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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...

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Variance sensitive adaptive threshold-based PCA method for fault detection with experimental application.

Alkan Alkaya¹, Ilyas Eker

¹Department of Electrical and Electronic Engineering, Mersin University, 33343 Çiftlikköy, Mersin, Turkey. alkanalkaya@mersin.edu.tr

ISA Transactions

|January 22, 2011

Summary

This study introduces a novel Principal Component Analysis (PCA) method with a variance sensitive adaptive threshold for improved fault detection. The new technique effectively reduces false alarms in transient states, enhancing industrial process monitoring reliability.

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Area of Science:

Statistical Process Monitoring
Industrial Fault Detection

Background:

Principal Component Analysis (PCA) is a common statistical process monitoring technique.
Conventional PCA for fault detection uses fixed thresholds, leading to false alarms and data issues during transient process states.

Purpose of the Study:

To propose a new PCA method addressing false alarms and data loss in transient operations.
To enhance the reliability of industrial process monitoring systems.

Main Methods:

Development of a novel PCA method utilizing a variance sensitive adaptive threshold (T(vsa)).
Experimental implementation and validation on an electromechanical system.
Comparison with conventional PCA monitoring methods.

Main Results:

The proposed T(vsa) PCA method effectively overcomes false alarms in transient states.
The method demonstrates applicability and effectiveness in both steady-state and transient operations.
Early warning capabilities for operators were confirmed through experimental tests.

Conclusions:

The variance sensitive adaptive threshold PCA method is a reliable and effective solution for industrial process monitoring.
This advanced PCA technique improves fault detection accuracy during dynamic process conditions.