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Research And Implementation Of Intelligent Residual Coal Cleaning System For Dumper Gondola

Posted on:2022-02-21Degree:MasterType:Thesis
Country:ChinaCandidate:J C XiaoFull Text:PDF
GTID:2511306323486794Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
The sticky coal adhesion phenomenon of the coal gondola has brought many inconveniences to the production and transportation of coal mines,and has seriously affected the production and benefits of coal enterprises and coal-using enterprises.A safe,efficient,low-cost,real-time and intelligent method is sought to solve the problem of transportation.The sticking problem in unloading coal in gondola cars has become a key problem to be solved urgently in the coal transportation industry.At present,the main ways to deal with the residual coal residue problems in unloading coal from gondola cars at home and abroad are manual cleaning or vibrator cleaning.The former is time-consuming and labor-intensive,and the cleaning efficiency is very low;although the latter can be cleaned in real time,it is cleaned during cleaning.The noise is very loud,and the vibration force cannot be controlled in real time,which can easily cause damage to the coal carriage.Aiming at the problems in the cleaning of sticky coal,this topic studies a set of intelligent residual coal cleaning system using high-pressure water jet technology,which aims to realize the automatic and synchronous cleaning of coal unloading on gondola cars and improve the efficiency of coal unloading.The main research contents are as follows:In terms of the overall scheme design of the residual coal cleaning system,based on the analysis of the principle of the sticky coal remaining in the gondola car,the function and technical requirements of the residual coal cleaning system are determined,and the scheme design of the intelligent residual coal cleaning system for the gondola car is completed,Spray gun actuator motion control system,water supply control system,host computer monitoring system and human-computer interaction interface are composed of five parts.The intelligent residual coal cleaning system adopts a three-layer control structure based on the PROFINET communication protocol as a whole,which is simple to install,convenient to maintain,and the system has high accuracy,reliability and easy scalability.In view of the numerous control parameters of the high-pressure water jet cleaning method and the strong coupling between the parameters,the parameters involved in the high-pressure water jet cleaning process are analyzed.The Fluent simulation is used to perform numerical simulation analysis on the cleaning process parameters,and the simulation numerical simulation is performed using experiments.The results are verified,and the relationship between the cleaning nozzle diameter,jet pressure and jet impact force,jet cleaning width,and jet cleaning distance is obtained,which can provide the best design variables for multi-objective parameter optimization of the cleaning process of the gondola car residual coal cleaning system Value range.Using Fluent simulation numerical simulation to match the remaining coal cleaning process parameters can not achieve the purpose of cleaning process parameter optimization.Therefore,the comprehensive application of Latin hypercube sampling design,particle swarm-improved BP neural network proxy model technology,and multi-objective optimization method are used to optimize the cleaning process parameters.The design parameters involved in the coal cleaning system are optimized to obtain the design variables under the best cleaning effect of the residual coal cleaning system,and the optimized design variable parameters are used to fit the relationship between cleaning time and cleaning efficiency to optimize the resulting design The parameters provide guidance for the realization of the residual coal cleaning system.Based on the use of multi-objective optimization and experimental fitting to obtain the best design parameters of the residual coal cleaning system,the intelligent residual coal cleaning system of the gondola car tipper is realized,and the Siemens S7-1200 PLC is used as the main controller to control the system as a whole.Control the motor speed of the high-pressure variable-frequency pump by controlling the frequency of the inverter,so as to realize the control of the pressure,flow and electric power consumption of the high-pressure variable-frequency pump;by controlling the servo motor of the spray gun actuator to realize the cleaning of the residual coal in the compartment,Use the laser radar sensor to detect the thickness of the residual coal sticking in the compartment,and for the difficult-to-clean parts,the motor can be controlled to make the spray gun stay for a short time.For the places with relatively little residual coal sticking,the spray gun moving speed can be speeded up,the cleaning time can be reduced,and the residual coal can be realized.Efficient and intelligent cleaning of the cleaning system.For the design of the host computer monitoring system,use Botu software to develop its interface.The host computer interface has functions such as residual coal sticking information monitoring,high-pressure variable frequency pump and inverter operation monitoring,motion control system monitoring and parameter setting and display;In addition,the Siemens KTP1000 Basic series panel is used as the touch screen for on-site human-computer interaction.Finally,the various components of the intelligent residual coal cleaning system are debugged and tested.The whole system is used for the residual coal cleaning of the unloading coal of the gondola car in Rizhao Port,Shandong.The results show that the intelligent residual coal cleaning system can automatically identify the residual coal sticky coal in the carriage and treat it.Performed efficient and intelligent cleaning,completed the entire system test and achieved good results.
Keywords/Search Tags:Clean-up of residual coal in gondola car, Numerical simulation, Constrained multi-objective optimization, Control system design
PDF Full Text Request
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