Calculation about the Fundamental Wave Amplitude of the Current in the Distribution Line on Wavelet Analysis

2011 ◽  
Vol 308-310 ◽  
pp. 1357-1360
Author(s):  
Chang Chun Chi ◽  
Jian Wei Chen ◽  
Yi Wu
Keyword(s):  
Wavelet Analysis ◽  
Frequency Characteristic ◽  
Wave Amplitude ◽  
Engineering Practice ◽  
Fundamental Wave ◽  
Time Frequency ◽  
Full Wave ◽  
Distribution Line ◽  
Complex Wavelet ◽  
Dc Component

Wavelet analysis, as a new kind of time-frequency representation technique, has made great progress recently and been applied widely in different engineering practice. To solve the problem of full-wave Fourier algorithm which is disable to filter decaying DC component and has worse frequency characteristic, it is presented an improved algorithm depending on the combination of subtraction filter and full-wave Morlet complex wavelet, to get out the fundamental wave amplitude of the current in the distribution line, by studying each parameter’s influence on the performances of Morlet complex wavelet algorithm. It can filter decaying DC component efficiently and has better frequency characteristic.

Thermal Overload Protection for AC Asynchronous Motor Based on Complex Morlet Wavelet

2015 ◽  
Vol 740 ◽  
pp. 364-367
Author(s):  
Su Wang ◽  
Lei Sun ◽  
Wei Cong Huang
Keyword(s):  
Asynchronous Motor ◽  
Morlet Wavelet ◽  
Algorithm Analysis ◽  
Full Wave ◽  
Overload Protection ◽  
Dc Component ◽  
Complex Morlet Wavelet ◽  
Fourier Algorithm ◽  
Wavelet Algorithm ◽  
Better Than

Conventionally, the fault signal of motor thermal overload in a non-periodic component is not effectively filtered with Full-wave Fourier Algorithm (or FFA). In this paper, a design which combined Complex Morlet Wavelet Algorithm with Subtraction (or CMWAS) filter is presented. The design gives system model of overload and algorithm analysis It is verified that the new algorithm is better than the FFA algorithm in terms of filtering decaying DC component.

scholarly journals Time-Frequency Analysis and Application of a Vibration Signal of Tunnel Excavation Blasting Based on CEEMD-MPE-HT

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chen-yang Ma ◽  
Li Wu ◽  
Miao Sun ◽  
Qing Yuan
Keyword(s):  
Empirical Mode Decomposition ◽  
Frequency Band ◽  
Frequency Analysis ◽  
Frequency Characteristic ◽  
Permutation Entropy ◽  
Natural Vibration Frequency ◽  
Characteristic Parameters ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Mode Decomposition

The traditional empirical mode decomposition method cannot accurately extract the time-frequency characteristic parameters contained in the noisy seismic monitoring signals. In this paper, the time-frequency analysis model of CEEMD-MPE-HT is established by introducing the multiscale permutation entropy (MPE), combining with the optimized empirical mode decomposition (CEEMD) and Hilbert transform (HT). The accuracy of the model is verified by the simulation signal mixed with noise. Based on the project of Loushan two-to-four in situ expansion tunnel, a CEEMD-MPE-HT model is used to extract and analyze the time-frequency characteristic parameters of blasting seismic signals. The results show that the energy of the seismic wave signal is mainly concentrated in the frequency band above 100 Hz, while the natural vibration frequency of the adjacent existing tunnel is far less than this frequency band, and the excavation blasting of the tunnel will not cause the resonance of the adjacent existing tunnel.

scholarly journals Adapted Wavelet Transform for Twisted Blade Diagnosis in Multi Stage Rotor

2019 ◽  
Vol 255 ◽  
pp. 02011
Author(s):  
Ahmed M. Abdelrhman ◽  
M. Salman Leong ◽  
Y.H. Ali ◽  
Iftikhar Ahmad ◽  
Christina G. Georgantopoulou ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Rotor System ◽  
Fault Detection And Diagnosis ◽  
Frequency Resolution ◽  
Time Frequency ◽  
Multi Stage ◽  
The Common ◽  
Detection And Diagnosis ◽  
Twisted Blade

This paper studies the diagnosis of twisted blade in a multi stages rotor system using adapted wavelet transform and casing vibration. The common detection method (FFT) is effective only if sever blade faults occurred while the minor faults usually remain undetected. Wavelet analysis as alternative technique is still unable to fulfill the fault detection and diagnosis accurately due to its inadequate time-frequency resolution. In this paper, wavelet is adapted and its time-frequency is improved. Experimental study was undertaken to simulate multi stages rotor system. Results showed that the adapted wavelet analysis is effective in twisted blade diagnosis compared to the conventional one.

Denoising Vibration Signals of Food Refrigerant Air Compressor Based on Wavelet Transform

2010 ◽  
Vol 439-440 ◽  
pp. 1037-1041 ◽  
Author(s):  
Yan Jue Gong ◽  
Zhao Fu ◽  
Hui Yu Xiang ◽  
Li Zhang ◽  
Chun Ling Meng
Keyword(s):  
Wavelet Transform ◽  
Frequency Characteristic ◽  
Vibration Signal ◽  
Wavelet Denoising ◽  
Signal Denoising ◽  
Denoising Method ◽  
Vibration Signals ◽  
Air Compressor ◽  
Time Frequency ◽  
Soft Threshold

On the basis of wavelet denoising and its better time-frequency characteristic, this paper presents an effective vibration signal denoising method for food refrigerant air compressor. The solution of eliminating strong noise is investigated with the combination of soft threshold and exponential lipschitza. The good denoising results show that the presented method is effective for improving the signal noise ratio and builds the good foundation for further extraction of the vibration signals.

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