Please use this identifier to cite or link to this item: https://doi.org/10.1109/FSKD.2009.137
Title: Detecting automotive exhaust gas based on fuzzy inference system
Authors: Li, S.-J.
Bai, M.
Wang, Q.
Chen, B.
Zhao, X.-B.
Yang, T.
Wang, Z.-X. 
Keywords: Automotive exhaust gas
Fuzzy inference
Infrared analyzer
Temperature compensation
Issue Date: 2009
Source: Li, S.-J., Bai, M., Wang, Q., Chen, B., Zhao, X.-B., Yang, T., Wang, Z.-X. (2009). Detecting automotive exhaust gas based on fuzzy inference system. 6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009 3 : 267-270. ScholarBank@NUS Repository. https://doi.org/10.1109/FSKD.2009.137
Abstract: 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 nonlinear 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. © 2009 IEEE.
Source Title: 6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/69886
ISBN: 9780769537351
DOI: 10.1109/FSKD.2009.137
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