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2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery
Detecting Automotive Exhaust Gas Based on Fuzzy Inference System
Tianjin, China
August 14-August 16
ISBN: 978-0-7695-3735-1
ASCII Text
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Shu-jin Li, Ming Bai, Quan Wang, Bo Chen, Xiao-bing Zhao, Ting Yang, Zhao-xia Wang, "Detecting Automotive Exhaust Gas Based on Fuzzy Inference System," Fuzzy Systems and Knowledge Discovery, Fourth International Conference on, vol. 3, pp. 267-270, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009.
 
 
BibTex
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@article{ 10.1109/FSKD.2009.137,
author = {Shu-jin Li and Ming Bai and Quan Wang and Bo Chen and Xiao-bing Zhao and Ting Yang and Zhao-xia Wang},
title = {Detecting Automotive Exhaust Gas Based on Fuzzy Inference System},
journal ={Fuzzy Systems and Knowledge Discovery, Fourth International Conference on},
volume = {3},
year = {2009},
isbn = {978-0-7695-3735-1},
pages = {267-270},
doi = {http://doi.ieeecomputersociety.org/10.1109/FSKD.2009.137},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on
TI - Detecting Automotive Exhaust Gas Based on Fuzzy Inference System
SN - 978-0-7695-3735-1
SP267
EP270
A1 - Shu-jin Li,
A1 - Ming Bai,
A1 - Quan Wang,
A1 - Bo Chen,
A1 - Xiao-bing Zhao,
A1 - Ting Yang,
A1 - Zhao-xia Wang,
PY - 2009
KW - infrared analyzer
KW - automotive exhaust gas
KW - fuzzy inference
KW - temperature compensation
VL - 3
JA - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on
ER -
 
This paper proposes a method of detecting automotive exhaust gas based on fuzzy logic inference after analyzing the principle of the infrared automobile exhaust gas analyzer and the influence of the environmental temperature on analyzer. This paper analyses the measurement error caused by environmental temperature, and then makes a non-linear error correction of temperature for the infrared sensor using fuzzy inference. The results of simulation have clearly demonstrated that the proposed fuzzy compensation scheme is better than the non-fuzzy method.
Index Terms:
infrared analyzer, automotive exhaust gas, fuzzy inference, temperature compensation
Citation:
Shu-jin Li, Ming Bai, Quan Wang, Bo Chen, Xiao-bing Zhao, Ting Yang, Zhao-xia Wang, "Detecting Automotive Exhaust Gas Based on Fuzzy Inference System," fskd, vol. 3, pp.267-270, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
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