S变换 Resources

Showing items tagged with "S变换"

Excellent research paper with complete source code implementation. Voltage sag is one of the most concerning dynamic power quality issues. The widespread use of new power electronic devices demands higher power quality standards in grid systems. Since voltage sags exhibit propagation characteristics within power networks, both grid operators and end-users urgently require research and solutions for voltage sag mitigation. Voltage sag detection serves as the fundamental prerequisite for addressing this issue. This paper focuses on researching voltage sag detection methods, analyzing current research status of short-term power quality disturbance detection, and specifically examining voltage sag characteristics under three scenarios: short-circuit faults, induction motor starting, and transformer excitation. The study implements an S-transform-based detection algorithm that extracts features from S-magnitude and S-complex matrices to analyze amplitude variations, phase jumps, duration, and harmonic content.

MATLAB 230 views Tagged

The S-transform is an advanced time-frequency analysis tool that employs adaptive windowing—using wider windows at low frequencies for better frequency resolution and narrower windows at high frequencies for superior time resolution. This implementation provides both standard ST and Generalized S-Transform (GST) functions for signal processing applications.

MATLAB 270 views Tagged

MATLAB-based power quality detection simulation featuring wavelet transform, S-transform, FFT, and dq-transform implementations. The simulation runs by directly executing Mypower without requiring a graphical interface, providing algorithmic analysis of various power quality issues.

MATLAB 234 views Tagged

MATLAB implementation of S-transform along with multiple signal examples demonstrating its practical applications. S-transform is an advanced time-frequency analysis technique gaining traction in signal processing, seismic exploration, and speech recognition research. The code includes implementation details showing how to perform time-frequency decomposition, analyze signal characteristics, and extract meaningful features from various data types.

MATLAB 203 views Tagged