Fault Detection of Brahmanbaria Gas Plant using Neural Network

Description

No / In recent years, several accidents in pioneer gas
processing industries led industries to put emphasis on real-time
fault detection. Neural Network (NN) based fault (abnormal
situation) detection technique played an important role in
monitoring industrial safety. In this work, an attempt has been
made to study the fault detection of Brahmanbaria gas
processing plant using multi layered feed forward NN based
system. NN based fault detection system is trained, validated
and tested using data generated using the dynamic model.
Preliminary results show that NN based method is able to detect
the faults of Brahmanbaria Gas processing plant for fewer no of
faults.

Links & Downloads

1. Sowgath MT and Ahmed S (2014) Fault Detection of Brahmanbaria Gas Plant using Neural Network. In: Proceedings of the 8th International Conference on Electrical and Computer Engineering (ICECE). 20-22 Dec 2014, Pan Pacific Sonargaon, Dhaka, Bangladesh.
2. http://hdl.handle.net/10454/10981
3. https://doi.org/10.1109/ICECE.2014.7026933

Tags

Additional Fields

Identifer	oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/10981
Date	22 December 2014
Creators	Sowgath, Md Tanvir, Ahmed, S.
Source Sets	Bradford Scholars
Language	English
Detected Language	English
Type	Conference paper, No full-text in the repository