Gas thickness on-line monitoring instrument design based on BP neural network

This paper uses neural network to process acquired digital signals on line, realizing automotive recognition to and thickness analysis of three kinds of gas. This method can automatically measure and show working temperature of air-sense organ, and according to a given temperature adjust the tempera...

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Bibliographic Details
Published in2008 27th Chinese Control Conference pp. 713 - 716
Main Authors Liu Weiwei, Mu Ping'an, Dai Shuguang, Wang Shijun
Format Conference Proceeding
LanguageChinese
English
Published IEEE 01.07.2008
Subjects
Artificial neural networks
Automotive Recognition
BP Neural Network
Intercross Sensitivity
Neurons
Sensitivity
Temperature measurement
Temperature sensors
Thickness Analysis
Training
Transfer functions
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Summary:This paper uses neural network to process acquired digital signals on line, realizing automotive recognition to and thickness analysis of three kinds of gas. This method can automatically measure and show working temperature of air-sense organ, and according to a given temperature adjust the temperature, which decreases effect of intercross sensitivity and improves accuracy of measurement results.
ISSN:1934-1768
2161-2927
DOI:10.1109/CHICC.2008.4605658