Wavelet Feature of Precipitation in Quzhou Jiuhua

2013 ◽  
Vol 438-439 ◽  
pp. 1286-1289
Author(s):  
Jun Ping Liu
Keyword(s):  
Wavelet Transform ◽  
Large Scale ◽  
Arithmetic Function ◽  
Small Scale ◽  
Time Frequency ◽  
Multi Scale ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Development And Management ◽  
Periodic Changes

Wavelet transform can carry on multi-scale and multi-resolution analysis of the signal through arithmetic function such as stretching and translation and so on .In this paper, applying Morlet complex wavelet performed wavelet transform of the month precipitation time sequence of Quzhou Jiuhua station, and analyzed period on different time scales. The future precipitation was analyzed based on main periods. The result showed that month precipitation has multi-scale characteristic and the main periods of month precipitation are 5-month, 11-month and 26-month. The periodic changes on large-scale nest the periodic changes on small-scale. The wavelet analysis can process signal in time frequency domain, which provide references for development and management of water resources.

ECG Signal Denoising Algorithm Based on Optimization Wavelet Transform

2013 ◽  
Vol 706-708 ◽  
pp. 785-788
Author(s):  
Guo Shun Yuan ◽  
Li Qing Geng
Keyword(s):  
Wavelet Transform ◽  
Median Filter ◽  
Noise Removal ◽  
Signal Denoising ◽  
Time Frequency ◽  
Multi Resolution Analysis ◽  
Signal Characteristics ◽  
Eigen Values ◽  
Resolution Analysis ◽  
Ecg Noise Removal

Wavelet transform algorithm with its unique multi-resolution analysis and it is in the time - frequency domain has the advantage of the ability to characterize the local signal characteristics, let it has been widely used in signal detection, noise removal, feature extraction, image compression and so on. In this paper, on the basis of already wavelet transform ECG noise removal, proposed a median filter optimization algorithm, enables ECG noise removal effect is more obvious, also for the Eigen values detection of ECG lay a better foundation.

WAVELET MULTI-RESOLUTION ANALYSIS ON LARGE-EDDY SIMULATION OF TURBURLENT FLOW BEHIND A VEHICLE EXERNAL MIRROR

2013 ◽  
Vol 11 (04) ◽  
pp. 1360007 ◽  
Author(s):  
A. RINOSHIKA ◽  
Y. ZHENG ◽  
E. SHISHIDO
Keyword(s):  
Large Eddy Simulation ◽  
Large Scale ◽  
Three Dimensional ◽  
Wake Flow ◽  
Small Scale ◽  
Three Dimensional Flow ◽  
Eddy Simulation ◽  
Multi Resolution Analysis ◽  
Large Eddy ◽  
Resolution Analysis

The three-dimensional orthogonal wavelet multi-resolution technique was applied to analyze flow structures of various scales around an externally mounted vehicle mirror. Firstly, the three-dimensional flow of mirror wake was numerically analyzed at a Reynolds number of 105 by using the large-eddy simulation (LES). Then the instantaneous velocity and vorticity were decomposed into the large-, intermediate- and relatively small-scale components by the wavelet multi-resolution technique. It was found that a three-dimensional large-scale vertical vortex dominates the mirror wake flow and makes a main contribution to vorticity concentration. Some intermediate- and relatively small-scale vortices were extracted from the LES and were clearly identifiable.

scholarly journals Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 215
Author(s):  
Na Cheng ◽  
Shuli Song ◽  
Wei Li
Keyword(s):  
Magnetic Storm ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Ionospheric Disturbance ◽  
Ionospheric Scintillation ◽  
Small Scale ◽  
Electron Content ◽  
Total Electron ◽  
Multi Scale ◽  
Intense Storm

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.

scholarly journals Ground Penetrating Radar for Belowground Phenotyping of High-biomass Grasses for Soil Carbon Sequestration

2021 ◽  
Author(s):  
Matthew Wolfe ◽  
Da Huo ◽  
Henry Ruiz-Guzman ◽  
Brody Teare ◽  
Tyler Adams ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Carbon Capture ◽  
Large Scale ◽  
Agricultural Practices ◽  
Signal Amplitude ◽  
Belowground Biomass ◽  
Continuous Wavelet ◽  
Time Frequency ◽  
Non Invasive

Abstract AimsMany governments and companies have committed to moving to net-zero emissions by 2030 or 2050 to tackle climate change, which require the development of new carbon capture and sequestration/storage (CCS) techniques. A proposed method of sequestration is to deposit carbon in soils as plant matter including root mass and root exudates. Adding perennial traits such as rhizomes to crops as part of a sequestration strategy would result in annual crop regrowth from rhizome meristems rather than requiring replanting from seeds which would in turn encourage no-till agricultural practices. Integrating these traits into productive agriculture requires a belowground phenotyping method compatible with high throughput breeding and selection methods (i.e., is rapid, inexpensive, reliable, and non-invasive), however none currently exist. MethodsGround penetrating radar (GPR) is a non-invasive subsurface sensing technology that shows potential as a phenotyping technique. In this study, a prototype GPR antenna array was used to scan roots of the perennial sorghum hybrid, PSH09TX15. A-scan level time-domain analyses and B-scan level time/frequency analyses using the continuous wavelet transform were utilized to extract features of interest from the acquired radargrams. ResultsOf six A-scan diagnostic indices examined, the standard deviation of signal amplitude correlated most significantly with belowground biomass. Time frequency analysis using the continuous wavelet transform yielded high correlations of B-scan features with belowground biomass. ConclusionThese results demonstrate that continued refinement of GPR data analysis workflows should yield a highly applicable phenotyping tool for breeding efforts in environments where selection is otherwise impractical on a large scale.

Voltage Flicker Extraction Based on Wavelet Analysis

2013 ◽  
Vol 385-386 ◽  
pp. 1389-1393 ◽  
Author(s):  
Lin Chai ◽  
Jun Ru Sun
Keyword(s):  
Low Frequency ◽  
Matlab Simulation ◽  
Time Frequency ◽  
Multi Resolution Analysis ◽  
Voltage Signal ◽  
Time Frequency Localization ◽  
Resolution Analysis ◽  
Modulus Maximum ◽  
Voltage Flicker ◽  
Non Stationary Signal

Extracting voltage flicker from the sampling voltage signal is a precondition for management of flicker. Voltage flicker signal is a low frequency time-varying non-stationary signal. The traditional fourier transform has great limitations when analyze the non-stationary signal for not having the time resolution. As wavelet transform has good property of time-frequency localization, it become a powerful tool for analyze this kind of signal. This paper adopts multi-resolution analysis of wavelet to extract voltage flicker signal. Furthermore, according to the characteristics of wavelet function, this paper selects Daubechies wavelet to accomplish the multi-level decomposition and reconstruction of signal, in order to get the frequency and amplitude of voltage flicker signals. Based on the principle of modulus maximum, it can be determined what time the voltage flicker happen and over. The results of MATLAB simulation indicate that voltage flicker signal can be effectively extracted by wavelet multi-resolution analysis. Wavelet multi-resolution analysis is considerably ideal for voltage flicker extraction.

Coal Gangue Image Edge Detection Based on Wavelet Transform

2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Coal Gangue ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Image Edge

An edge detection algorithm is developed for coal gangue images, and the method has two advantages compared with traditional ones. Firstly, multi-resolution analysis of wavelet transform can improve the quality of edge detection. Secondly, the algorithm is faster for real time. Since the threshold directly from the coefficients of wavelet transform, the rate of recognition for coal gangue is highly raised. The experiment results show that the method is an efficient edge detection algorithm for extraction edges from the noised images of coal gangues.

A New Approach for Classification of Fault in Transmission Line with Combination of Wavelet Multi Resolution Analysis and Neural Networks

2017 ◽  
Vol 8 (1) ◽  
pp. 505
Author(s):  
Y Srinivasa Rao ◽  
G. Ravi Kumar ◽  
G. Kesava Rao
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Transmission Line ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
New Approach ◽  
The Neural Network ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

An appropriate fault detection and classification of power system transmission line using discrete wavelet transform and artificial neural networks is performed in this paper. The analysis is carried out by applying discrete wavelet transform for obtained fault phase currents. The work represented in this paper are mainly concentrated on classification of fault and this classification is done based on the obtained energy values after applying discrete wavelet transform by taking this values as an input for the neural network. The proposed system and analysis is carried out in Matlab Simulink.

Wavelet Multi-Resolution Analysis of Coherent Structure in a Jet Issuing From Rotating Circular Pipe With Inclined Section

2002 ◽  
Author(s):  
Masahiro Nakashima ◽  
Hui Li ◽  
Takahide Tabata ◽  
Tsutomu Nozaki
Keyword(s):  
Coherent Structure ◽  
Circular Pipe ◽  
Turbulent Structures ◽  
Rotating Speed ◽  
Multi Scale ◽  
The Core ◽  
Multi Resolution Analysis ◽  
Flow Feature ◽  
Resolution Analysis ◽  
Inclined Angle

The flow feature of the jet issuing from the circular pipe with the rotating inclined section has been investigated by the method of the flow visualization and the image processing. It has been found that the jet diffusion is affected by the inclined angle and the rotating speed. The coherent structure of the jet has been also studied by using the wavelet multi-resolution analysis. The multi-scale turbulent structures were visualized and the core and edge of the vortex were identified at different broad scales.

Large-Scale Assembly of Carbon Nanotubes

2004 ◽  
Author(s):  
T. El-Aguizy ◽  
Sang-Gook Kim
Keyword(s):  
Carbon Nanotubes ◽  
Carbon Nanotube ◽  
Large Scale ◽  
Small Scale ◽  
Manufacturing Processes ◽  
Micro Scale ◽  
Multi Scale ◽  
Novel Method ◽  
Functionalization Of Carbon Nanotubes

The scale decomposition of a multi-scale system into small-scale order domains will reduce the complexity of the system and will subsequently ensure a success in nanomanufacturing. A novel method of assembling individual carbon nanotube has been developed based on the concept of scale decomposition. Current technologies for organized growth of carbon nanotubes are limited to very small-scale order. The nanopelleting concept is to overcome this limitation by embedding carbon nanotubes into micro-scale pellets that enable large-scale assembly as required. Manufacturing processes have been developed to produce nanopellets, which are then transplanted to locations where the functionalization of carbon nanotubes are required.

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