Bayesian decoding of the ammonia response of a zirconia-based mixed-potential sensor in the presence of hydrocarbon interference

Sensors and Actuators, B: Chemical

Volumn 192, Issue , 2014, Pages 283-293

  Tsitron, Julia ^a   Kreller, Cortney R ^b   Sekhar, Praveen K ^c   Mukundan, Rangachary ^b   Garzon, Fernando H ^b   Brosha, Eric L ^b   Morozov, Alexandre V ^a  

^a RUTGERS UNIVERSITY   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

^c WASHINGTON STATE UNIVERSITY   (United States)

Author keywords

Bayesian modeling; Electrochemical sensor; Engine exhaust analysis; Mixed potential sensor

Indexed keywords

ACCURATE PREDICTION; BAYESIAN FRAMEWORKS; BAYESIAN MODEL; EXHAUST ANALYSIS; MIXED-POTENTIAL; SENSOR SENSITIVITY; TARGET AND NON TARGETS; UNBURNED HYDROCARBONS;

AMMONIA; BIAS CURRENTS; DIESEL ENGINES; ELECTROCHEMICAL SENSORS; EXHAUST SYSTEMS (ENGINE); FORECASTING; GASES; HYDROCARBONS; MIXTURES; NITROGEN OXIDES; NONLINEAR SYSTEMS; PROPYLENE; ZIRCONIA;

SENSORS;

EID: 84889063181     PISSN: 09254005     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.snb.2013.10.115     Document Type: Article

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