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Research On Slag Removal Device And Control System Of Biomass Pellet Fuel Hot Water Furnace

Posted on:2024-07-25Degree:MasterType:Thesis
Country:ChinaCandidate:C J GaoFull Text:PDF
GTID:2542307160462614Subject:Agriculture
Abstract/Summary:PDF Full Text Request
In order to alleviate the pressure of the use of traditional energy materials,reduce the shortage of traditional energy and environmental pollution,promoting the development of biomass energy is an effective solution at present.Our country is a big agricultural country,the agricultural conditions are good,many crop varieties,wide distribution,output is large,is the main source of new biomass energy materials.With the mass use of biomass energy,although it solves the problem of traditional energy shortage and reduces the emission of pollutants,the slagging problem of biomass is prominent in the combustion process.Therefore,this paper designs the slag removal device and its control system of biomass pellet fuel hot water furnace.Firstly,peanut shell molding particles are selected as fuel and biomass pellet fuel hot water furnace is selected as the research object.According to the actual combustion conditions and the shortcomings of the current combustion hot water furnace,a mechanical slag removal device and its control system are designed.The length of the crank and the length of the connecting rod are obtained by kinematic analysis.In addition,the mechanical slag removal device is driven to work by the rotation of the motor,so it is necessary to select the type of the motor.Through calculation,the motor model is finally determined as ZSM65-120-3R.The construction of the control system is mainly divided into two parts.The first part is the hardware part,including the camera,51 microcontroller and the total controller.The second part is the software part,including the motor control model,ShuffleNet model.Secondly,in order to achieve the best slag removal effect,the slag removal is divided into two steps,the first step is to solve the slag problem from the source of the material by adding the slag removal additives,the second step is to add the slag removal additives on the basis of mechanical slag removal device for slag removal.In the experimental stage of additive slagging,the combustion modes are divided into large fire mode and small fire mode.Elemental analysis and ash composition analysis are carried out on the biomass ash samples burned by different combustion modes and adding slagging additives,and the slag discrimination index is used to analyze the slag removal results.The results show that: Under the two combustion modes,according to the fouling index,iron-calcium ratio,alkali-acid ratio,silicon ratio and silica-aluminum ratio,the slagging degree of the five evaluation indexes is 3 medium and 2 slight in the fire mode,and 2 medium and 3 slight in the small fire mode.Therefore,the slag removal effect of kaolin additive added alone is the best.It is obviously better than the slag removal effect of adding Mg O additive alone,Ca O additive or mixed kaolin: Mg O: Ca O ratio of 1:1:1,1:1:2,1:2:1,2:1:1,and the combustion image as the input signal of the control system.Finally,through the collection of combustion images under the condition of adding kaolin slagging additive alone,based on ShuffleNet’s slagging recognition model,the identification accuracy and confusion matrix are used to judge the effect of image processing.According to the identified image results,the established control system is used to control whether the motor of the mechanical slagging device starts.The results show that in the training and learning process of ShuffleNet slagging recognition model,the correct rate increases rapidly in the first 25 iterations,indicating that the weight obtained in the pre-training stage plays a role in the process of feature extraction in the shallow network,which accelerates the model convergence.After 25 iterations,the network becomes stable and the accuracy reaches 0.98.Through the test verification,the verification times of 5 and 5 test results are all greater than the set recognition accuracy threshold of 0.9,indicating that the mechanical slag removal control system built is feasible and accurate.This study provides a certain theoretical basis for improving the combustion efficiency and heat utilization of biomass pellet fuel hot water furnace,improving the service life and safety performance of combustion equipment,and provides a certain reference value for reducing the impact of biomass fuel on combustion equipment and combustion performance in the combustion process,and has engineering application significance.
Keywords/Search Tags:Peanut shell, Slagging characteristics, Slag removal device, Control system, ShuffleNet classification model
PDF Full Text Request
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