Software fault analysis is on major vector adopted by different researchers to analyze the software reliability. But most of the author taken the fault individually as the fault criticality or the fault count. But in this presented work we have considered all aspects of software faults i.e. fault count, fault criticality, fault frequency, associatively between faults. In this work a three level...

This paper deals with the application of artificial neural networks (ANNs) to the fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using one terminal line. The neural fault detector and locators have been trained with different sets of data available from a selected power network model and simulating different fault scenarios (fault types, fa...

Near-fault ground motions have caused very much damage in the vicinity of seismic sources during recent earthquakes. It is well known that under specific circumstances, intensive ground shakings near fault ruptures may be characterized by short-duration impulsive motions. This pulse-type motion is generally particular to the forward direction, where the fault rupture propagates towards the site...

In this paper, we investigate software fault detection and fault correction processes based on infinite server queuing model which incorporate testing effort functions. Some researches proposed in the literature to study fault detection and fault correction processes. However, most of them do not consider the amount of resources consumed during fault detection and fault correction processes. Th...

in this research, a new mathematical modeling on strength changes due to reservoir elastic stresses across the preexisting fault plane is introduced. the method has been applied to the dalpari fault, which is one of the potential seismic sources in the vicinity of the karkheh reservoir. in this method the distribution of total stress across the fault cannot be determined because the initial str...

in this study, detection and identification of common faults in industrial gas turbines is investigated. we propose a model-based robust fault detection(fd) method based on multiple models. for residual generation a bank of local linear neuro-fuzzy (llnf) models is used. moreover, in fault detection step, a passive approach based on adaptive threshold is employed. to achieve this purpose, the a...