Title :
Faulty sensor detection, identification and reconstruction of indoor air quality measurements in a subway station
Author :
Liu, Hongbin ; Huang, Mingzhi ; Janghorban, Iman ; Ghorbannezhad, Payam ; Yoo, ChangKyoo
Author_Institution :
Dept. of Environ. Sci. & Eng., Kyung Hee Univ., Yongin, South Korea
Abstract :
Indoor air quality (IAQ) is important in subway stations because it can influence the health and comfort of passengers significantly. To effectively monitor and control the IAQ in subway stations, several key air pollutants data were collected by the air sampler and tele-monitoring system. In this study, an air pollutant prediction model based an adaptive network-based fuzzy inference system (ANFIS) was used to detect sensor fault, and a structured residual approach with maximum sensitivity (SRAMS) method was used to identify and reconstruct sensor faults existing in subway system. When a sensor failure was detected, the faulty sensor was identified using the exponential weighted moving average filtered squared residual (FSR). Four identification indices, including the identification index based on FSR (IFSR), the identification index based on generalized likelihood ratio (IGLR), the identification index based on cumulative sum of residuals (IQsum), and the identification index based on cumulative variances index (IVsum) were used to assist in identifying sensor faults. The best reconstructed sensor value can be estimated based on a given sensor fault direction. The drifting sensor failure was tested and the effectiveness of the proposed sensor validation procedure was verified.
Keywords :
air pollution; computerised monitoring; fault diagnosis; fuzzy reasoning; sensors; adaptive network based fuzzy inference system; air pollutant prediction model; air sampler; exponential weighted moving average filtered squared residual; faulty sensor detection; faulty sensor identification; faulty sensor reconstruction; generalized likelihood ratio; indoor air quality measurements; passenger comfort; passenger health; sensor validation procedure; subway station; telemonitoring system; Fault detection; Fault diagnosis; Indexes; Mathematical model; Monitoring; Principal component analysis; Temperature sensors; Adaptive network-based fuzzy inference system; Fault detection and identification; Fault reconstruction; Indoor air quality; Sensor validation; Subway system;
Conference_Titel :
Control, Automation and Systems (ICCAS), 2011 11th International Conference on
Conference_Location :
Gyeonggi-do
Print_ISBN :
978-1-4577-0835-0