Pregled bibliografske jedinice broj: 798669
Anomaly Detection in Thermal Power Plant using Probabilistic Neural Network
Anomaly Detection in Thermal Power Plant using Probabilistic Neural Network // 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) : Proceedings / Biljanović, Petar ; Butković, Željko ; Skala, Karolj ; Mikac, Branko ; Čičin-Šain, Marina ; Sruk, Vlado ; Ribarić, Slobodan ; Gros, Stjepan ; Vrdoljak, Boris ; Mauher, Mladen ; Sokolić, Andrej (ur.).
Opatija, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2015. str. 1321-1326 doi:10.1109/MIPRO.2015.7160443 (predavanje, podatak o recenziji nije dostupan, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 798669 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Anomaly Detection in Thermal Power Plant using Probabilistic Neural Network
Autori
Hajdarević, Amel ; Džananović, Izet ; Banjanović-Mehmedović, Lejla ; Mehmedović, Fahrudin
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) : Proceedings
/ Biljanović, Petar ; Butković, Željko ; Skala, Karolj ; Mikac, Branko ; Čičin-Šain, Marina ; Sruk, Vlado ; Ribarić, Slobodan ; Gros, Stjepan ; Vrdoljak, Boris ; Mauher, Mladen ; Sokolić, Andrej - : Institute of Electrical and Electronics Engineers (IEEE), 2015, 1321-1326
ISBN
978-9-5323-3082-3
Skup
38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
Mjesto i datum
Opatija, Hrvatska, 25-29.05.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Podatak o recenziji nije dostupan
Ključne riječi
neural nets ; thermal power stations
Sažetak
Print Request Permissions Anomalies are integral part of every system's behavior and sometimes cannot be avoided. Therefore it is very important to timely detect such anomalies in real-world running power plant system. Artificial neural networks are one of anomaly detection techniques. This paper gives a type of neural network (probabilistic) to solve the problem of anomaly detection in selected sections of thermal power plant. Selected sections are steam superheaters and steam drum. Inputs for neural networks are some of the most important process variables of these sections. It is noteworthy that all of the inputs are observable in the real system installed in thermal power plant, some of which represent normal behavior and some anomalies. In addition to the implementation of this network for anomaly detection, the effect of key parameter change on anomaly detection results is also shown. Results confirm that probabilistic neural network is excellent solution for anomaly detection problem, especially in real-time industrial applications.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
