This paper discusses the application of MultiLayer Feed Forward Neural Network (MFNN) for the differential protection of the turbogenerator based on pattern classification. The cases of all the possible internal faults in the stator of the generator with lap winding have been simulated using Modified Winding function Approach. The simulated fault currents in the phases and their parallel paths ...

Fault detection and isolation (FDI) for industrial processes has been actively studied during the last decades. Traditionally, the most widely implemented FDI methods have been based on model-based approaches. In modern process industry, however, there is a demand for data-based methods due to the complexity and limited availability of the mechanistic models. The aim of this paper is to present...

The recurrence time, T r , of strong earthquakes above a predefined magnitude threshold on specific faults or fault segments is an important parameter, that could be used as input in the development long-term fault-based Earthquake Rupture Forecasts (ERF). amount observational time data per segment often limited, due to long duration stress rebuilt and shortage earthquake catalogs. As consequen...

We simulated dynamic rupture propagation along various nonplanar fault models of the 1999 İzmit, Turkey, earthquake using a boundary integral equation method. These models were inferred from geological and geodetic observations. Based on these results, we modeled seismic-wave propagation around the fault system using a finite difference method. We focused on the effect of different fault geomet...

This paper presents a new approach for fault detection and classification in transmission line using Decision Tree (DT). The DT based fault detection algorithm uses 1/4th cycle data of fault currents from fault inception, to generate the optimal decision tree for fault detection. Similarly, the DT based classification algorithm takes half cycle data from fault inception of three phase currents ...

The optimal interpolative (OI) classification network is extended to include fault tolerance and make the network more robust to the loss of a neuron. The OI net has the characteristic that the training data are fit with no more neurons than necessary. Fault tolerance further reduces the number of neurons generated during the learning procedure while maintaining the generalization capabilities ...

A comparison of the X-ray powder diffraction (XRPD) patterns of face-centered cubic silver with twin faults simulated with the DIFFaX and MAUD computer programs is presented. MAUD was used to refine the DIFFaX-simulated patterns to determine systematic differences between these simulation programs. The results indicated the Warren model of twin faults is applicable for fault probabilities <10% ...

In the framework of quantum computational tensor network, which is a general framework of measurement-based quantum computation, the resource many-body state is represented in a tensor-network form (or a matrix-product form), and universal quantum computation is performed in a virtual linear space, which is called a correlation space, where tensors live. Since any unitary operation, state prepa...