CPS

The paper entitled “Data-Driven Fault Diagnosis of Once-Through Benson Boilers” (Mehdi Saman Azari, Francesco Flammini, Stefania Santini, Mauro Caporuscio) will be presented at the 4th International Conference on System Reliability and Safety (ICSRS’19), sponsored by the IEEE, which will be held in Rome (Italy) on November 20-22, 2019.

The new PhD student Mehdi Saman Azari will attend the conference and present the paper, which will be published in the IEEE Digital Library.

Congratulations to Mehdi for his first paper as a PhD student at LNU!

Abstract

Fault Diagnosis (FD) of once-through Benson boilers, as a crucial equipment of many thermal power plants, is of paramount importance to guarantee continuous performance. In this study, a new fault diagnosis methodology based on data-driven methods is presented to diagnose faults in once-through Benson boilers. The present study tackles this issue by adopting a combination of data-driven methods to improve the robustness of FD blocks. For this purpose, one-class versions of minimum spanning tree and K-means algorithms are employed to handle the strong interaction between measurements and part load operation and also to reduce computation time and system training error. Furthermore, an adaptive neuro-fuzzy inference system algorithm is adopted to improve accuracy and robustness of the proposed fault diagnosing system by fusion of the output of minimum spanning tree (MST) and K-means algorithms. Performance of the presented scheme against six major faults is then assessed by analyzing several test scenarios.

UPDATE February 17th 2020

The paper is now available in the IEEE Digital Library and accessible at the following link:

https://ieeexplore.ieee.org/document/8987699