Abstract — Fault detection in large-scale systems is conducted by the use of sensors, thus the sensor location influences the performances of fault detection directly. As the scale of systems increases, traditional input-output models may not work well or may even not be applicable. The Signed Directed Graph (SDG) model is used to describe large-scale complex systems and the cause-effect relationships among variables. However, SDG cannot express the dynamic propagation properties when describing the fault propagation phenomena. In this paper, time parameters are taken into account within the branches of an SDG, in order to approximately denote the propagation time of the variable changes in the systems. An SDG constructed this way is called...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
An optimally located network of sensors is a prerequisite for successful application of fault diagno...
Fault diagnosis is an important task for the safe ann optimal operation of chemical processes. Hence...
The success of any fault diagnosis technique depends critically on the sensors measuring the importa...
Nowadays in modern industries, the scale and complexity of process systems are increased continuousl...
Performance of fault diagnosis system based on signed directed graph (SDG) is experimentally analyze...
Modern enterprise networks encompass tens of thousands of network entities and present a very challe...
In this paper, the performance limits of faults localization are investigated using synchrophasor da...
In location problems, the outtransmission and intransmission numbers are important indices to evalua...
In location problems, the outtransmission and intransmission numbers are important indices to evalua...
This paper introduces a novel cognitive fault diagnosis system (FDS) for distributed sensor networks...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
An optimally located network of sensors is a prerequisite for successful application of fault diagno...
Fault diagnosis is an important task for the safe ann optimal operation of chemical processes. Hence...
The success of any fault diagnosis technique depends critically on the sensors measuring the importa...
Nowadays in modern industries, the scale and complexity of process systems are increased continuousl...
Performance of fault diagnosis system based on signed directed graph (SDG) is experimentally analyze...
Modern enterprise networks encompass tens of thousands of network entities and present a very challe...
In this paper, the performance limits of faults localization are investigated using synchrophasor da...
In location problems, the outtransmission and intransmission numbers are important indices to evalua...
In location problems, the outtransmission and intransmission numbers are important indices to evalua...
This paper introduces a novel cognitive fault diagnosis system (FDS) for distributed sensor networks...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...
Exploiting spatial and temporal relationships in acquired datastreams is a primary ability of Cognit...