Abstract
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.Version
No full-text in the repositoryCitation
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.Link to Version of Record
https://doi.org/10.1109/ICECE.2014.7026933Type
Conference paperae974a485f413a2113503eed53cd6c53
https://doi.org/10.1109/ICECE.2014.7026933