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Research On Electronic Nose Technology For Gas Quantitative Detection

Posted on:2014-08-04Degree:MasterType:Thesis
Country:ChinaCandidate:W HeFull Text:PDF
GTID:2268330401965344Subject:Optical Engineering
Abstract/Summary:PDF Full Text Request
Electronic nose technology as a major branch of sensor technology has a greatapplication value in gas detection. China as the world’s coal power has a rapidlydeveloping coal industry. However, gas causes serious damage to people’s productionand life, so high precision detection of gas is imminent. As the increasing use of thesensor technology and electronic nose technology, electronic noses have a greaterchallenge in gas detection: quantitative detection of gas mixture.This paper introduces the development history of electronic nose technology andresearch status at home and abroad, and expounds the research purpose and meaning ofgas quantitative detection by using electronic nose technology. At the same time, basedon the composition and working principle of electronic nose, the combination of sensorarray, the collection of the response data, and the design pattern recognition algorithm,are all completed, leading to the success of the gas quantitative detection. The work ofthis paper includes:1. By researching the working principle of the electronic nose, based on ARM11processor, from the selection of sensor to the design of reading-circuit, from ADsampling to data processing, from training algorithm to quantitative detection, aportable electronic nose is completely designed.2. Based on the WINCE embedded operating system and the VS2005environment, the related programs for electronic noses are written. The programs adoptmodular design, containing three modules of collection, training and recognition.Software has a good human-computer interaction interface, and uses the touch LCDscreen for displaying, greatly improving the operability.3. Based on neural network, this paper contrasts three quantitative recognitionalgorithms: BP network, distributed neural network and approximated neural network.The electronic nose system can well complete the gas quantitative detection, and canconveniently by changing sensors to achieve other quantitative detection of gas mixture.
Keywords/Search Tags:Electronic nose, Gas, Pattern recognition, Quantitative, Neural network
PDF Full Text Request
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