by new designed wear test;the wear of the chute was studied by discrete element simulation,and the simulation parameters of different moisture content coal bulk material were calibrated by Micro-parameter calibration method,and the variation law of parameters was studied;based on the calibration results,wear model was established by using Recur Dyn and EDEM coupling.The simulation model studied the influence of coal physical properties on the wear of the chute;established the discrete element wear model of scraper conveyor to study the influence of mine environment on the wear;finally,based on the wear test data,combinedmachine learning algorithm to predict the wear loss of the chute.The main research results of this paper are as follows:(1)Aiming at the wear form of the chute,a wear tester was designed and manufactured.On the basis of traditional pin-on-disc wear tester,the upper sample simulated scraper operation and was machined into oblique angle form.The lower sample simulated middle plate operation and was machined into circular arc and fixed on the surface of the trough.The trough filled with coal bulk material rotated to simulate the movement of bulk material driven by the motor.(2)Aiming at the wear test of the chute under the influence of many factors,through Plackett-Burman test,the significant factors was screened out: water content,gangue content,normal load.Combined with the central composite design(CCD),the coupling effect between the significant factors was studied,which showed that the coupling effect of water content and gangue content,water content and sliding distance would aggravate the wear of the chute.And The regression prediction model of wear loss was obtained.(3)The wear condition of the middle plate with different hardness under different working conditions was studied.It showed that the wear would be effectively improved by increasing the hardness of middle under the condition of high water content and gangue content.Based on the interaction test of various factors,the improved Archard wear prediction empirical model was obtained.Compared with the traditional Archard model,the prediction accuracy is higher.(4)Measure and calibrate the Micro-Parameters of DEM for wet coal bulk.The test results showed that with the increase of water content of coal particles,the recovery coefficient of Coal-Coal and Coal-Steel decreased gradually,and the static friction coefficient of Coal-Steel increases gradually.The calibration experiment resulted show that the significant factors affecting the accumulation angle of wet materials were Coal-Coal surface energy,Coal-Coal rolling friction coefficient and Coal-Coal static friction coefficient,while the influence of Coal-steel rolling friction coefficient could be neglected.(5)According to the physical properties of coal,the DEM simulation showed that the wear depth is positively correlated with Poisson's ratio,shear modulus and density.(6)According to the research of wear prediction for the chute,the model built by machine learning algorithm GS-SVM had higher prediction accuracy.