A perspective on fault diagnosis of industrial communication networks

Fault Diagnosis of Networked Control Systems Networked Control Systems (NCSs) deal with feedback control systems with loops closed via data communication networks. Control over a network has many advantages compared with traditionally controlled systems, such as a lower implementation cost, reduced wiring, simpler installation and maintenance and higher reliability. Nevertheless, the network-induced delay, packet dropout, asynchronous behavior and other specificities of networks will degrade the performance of closed-loop systems. In this context, it is necessary to develop a new theory for systems that operate in a distributed and asynchronous environment. Research on Fault Detection and Isolation (FDI) for NCSs has received increasing attention in recent years. This paper reviews the state of the art in this topic.

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An intelligent fault diagnosis for centrifugal pumps based on electric current information available in industrial communication networks

10.1109/induscon51756.2021.9529678 ◽

2021 ◽

Author(s):

Andre Luis Dias ◽

Jonathan Tobias da Silva ◽

Afonso Celso Turcato ◽

Guilherme Serpa Sestito

Keyword(s):

Fault Diagnosis ◽

Electric Current ◽

Communication Networks ◽

Centrifugal Pumps ◽

Intelligent Fault Diagnosis ◽

Current Information

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A New Algorithm for the Fuzziness of Alarms in Network Faults Diagnosis

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.198-199.1539 ◽

2012 ◽

Vol 198-199 ◽

pp. 1539-1544 ◽

Cited By ~ 1

Author(s):

Pan Liu ◽

Xing Ming Li ◽

Jian Wu

Keyword(s):

Fault Diagnosis ◽

Correlation Analysis ◽

Communication Networks ◽

Association Rules ◽

Association Rules Mining ◽

Fuzzy Association Rules ◽

Edge Field ◽

Alarm Correlation ◽

Faults Diagnosis ◽

Network Fault

The alarm correlation analysis based on fuzzy association rules mining is the popular and cutting-edge field of the network fault diagnosis research. In the application environment of alarms in communication networks, a new algorithm of the fuzziness of alarms which is called FKMA (Fuzzy K-Means of Alarms algorithm) is proposed .During the process of fuzziness, there are two methods of sorting the center. Simulations are carried out to the comparison of the two methods. The fuzziness of alarms is effectively realized. And fuzzy association rules mining are achieved. The advantages and efficiency of FKMA are demonstrated by experiments.

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