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Univ logo Fault Diagnosis for Power Transmission Line using Statistical Methods Yuanjun Guo Prof. Kang Li Queen’s University, Belfast UKACC PhD Presentation Showcase
Univ logo
Fault Diagnosis for Power Transmission Line using Statistical Methods
Yuanjun Guo
Prof. Kang Li
Queen’s University, Belfast
UKACC PhD Presentation Showcase
Univ logo UKACC PhD Presentation Showcase Slide 2
Background
Huge data
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Problems & Motivation
ProblemsCurse of Dimensionality
multivariate and correlated data
Classification various types of faults in transmission lines
MotivationDimension reductionBalance the real time implementation
and the accuracy
Univ logo UKACC PhD Presentation Showcase Slide 4
Research methodology
Principal Component Analysis
Support Vector Machine
PLS, ICA, PCR etc.
Univ logo UKACC PhD Presentation Showcase Slide 5
Current status
Univ logo UKACC PhD Presentation Showcase Slide 6
Conclusion
Statistical approaches are capable of reduce the data dimensionality by capturing the relationship between the recorded variables from the data.
Provide confidential limit charts for the violate fault points.
Extract the features of the faulty signal under different faulty situations.
SVMs uses the features as input to classify these faults correctly.
Univ logo UKACC PhD Presentation Showcase Slide 7
Future work
Develop nonlinear and dynamic extensions to identify the nonlinear relations of the process variables;
Optimize or select parameters for SVMs to achieve better classification results.
Research the application in power transmission lines.
Univ logo UKACC PhD Presentation Showcase Slide 8
