Analysis for Power System Transient Harmonics Based on Wavelet Packet Transform

2013 ◽  
Vol 415 ◽  
pp. 241-244
Author(s):  
Rong Hui Liu ◽  
Ai Qang Pan ◽  
Xiu Yang
Keyword(s):  
Wavelet Transform ◽  
Power Systems ◽  
Power System ◽  
Harmonic Analysis ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Time Varying ◽  
Analysis Method ◽  
Frequency Decomposition ◽  
Harmonic Analysis Method

In this paper, the principles of wavelet transform and wavelet packet transform were presented. The wavelet packet transform had good characteristics of uniform frequency decomposition, and thus transient harmonic analysis method was proposed based on wavelet packet transform. Finally, transient interharmonic, time varying harmonic and transient oscillation signals in power systems were simulated with Matlab emulator. The perfect results of simulation show that the presented method can accurately detect the transient harmonics, which provides support for harmonic analysis in power systems.

FEATURE EXTRACTION OF RADAR MULTIPLE-TARGET ECHOES USING WAVELET PACKET TRANSFORM WITH THE BEST BASES

2003 ◽  
Vol 17 (01) ◽  
pp. 127-150 ◽  
Author(s):  
SHOUYONG WANG ◽  
GUANGXI ZHU ◽  
YUAN Y. TANG
Keyword(s):  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Time Varying ◽  
Multiple Target ◽  
Time Frequency ◽  
Frequency Decomposition ◽  
Frequency Domains ◽  
Stationary Signals ◽  
Entropy Criterion ◽  
Positive Results

Extraction of effective features plays a key role in pattern recognition. A large number of patterns, such as speech, radar signals, earthquake signals, handwriting, etc. are of non-stationary signals or exhibit time-varying behavior. The features of these patterns are often located in both the time and frequency domains. The traditional methods fail to extract such kind of features. Fortunately, wavelet packet transform (WPT) can provide an arbitrary time-frequency decomposition for the signals, because a wavelet packet (WP) library contains many WP bases, which can handle the different components of a signal. Therefore, by selecting a suitable basis, which is called "best basis", the effective features can be extracted. In this paper, three criteria are used to select the best WPT basis, namely: (1) distance criterion, (2) divergence criterion and (3) entropy criterion. Three algorithms to implement the above criteria are also provided. Experiments are conducted and the positive results are obtained.

Application of Wavelet Transform in Signal Compression and Signal Recombination

2014 ◽  
Vol 986-987 ◽  
pp. 2056-2059
Author(s):  
Zhe Yuan Wang ◽  
Li Jiang
Keyword(s):  
Wavelet Transform ◽  
Wavelet Packet ◽  
Influence Factors ◽  
Wavelet Packet Transform ◽  
Signal Compression ◽  
Matlab Simulation ◽  
Paper Briefly ◽  
Simulation Experiments

This paper discusses the application of wavelet transform in signal compression and signal recombination detailedly. This paper briefly introduces the principle of wavelet transform in signal compression and signal recombination, this paper also introduces the wavelet MATLAB simulation experiments. This paper researches the differences the wavelet transform and wavelet packet transform in signal compression, this paper also briefly discusses the influence factors of signal compression.

Energy Distribution Analysis Regarding the Crack Size in a Rotating Shaft

2019 ◽  
Vol 24 (3) ◽  
pp. 418-425
Author(s):  
Cristina Cristina Castejon ◽  
Marıa Jesus Gomez ◽  
Juan Carlos Garcia-Prada ◽  
Eduardo Corral
Keyword(s):  
Wavelet Transform ◽  
Crack Detection ◽  
Wavelet Packet ◽  
Critical Role ◽  
Wavelet Packet Transform ◽  
Discrete Wavelet ◽  
Distribution Analysis ◽  
Rotating Shaft ◽  
Vibration Signals ◽  
Machine Monitoring

Maintenance is critical to avoid catastrophic failures in rotating machinery, and the detection of cracks plays a critical role because they can originate failures with costly processes of reparation, especially in shafts. Vibration signals are widely used in machine monitoring and fault diagnostics. The most critical issue in machine monitoring is the suitable selection of the vibration parameters that represent the condition of the machine. Discrete Wavelet Transform, and one of its recursive forms, called Wavelet Packet Transform, provide a high potential for pattern extraction. Several factors must be selected and taken into account in the Wavelet Transform application such as the level of decomposition, the suitable mother wavelet, and the level basis or features. In this work, the dynamic response of a shaft with different levels of crack is studied. The evolution of energy of the vibration signals obtained from the rotating shaft and the frequencies where maximum increments of energy appear with the crack are analyzed. The results allow the conclusion that changes in energies computed by means of the Wavelet Packet Transform can be successfully used for crack detection.

The Application of Improved HHT to Harmonic Analysis and Fault Detection of Power System

2011 ◽  
Vol 354-355 ◽  
pp. 1406-1411
Author(s):  
Wen Hua Han ◽  
Hai Xia Ren ◽  
Xu Chen ◽  
Xiao Juan Tao
Keyword(s):  
Fault Detection ◽  
Power System ◽  
Harmonic Analysis ◽  
Harmonic Signal ◽  
Ensemble Empirical Mode Decomposition ◽  
Frequency Domain Analysis ◽  
Analysis Method ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Mode Decomposition

Hilbert-Huang transform (HHT) is a new time-frequency-domain analysis method, which is suitable for non-stationary and nonlinear signals. In this paper, endpoint continuation and ensemble empirical mode decomposition (EEMD) decomposition method are introduced to improve the HHT, which solve the endpoint winger and modal aliasing problem. The improved HHT (IHHT) is used for analyzing the harmonic signal and detecting the fault signal of power system. Simulation results show that IHHT is feasible and effective for harmonic analysis and fault detection.

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