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A platform for research: civil engineering, architecture and urbanism
Sensor failure detection in road tunnel ventilation
This paper has presented a failure detection method for TC (traffic counter(s)), AV (Air velocity), VI (visibility index), and CO meters in routine tunnel operation. The method makes statistical comparisons between measured values and values predicted by air speed and pollution models based on quasi-steady approximations to air flows. The following statements summarise the key messages of the paper: (1) Measurements of traffic data at tunnel portals can be used to predict evolving air velocities and pollutions concentrations throughout a tunnel; (2) By analyzing measured data over sufficiently long periods, it is possible to infer realistic approximations for values of base data describing tunnel and vehicle characteristics; (3) As a by-product of the method of determining optimal values for the base data, quantifiable statistical data are obtained about expected deviations between measured and predicted values at any particular sensor; (4) By monitoring statistical variations at sensors during actual tunnel operation and comparing them with the expected variations, it is possible to detect significant variations from normal behaviour and hence to identify instances of probable sensor malfunctions.
Sensor failure detection in road tunnel ventilation
This paper has presented a failure detection method for TC (traffic counter(s)), AV (Air velocity), VI (visibility index), and CO meters in routine tunnel operation. The method makes statistical comparisons between measured values and values predicted by air speed and pollution models based on quasi-steady approximations to air flows. The following statements summarise the key messages of the paper: (1) Measurements of traffic data at tunnel portals can be used to predict evolving air velocities and pollutions concentrations throughout a tunnel; (2) By analyzing measured data over sufficiently long periods, it is possible to infer realistic approximations for values of base data describing tunnel and vehicle characteristics; (3) As a by-product of the method of determining optimal values for the base data, quantifiable statistical data are obtained about expected deviations between measured and predicted values at any particular sensor; (4) By monitoring statistical variations at sensors during actual tunnel operation and comparing them with the expected variations, it is possible to detect significant variations from normal behaviour and hence to identify instances of probable sensor malfunctions.
Sensor failure detection in road tunnel ventilation
Sensorausfall-Detektion in der Lüftung von Straßentunneln
Nakahori, I. (author) / Sakaguchi, T. (author) / Mitani, A. (author) / Vardy, A.E. (author)
2012
8 Seiten, 2 Bilder, 4 Quellen
Conference paper
English
Tunnel , Verkehrsbauwerk , Untergrundbauwerk , Tunnelbau , Tunnelausbau , Detektor , Ausfall , Zählung , Luftgeschwindigkeit , Luftströmung , Ventilation (Lüftung) , Verschmutzung , statistische Analyse , mathematisches Verfahren , Stochastik , Auswertung , Statistik , Verkehrsanalyse , Verkehrsdichte , Straßentunnel
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