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Design And Research Of Harmful Gas Detecting Device Based On Wireless Communication Platform SRV1

Posted on:2012-11-25Degree:MasterType:Thesis
Country:ChinaCandidate:J J JinFull Text:PDF
GTID:2218330338951843Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
With the improvement of human life, The requirements for air quality are also rising. But we will find that, in our real life, along with the development of industrial level, the use of various industrial gases is increasing. This inevitably results some kinds of gases, especially toxic and harmful gas leaks, along with a variety of industrial discharge of harmful emissions, the environment on human life and the quality of life will be severely damaged. The former gas detectors are all fixed and portable, but the locations of the gas leaking may be unpredictable, so we can not install the fixed gas detector beforehand. When the harmful gas leaks, the people with portable gas detector have to go to the leaking area. This seriously threatened the safety of their lives. So we need to develop a remote control for the detection devices, which can detect the gas concentration without workers getting into the area.In this paper, the devices needed in this design such as SRV1 and iTrans are deeply researched, hardware platform is designed , and explosion-proof design is researched . At the same time , the software of the design is designed , and the software design includes three parts : Signal acquisition program , data transfer program, and client program. Through programming, concentration detection of CO and SO2 is achieved, and the concentration information of the gas are displayed in the client interface, There is great influence on the concentration output of the gas detection devices because of the sensor drift, In this paper, We proposed a method, using RBF neural network, to compensate and correct the sensor drift, to make suer the output value of the device reflect the concentration of gas accurately.And through MATLAB simulation, we make the output of the device accurately reflect the actual gas concentrations.
Keywords/Search Tags:SRV1, DSP, Gas detection, Neural network
PDF Full Text Request
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