Abstract: Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.
Abstract: This paper presents the voltage regulation scheme of
D-STATCOM under three-phase faults. It consists of the voltage
detection and voltage regulation schemes in the 0dq reference. The
proposed control strategy uses the proportional controller in which
the proportional gain, kp, is appropriately adjusted by using genetic
algorithms. To verify its use, a simplified 4-bus test system is situated
by assuming a three-phase fault at bus 4. As a result, the DSTATCOM
can resume the load voltage to the desired level within
1.8 ms. This confirms that the proposed voltage regulation scheme
performs well under three-phase fault events.
Abstract: A novel application of neural network approach to
fault classification and fault location of Medium voltage cables is
demonstrated in this paper. Different faults on a protected cable
should be classified and located correctly. This paper presents the use
of neural networks as a pattern classifier algorithm to perform these
tasks. The proposed scheme is insensitive to variation of different
parameters such as fault type, fault resistance, and fault inception
angle. Studies show that the proposed technique is able to offer high
accuracy in both of the fault classification and fault location tasks.
Abstract: This paper proposes the use of metrics in design space exploration that highlight where in the structure of the model and at what point in the behaviour, prevention is needed against transient faults. Previous approaches to tackle transient faults focused on recovery after detection. Almost no research has been directed towards preventive measures. But in real-time systems, hard deadlines are performance requirements that absolutely must be met and a missed deadline constitutes an erroneous action and a possible system failure. This paper proposes the use of metrics to assess the system design to flag where transient faults may have significant impact. These tools then allow the design to be changed to minimize that impact, and they also flag where particular design techniques – such as coding of communications or memories – need to be applied in later stages of design.
Abstract: Dissolved gas analysis has been accepted as a sensitive, informative and reliable technique for incipient faults detection in power transformers and is widely used. In the last few years this method, which has been recommended by IEEE Power & Energy society, has been applied for fault detection in load tap changers. Regarding the critical role of load tap changers in electrical network and essential of catastrophic failures prevention, it is necessary to choose "condition based preventative maintenance strategy" which leads to reduction in costs, the number of unnecessary visits as well as the probability of interruptions and also increment in equipment reliability. In current work, considering the condition based preventative maintenance strategy, condition assessment of an Elin tap changer was carried out using dissolved gas analysis.
Abstract: The structural interpretation of a part of eastern Potwar
(Missa Keswal) has been carried out with available seismological,
seismic and well data. Seismological data contains both the source
parameters and fault plane solution (FPS) parameters and seismic data
contains ten seismic lines that were re-interpreted by using well data.
Structural interpretation depicts two broad types of fault sets namely,
thrust and back thrust faults. These faults together give rise to pop up
structures in the study area and also responsible for many structural
traps and seismicity. Seismic interpretation includes time and depth
contour maps of Chorgali Formation while seismological interpretation
includes focal mechanism solution (FMS), depth, frequency,
magnitude bar graphs and renewal of Seismotectonic map. The Focal
Mechanism Solutions (FMS) that surrounds the study area are
correlated with the different geological and structural maps of the area
for the determination of the nature of subsurface faults. Results of
structural interpretation from both seismic and seismological data
show good correlation. It is hoped that the present work will help in
better understanding of the variations in the subsurface structure and
can be a useful tool for earthquake prediction, planning of oil field and
reservoir monitoring.
Abstract: Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.
Abstract: Power transformers are among the most important and
expensive equipments in the electric power systems. Consequently
the transformer protection is an essential part of the system
protection. This paper presents a new method for locating
transformer winding faults such as turn-to-turn, turn-to-core, turn-totransformer
body, turn-to-earth, and high voltage winding to low
voltage winding. In this study the current and voltage signals of input
and output terminals of the transformer are measured, which the
Fourier transform of measured signals and harmonic analysis
determine the fault's location.
Abstract: It has been defined that the “network is the system".
This implies providing levels of service, reliability, predictability and
availability that are commensurate with or better than those that
individual computers provide today. To provide this requires
integrated network management for interconnected networks of
heterogeneous devices covering both the local campus. In this paper
we are addressing a framework to effectively deal with this issue. It
consists of components and interactions between them which are
required to perform the service fault management. A real-world
scenario is used to derive the requirements which have been applied
to the component identification. An analysis of existing frameworks
and approaches with respect to their applicability to the framework is
also carried out.
Abstract: Springback is a significant problem in the sheet metal
forming process. When the tools are released after the stage of
forming, the product springs out, because of the action of the internal
stresses. In many cases the deviation of form is too large and the
compensation of the springback is necessary. The precise prediction
of the springback of product is increasingly significant for the design
of the tools and for compensation because of the higher ratio of the
yield stress to the elastic modulus.
The main object in this paper was to study the effect of the
anisotropy on the springback for three directions of rolling: 0°, 45°
and 90°. At the same time, we highlighted the influence of three
different metallic materials: Aluminum, Steel and Galvanized steel.
The original of our purpose consist on tests which are ensured by
adapting a U-type stretching-bending device on a tensile testing
machine, where we studied and quantified the variation of the
springback according to the direction of rolling. We also showed the
role of lubrication in the reduction of the springback.
Moreover, in this work, we have studied important characteristics
in deep drawing process which is a springback. We have presented
defaults that are showed in this process and many parameters
influenced a springback.
Finally, our results works lead us to understand the influence of
grains orientation with different metallic materials on the springback
and drawing some conclusions how to concept deep drawing tools. In
addition, the conducted work represents a fundamental contribution
in the discussion the industry application.
Abstract: This paper deals with the effect of a power transformer’s vector group on the basic voltage sag characteristics during unbalanced faults at a meshed or radial power network. Specifically, the propagation of voltage sags through a power transformer is studied with advanced short-circuit analysis. A smart method to incorporate this effect on analytical mathematical expressions is proposed. Based on this methodology, the positive effect of transformers of certain vector groups on the mitigation of the expected number of voltage sags per year (sag frequency) at the terminals of critical industrial customers can be estimated.
Abstract: This paper presents a wavelet transform and Support
Vector Machine (SVM) based algorithm for estimating fault location
on transmission lines. The Discrete wavelet transform (DWT) is used
for data pre-processing and this data are used for training and testing
SVM. Five types of mother wavelet are used for signal processing to
identify a suitable wavelet family that is more appropriate for use in
estimating fault location. The results demonstrated the ability of SVM
to generalize the situation from the provided patterns and to
accurately estimate the location of faults with varying fault resistance.
Abstract: Interpolated contour maps drawn for aluminum,
copper and molybdenum in downstream monitoring boreholes of
water dam in Miduk Copper Complex and the values of pH, redox
potential (Eh) and distance from water dam indicate different trends
of variation and behavior of these three elements in downward
groundwater resources. As these maps exhibit, aluminum is dominant
in the most alkaline (pH = 9-11) borehole (MB5) to water dam. The
highest concentration of molybdenum is found in the nearest
borehole (MB6) to water dam. Main concentration of copper is
observed in the most oxidized borehole (MB3 with Eh=293.2mV).
The spatial difference among sampling stations can be attributed to
the existence of faults and diaclases in the geologic structure of
Miduk region which causes the groundwater sampling sites to be
impressed by different contamination sources (toe seepage and upper
seepage water originated from different zones of tailings dump).
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: Software maintenance is extremely important activity in software development life cycle. It involves a lot of human efforts, cost and time. Software maintenance may be further subdivided into different activities such as fault prediction, fault detection, fault prevention, fault correction etc. This topic has gained substantial attention due to sophisticated and complex applications, commercial hardware, clustered architecture and artificial intelligence. In this paper we surveyed the work done in the field of software maintenance. Software fault prediction has been studied in context of fault prone modules, self healing systems, developer information, maintenance models etc. Still a lot of things like modeling and weightage of impact of different kind of faults in the various types of software systems need to be explored in the field of fault severity.
Abstract: Back-to-back static synchronous compensator (BtBSTATCOM) consists of two back-to-back voltage-source converters (VSC) with a common DC link in a substation. This configuration extends the capabilities of conventional STATCOM that bidirectional active power transfer from one bus to another is possible. In this paper, VSCs are designed in quasi multi-pulse form in which GTOs are triggered only once per cycle in PSCAD/EMTDC. The design details of VSCs as well as gate switching circuits and controllers are fully represented. Regulation modes of BtBSTATCOM are verified and tested on a multi-machine power system through different simulation cases. The results presented in the form of typical time responses show that practical PI controllers are almost robust and stable in case of start-up, set-point change, and line faults.
Abstract: Pyritisation halos are identified in weathering crusts and unconsolidated formations at five locations within large fault structure of the Urals’ eastern slope. Electron microscopy reveals the presence of inclusions and growths on pyrite faces – normally on cubic pyrite with striations, or combinations of cubes and other forms. Following neogenesis types are established: native elements and intermetallic compounds (including gold and silver), halogenides, sulphides, sulfosalts, tellurides, sulphotellurides,
selenides, tungstates, sulphates, phosphates, carbon-based substances. Direct relationship is noted between amount and diversity of such mineral phases, and proximity to and scale of ore-grade mineralization. Gold and silver, both in native form and within tellurides, presence of lead (galena, native lead), native tungsten, and, possibly, molybdenite and sulfosalts can indicate gold-bearing formations. First find of native tungsten in the Urals is for the first time – in crystallised and druse-like form. Link is suggested between unusual mineralization and “reducing” hydrothermal fluids from deep-seated faults at later stages of Urals’ reactivation.
Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.
Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.