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Research Of Harvesting Machinery Yield Monitor System

Posted on:2015-03-04Degree:MasterType:Thesis
Country:ChinaCandidate:C Z LiFull Text:PDF
GTID:2253330428957257Subject:Agricultural Electrification and Automation
Abstract/Summary:PDF Full Text Request
With the rapid development of precision agriculture, our country also has a leap developmentin traditional agriculture. The level of agricultural mechanization also has remarkableimprovement. Because the grain production is related to a country’s economic lifeline and isclosely linked to the country’s politics and economy, thus accurate prediction of the grain outputis of great significance to the country. Therefore, the main content of this article is to research theyield monitoring system of harvester. By means of researching existing method of yieldmonitoring, this article puts forward to a new concept based on the predecessor’s research, whichis to set up regression model by way of multiple linear regression analysis to predict grain output.According to the need of yield monitoring system, we design the yield monitoring system ofgrain on the basis of single chip AT89S51.This system’s main function is that it can measure the current speed of harvester, harvesterarea and current grain total output when working in the field. In terms of data collection, thissystem selects and uses electronic follow-up strain gauge pressure transducer which has higherprecision and stability than others. This system applies differential transition chip ADC0804-A/Dtransition chip to analog signal processing and it collects differential input signal in the way ofanalog signal processing, which can overcome system error effectively. This system puts datacollected into core controller for data calculation firstly, then predicts current grain outputaccording to regression model, and finally displays the prediction result on LCD. This systemcan observe harvest information of the field in real time and the working condition of harvesterin order that it can timely assist users to make decision with advantageous information.
Keywords/Search Tags:Harvester, Grain Output, Multiple Regression Analysis, Prediction Model
PDF Full Text Request
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