Font Size: a A A

Experimental Research On The Design Of Aerobic Composting Fermentation Device And Process Aeration Control

Posted on:2020-08-02Degree:MasterType:Thesis
Country:ChinaCandidate:J Y XuFull Text:PDF
GTID:2431330578475811Subject:Master of Agriculture
Abstract/Summary:PDF Full Text Request
Composting is an important way of the comprehensive utilization of organic waste in agriculture and animal husbandry.The main control factors of aerobic composting are agitation,turning over and aeration.Aeration has an impact on the temperature,humidity and oxygen concentration of aerobic fermentation.Too high or too low aeration will have a great impact on the internal fermentation process of the reactor.The traditional way of aeration control is manual control or set fixed time period aeration.Artificial control is time-consuming and laborious.Timing aeration only depends on experience,which ultimately affects the fermentation effect.Therefore,intelligent control of aeration process is particularly important.In this paper,different manure and straw mixtures were used as raw materials to study the different aeration control methods in the aerobic composting process,so as to provide a reference for the intelligent and efficient fermentation of aerobic composting.In thisthesis,the main research work is as follows:(1)According to the technical requirements of composting test process,a set of small multi-point aerobic composting test device is designed.The device includes aerobic fermentation unit,measurement and control unit and aeration unit.The tank body of aerobic fermentation unit is made of double-layer heat preservation and corrosion-resistant materials,with test sensor interface,aeration port and drainage port;the measurement and control unit is composed of wireless temperature and humidity sensor,oxygen sensor and intelligent compost controller;the aeration unit is composed of mass flowmeter,pneumatic valve,throttle valve and air pump.(2)Using HOBOnode wireless temperature and humidity sensor as standard contrast,the EP-200 wireless temperature and humidity sensor developed by our research group was calibrated,the error parameters and value range between the two sensors were obtained,and the relationship model between temperature and error parameters was established.Through calibration,the measurement range and accuracy of EP-200 wireless temperature and humidity sensor can meet the needs of the test.(3)The experiment of aerobic composting was carried out by mixing three kinds of manure materials,namely cow manure,cow manure biogas mud and chicken manure with corn straw.Through the measurement of temperature,moisture content,oxygen concentration,pH,EC,C/Nand other parameters,the change rules of parameters in different fermentation materials under the same conditions were obtained.The experimental results show that the designed multi-point aerobic composting test device has stable performance,stable control of automatic control system,and can meet the requirements of aerobic composting test.(4)With the same proportion of cow manure and corn straw as raw materials,and the aeration rate as a variable,the experiments of aeration rate of 7L/min,9L/min,11L/min,13L/min and15L/min were designed.Based on the data of aeration rate,composting time,raw material quality and C/N,the required aeration rate,aeration time and maturity of compost were obtained.The prediction models of raw material quality,composting time,aeration rate and C/N were established by using BP neural network.The validation test was carried out by adjusting aeration rate.The results show that the prediction model meets the requirements.The small-scale and multi-point aerobic composting test device designed in this paper has a high degree of automation.The neural network prediction model established can meet the automatic control requirements of aerobic composting test process,and provide a reference for the future research of aerobic composting intelligent production equipment.
Keywords/Search Tags:aerobic composting, fermentation equipment, aeration, automatic control, BP neural network
PDF Full Text Request
Related items