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Related Concept Videos

Fault Types01:18

Fault Types

76
When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
76
Bus Impedance Matrix01:24

Bus Impedance Matrix

106
Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...
106
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

77
Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
77
Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

123
Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
123
Series R—L Circuit Transients01:22

Series R—L Circuit Transients

90
In a series resistor-inductor (R-L) circuit, closing the switch at the start of the time period simulates a three-phase short circuit, a fault condition where all three phases of an unloaded synchronous machine are short-circuited. When there is no fault impedance and no initial current, the initial voltage is determined by the phase angle of the source voltage.
Using Kirchhoff's Voltage Law (KVL) to analyze this circuit helps determine the total asymmetrical fault current, which consists...
90
Taping Over Different Ground Profiles01:12

Taping Over Different Ground Profiles

23
Taping over varying ground profiles requires careful adaptation to achieve accurate measurements. On smooth, level ground with minimal vegetation, the tape can rest directly on the ground. Here, the taping team, typically consisting of a head and a rear tapeman, coordinates their positions with clear communication. The rear tapeman holds the tape at the starting point and guides the head tapeman toward a range pole placed beyond the endpoint, using hand or voice signals to ensure alignment.On...
23

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Estimating t-way Fault Profile Evolution During Testing.

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Summary
This summary is machine-generated.

Most software interaction faults involve few variables. This study hypothesizes why this occurs, offering insights into fault removal and software reliability growth.

Keywords:
combinatorial testingsoftware faulttesting

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Area of Science:

  • Computer Science
  • Software Engineering
  • Reliability Engineering

Background:

  • Empirical studies reveal a pattern in software interaction faults.
  • Most faults involve one or two interacting variables.
  • Failures involving more than six variables are unreported.

Purpose of the Study:

  • To propose a hypothesis explaining the observed distribution of software interaction faults.
  • To explore implications for software fault removal strategies.
  • To enhance understanding of software reliability growth.

Main Methods:

  • Analysis of existing empirical data on software interaction faults.
  • Development of a theoretical hypothesis for fault distribution.
  • Discussion of the hypothesis's implications for fault removal and reliability.

Main Results:

  • A hypothesis is presented to explain the prevalence of low-variable interaction faults.
  • The findings suggest potential improvements in identifying and removing interaction faults.
  • The study provides a framework for understanding reliability growth based on fault interaction.

Conclusions:

  • The proposed hypothesis offers a novel perspective on software fault behavior.
  • Understanding the origin of fault distributions can lead to more effective testing and debugging.
  • This work contributes to advancing the field of software reliability engineering.