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Fault Types

Fault Types

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...

Power System Three-Phase Short Circuits

Power System Three-Phase Short Circuits

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...

Bus Impedance Matrix

Bus Impedance Matrix

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,...

Zones of Protection

Zones of Protection

In power systems, the entire setup is divided into protective zones to isolate faults and protect the rest of the network. These zones include generators, transformers, buses, transmission lines, distribution lines, and motors. Each zone can be visualized as a separate room in a house, with each room protected by its own circuit breaker.
Protective zones are defined by closed dashed lines, containing one or more components. A key characteristic of these zones is the strategic placement of...

Control System Problem

Control System Problem

In an open-loop system, such as a basic thermostat, the poles of the transfer function influence the system's response but do not determine its stability. However, when feedback is introduced to form a closed-loop system, such as an advanced thermostat that adjusts heating based on room temperature, stability is governed by the new poles of the closed-loop transfer function.
When forming a closed-loop system, issues can arise if the poles cross into the unstable region, leading to potential...

Root Loci for Positive-Feedback Systems

Root Loci for Positive-Feedback Systems

The Hartley oscillator is a positive feedback system that sustains oscillations by feeding the output back to the input in phase, thereby reinforcing the signal. Positive feedback systems can be viewed as negative feedback systems with inverted feedback signals. In these systems, the root locus encompasses all points on the s-plane where the angle of the system transfer function equals 360 degrees.
The construction rules for the root locus in positive feedback systems are similar to those in...

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Related Experiment Video

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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

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A New Sensor Fault Isolation Method for T-S Fuzzy Systems.

Jiuxiang Dong, Yue Wu, Guang-Hong Yang

IEEE Transactions on Cybernetics

|June 11, 2017

Summary

This study introduces a novel fault isolation scheme for Takagi-Sugeno (T-S) fuzzy systems experiencing sensor faults. The method enhances fault detection performance by utilizing premise variables independent of specific sensor outputs.

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Area of Science:

Control Systems Engineering
Fuzzy Logic Systems
Fault Diagnosis

Background:

Sensor faults pose significant challenges in the reliable operation of Takagi-Sugeno (T-S) fuzzy systems.
Existing fault isolation methods may have limitations in performance and specificity.

Purpose of the Study:

To propose a new fault isolation scheme for T-S fuzzy systems with sensor faults.
To improve the performance of fault isolation by decoupling observer design from specific sensor outputs.

Main Methods:

A set-theoretic description of T-S fuzzy models is employed.
A novel fault isolation scheme comprising a set of fuzzy observers is developed.
Premise variables are designed to be independent of the specific sensor output under consideration, relying instead on other sensor outputs.

Main Results:

The proposed fuzzy observers are independent of the faulty sensor's output in their antecedent and consequent parts.
Utilizing premise variables dependent on other sensor outputs shows potential for enhanced fault isolation performance.
A case study demonstrates the effectiveness of the proposed fault isolation method.

Conclusions:

The developed fault isolation scheme offers a promising approach for T-S fuzzy systems with sensor faults.
The independence of observer design from specific sensor outputs and the use of alternative premise variables contribute to improved fault isolation capabilities.